Conservation and Biological Senescence in Polar Bears ... · experience. I would also like to thank Kathy Shire, Guido Stadler, Amy Lathrop, Kristen Choffe, Lori Frappier, Jennifer

Conservation and Biological Senescence in Polar Bears: Telomeres and Inuit Traditional Knowledge

by

Pamela B.Y. Wong

A thesis submitted in conformity with the requirements for the degree of Doctor of Philosophy

Ecology and Evolutionary Biology University of Toronto

© Copyright by Pamela B.Y. Wong 2017

ii

Conservation and Biological Senescence in Polar Bears:

Telomeres and Inuit Traditional Knowledge

Pamela B.Y. Wong

Doctor of Philosophy

Ecology and Evolutionary Biology University of Toronto

2017

Abstract Although noninvasive genetic surveys play an increasing role in monitoring polar bear

population dynamics, genetic methods of identifying age await development. Telomeres–

–repetitive DNA sequences at chromosome ends––may indicate biological senescence

and chronological aging. In some taxa, telomere length has been shown to decline with

chronological age, but may vary with tissue, sex, and environmental variation and even

within and among individuals of the same age. This thesis evaluates patterns of variation

in telomeres as a function of chronological age by i) developing a telomere restriction

fragment (TRF) assay in grizzly bears to examine how telomere length varies with age

sex, and stress in this taxa and ii) using a quantitative polymerase chain reaction (qPCR)

to determine how telomere length varies with tissue, age, sex, and population in harvested

polar bears. I also examine iii) Inuit methods of identifying polar bear characteristics to

enrich interpretations of these patterns and iv) Inuit perspectives of research and

management for insight into long-term community-level monitoring. TRF assays in

grizzly bears are able to detect age and sex effects on telomere length, yet these findings

are inconclusive. Future work using a larger sample can confirm these relationships. For

heart, muscle, and skin salvaged from polar bears, significant differences in telomere

length occur among populations and these involve differences in age and sex in muscle

and potentially skin. Telomeres will likely serve as a better indicator of biological versus

chronological aging. Inuit across Nunavut continue to share methods in identifying sex,

age, body size and health of encountered polar bears and their knowledge could inform

iii

polar bear surveys. Unfortunately, not all Inuit support current research and management

practices, suggesting there is a need to improve collaborative relationships. Including

Inuit in monitoring programs can highlight unique, novel methods of monitoring a high

profile at-risk species.

iv

Acknowledgments

This thesis would not have been possible without the support of my supervisors,

collaborators, friends, and family. This work was funded by the International Bear

Association Research and Conservation, Royal Ontario Museum Schad Conservation,

and Northern Scientific Training Program grants.

First and foremost, I would like to thank my supervisors, Dr. Robert Murphy and Dr.

Deborah McGregor for their immense encouragement and support for this work. Dr. Don

Jackson provided valuable insight and guidance in completing this work. I would like to

thank Dr. Peter van Coeverden de Groot for his innovative ideas and enthusiasm that

helped shaped this project, and the years of often-challenging camping trips on the arctic

tundra that inspired me on this path. I would also like to thank Markus Dyck for his

incredible advice and support both in the field and in my research endeavours in the

north.

This research would not have been possible without samples and biological data provided

by my collaborators: Dr. Marc Cattet and Gordon Stenhouse from the fRI Research

Grizzly Bear Program; Markus Dyck from the Department of Environment, Government

of Nunavut; and Toronto Metro, Albuquerque Biopark, Cleveland Metroparks,

Brookfield, Buffalo, North Carolina, SeaWorld (San Diego), and San Diego zoos. I

would also like to thank the University of Guelph Agriculture and Food Laboratory for

processing samples for this work. I would additionally like to thank Dr. Marc Cattet for

his advice on analyses for this work. I would also like to thank Natalie Erdmann for her

tremendous patience, guidance, and expertise in helping me establish my laboratory

experience. I would also like to thank Kathy Shire, Guido Stadler, Amy Lathrop, Kristen

Choffe, Lori Frappier, Jennifer Mitchell, Hitoshi Okada, Woodring Wright, John

Stinchcombe, Ina Anreiter, Brandon Campitelli, Lisa Martin, and Shu Chen for their

expertise, insight and support in developing laboratory procedures.

I would also like to thank Ikajutit (Arctic Bay), Arviat, Mayukalik (Kimmirut), and Gjoa

Haven Hunters and Trappers for their insight, experience, and recommendations that

v

developed this project, without which this work would not have been possible. I would

also like to offer a tremendous thanks to all interview participants and George Aklah,

Susie Issuqangituq, Kolola Pitsiulak, Akeego Akkidluak, Angie Akammak, Rosie

Ivunirjuk, Leah Muckpah, Rosie Porter, Hilda Panigoniak, Teddy Carter, and Louie

Kamookak. I would also like to thank Mosha Kotierk, Sheila Oolayu, and Jamal Shirley

for their helpful advice and experience.

To my Mom, Dad, Madelene, and Isaac, thank you so much for your tremendous love

and encouragement, for believing in everything that I do. I am so grateful to have a

supportive family. Thanks to my sisters and brothers who have supported me, who never

failed to remind me of the value and importance in following my dharma.

Finally, my heart is overwhelmed with the wisdom, generosity, and teachings that the

people of the north have shown me. I cannot thank you enough. This is for you.

vi

Chapter Acknowledgments

This thesis contains four co-authored manuscripts that are in preparation, in review, or

have been published in peer-reviewed journals. I obtained permission to publish these

articles from their publishers. I designed all research and analysis procedures and wrote

all resulting manuscripts. Co-authors were involved through providing samples and their

associated biological data, guidance and review, and editing.

• Chapter 2: Wong PBY, Cattet MC, Stenhouse G, Erdmann N, Murphy RW.

Telomeres as an indicator of aging and oxidative stress in grizzly bears. In

preparation.

• Chapter 3: Wong PBY, Murphy RW. Telomere variation in polar bears: the effect

of age, sex, and population in tissues harvested by Inuit hunters. In preparation.

• Chapter 4: Wong PBY, Murphy RW. 2016. Inuit methods of identifying polar

bear characteristics: potential for Inuit inclusion in polar bear surveys. Arctic. In

press.

• Chapter 5: Wong PBY, Arviat Hunters and Trappers, Ikajutit Hunters and

Trappers, Mayukalik Hunters and Trappers, Dyck MG, Murphy RW. Inuit

perspectives of polar bear research: lessons for community-based collaborations.

2016. Polar Record. Submitted.

The following independent articles were also published over the course of this research

program:

• Wong PBY. 2016. Traditional ecological knowledge and practice and Red List

assessments: guidelines and considerations for integration. Social Science for

Conservation Fellowship Programme Working Paper 2. The International Union

for Conservation of Nature. In press.

vii

• Tondu JME, Balasubramaniam AM, Chavarie L, Gantner N, Knopp JA,

Provencher JF, Wong PBY, Simmons D. 2014. Working with northern

communities to build collaborative research partnerships: perspectives from early

career researchers. Arctic 67: 419–429.

• Xia Y, Zheng Y, Miura I, Wong PBY, Murphy RW, Zeng X. 2014. The evolution

of mitochondrial genomes in modern frogs (Neobatrachia): nonadaptive evolution

of mitochondrial genome reorganization. BMC Genomics 15: 691–675.

• van Coeverden de Groot P, Wong PBY, Harris C, Dyck MG, Kamookak L, Pagès

M, Michaux J, Boag PT. 2013. Toward a noninvasive Inuit polar bear survey:

genetic data from polar bear hair snags. Wildlife Society Bulletin 37: 394–401.

• Wong PBY, Wiley EO, Johnson WE, Ryder OA, O’Brien SJ, Haussler D,

Koepfli KP, Houck M, Perelman P, Mastromonaco G, Bentley AC, Venkatesh B,

Zhang YP, Murphy RW. 2012. Tissue sampling and standards for vertebrate

genomics. GigaScience 1: 8–20.

• Wong PBY, van Coeverden de Groot P, Fekken C, Boag PT. 2011. Polar bear

(Ursus maritimus) tracking techniques of Inuit hunters: interrater reliability and

inferences on accuracy. Canadian Field Naturalist 125: 140–153.

viii

Table of Contents

Acknowledgments ........................................................................................................................... iv

Chapter Acknowledgments ............................................................................................................. vi

Table of Contents .......................................................................................................................... viii

List of Figures ................................................................................................................................. xi

List of Tables .................................................................................................................................. xii

List of Appendices ........................................................................................................................ xiii

List of Abbreviations ...................................................................................................................... xv

Introduction and context ............................................................................................................ 1 1

1.1 Telomeres as an indicator of biological and/or chronological aging .................................. 2

1.2 Methods of telomere measurement ..................................................................................... 5

1.3 Thesis objectives ................................................................................................................. 6

1.4 Synthesis of chapters .......................................................................................................... 8

Development of a telomere restriction fragment assay in grizzly bears: telomeres as an 2indicator of aging, sex, and oxidative stress .................................................................................. 10

2.1 Summary ........................................................................................................................... 10

2.2 Introduction ...................................................................................................................... 10

2.3 Development of a TRF assay ............................................................................................ 13

2.4 Results .............................................................................................................................. 16

2.5 Discussion ......................................................................................................................... 22

2.6 Appendix .......................................................................................................................... 28

A qPCR assay of telomeres comparing tissue-type, age, sex, and population in polar bears . 31 3

3.1 Summary ........................................................................................................................... 31

3.2 Background ....................................................................................................................... 32

3.3 Methods ............................................................................................................................ 35

3.3.1 QPCR in samples of wild polar bears ........................................................................ 35

ix

3.3.2 Comparisons between TRF and qPCR assays ........................................................... 40

3.4 Results .............................................................................................................................. 41

3.4.1 Telomeres in harvested polar bears based on qPCR ................................................. 41

3.4.2 Comparisons between TRFs and T/S ........................................................................ 55

3.5 Discussion ......................................................................................................................... 56

3.6 Appendix .......................................................................................................................... 62

3.6.1 Development of a TRF assay of captive (zoo) polar bear samples ........................... 62

3.6.2 Supplementary analyses ............................................................................................ 65

3.6.3 Age, sex, and stress effects on grizzly bear telomere length using qPCR ................. 67

3.6.4 QPCR data and standard curves for six telomere and reference primer plates ......... 71

3.6.5 Model selection for telomere length .......................................................................... 97

Inuit methods of identifying polar bear characteristics: potential for Inuit inclusion in polar 4bear surveys .................................................................................................................................... 99

4.1 Summary ........................................................................................................................... 99

4.2 Polar bear conservation and harvest management in Nunavut ......................................... 99

4.3 Methods .......................................................................................................................... 103

4.4 Results ............................................................................................................................ 108

4.4.1 Hunter preference for bear characteristics ............................................................... 110

4.4.2 Methods of identifying polar bear characteristics ................................................... 114

4.5 Discussion ....................................................................................................................... 127

4.5.1 The role of Inuit methods of identifying polar bear characteristics in monitoring programs ............................................................................................................................... 127

4.5.2 Comparisons between Inuit methods of identifying characteristics and science .... 129

4.5.3 The role and persistence of Inuit knowledge in polar bear management ................ 131

4.5.4 Barriers to Inuit inclusion in polar bear research .................................................... 133

4.6 Appendix ........................................................................................................................ 135

4.6.1 Participant responses to interview questions ........................................................... 135

x

Inuit perspectives of polar bear research: lessons for community-based collaborations ...... 141 5

5.1 Summary ......................................................................................................................... 141

5.2 Background ..................................................................................................................... 141

5.3 Methods .......................................................................................................................... 145

5.4 Results ............................................................................................................................ 146

5.4.1 Cultural factors affecting participant responses to research questions .................... 147

5.4.2 Inuit observations of polar bear ecology ................................................................. 149

5.4.3 Management perspectives and recommendations for polar bear research .............. 152

5.5 Discussion ....................................................................................................................... 158

5.5.1 Lessons learned from community-based interactions ............................................. 158

5.5.2 Overlaps between polar bear TEK with science and other TEK studies ................. 160

5.5.3 Challenges and considerations for polar bear monitoring and research methods ... 162

5.5.4 Concluding remarks for northern community-based research ................................ 165

Synthesis of chapters and concluding discussion .................................................................. 168 6

6.1 Summary of chapters ...................................................................................................... 168

6.2 Telomeres as an indicator of biological senescence ....................................................... 169

6.3 Inuit methods of estimating polar bear health as potential indicators of biological senescence ................................................................................................................................ 172

6.4 Conclusions .................................................................................................................... 173

References .................................................................................................................................... 175

xi

List of Figures

Figure 1. A sample TRF gel of 18 grizzly bear samples showing a sample analysis window ....... 19

Figure 2. Non-significant and significant linear regressions of age on mean TRF length (in kilobase pairs) in 14 males and seven females, respectively ............................................................ 20

Figure 3. A sample gel showing little to no signal in samples with compared to samples without BAL-31 exonuclease digestion ................................................................................................................... 21

Figure 4. A graph showing a significant model II regression between mean TRF length with and without BAL-31 exonuclease digestion in nine grizzly bear samples ........................................... 22

Figure 5. A map showing distributions of Nunavut communities among 16 of 19 global polar bear populations (Laptev, Kara, and Barents Sea populations not shown) ........................................... 35

Figure 6. A graph of a significant model II regression between heart and muscle T/S in 39 polar bears .................................................................................................................................................................... 44

Figure 7. A graph of a significant model II regression between heart and skin T/S in 40 polar bears. ................................................................................................................................................................... 45

Figure 8. A graph of a significant model II regression between muscle and skin T/S in 39 polar bears .................................................................................................................................................................... 46

Figure 9. A graph showing significant differences in heart T/S across polar bear populations ..... 48

Figure 10. A box plot comparing muscle T/S among age groups in 10 females (F) and 30 males (M). ...................................................................................................................................................................... 50

Figure 11. A graph showing significant differences in muscle T/S across polar bear populations. ............................................................................................................................................................................... 53

Figure 12. A qualitative comparison of heart, muscle, and skin T/S across communities ............... 54

Figure 13. A graph of a non-significant model II regression between mean TRF length and blood T/S measured in 14 grizzly bears .............................................................................................................. 56

Figure 14. A map displaying Gjoa Haven (1), Kugaaruk (2), Arctic Bay (3), Kimmirut (4), and Arviat (5) communities where participants were interviewed for this study ............................ 106

xii

List of Tables

Table 1. A general linear model for the effect of age, sex, HCC, GGT, and the interaction between age and sex on mean TRF length in 21 grizzly bears ........................................................ 18

Table 2. Linear regressions for the effect of age on mean TRF length in 14 male and seven female grizzly bears. .................................................................................................................................................... 18

Table 3. A one-way analysis of variance using type III sums of squares showing significant differences in heart T/S among Baffin Bay (N=10), Davis Strait (N=6), Foxe Basin (N=5), Lancaster Sound (N=9), and Western Hudson Bay (N=10) polar bear populations. ............... 47

Table 4. A multi-factor analysis of variance using type III sums of squares showing significant effects of age, sex, population, and the interaction between age and sex on muscle T/S in 39 polar bears. ........................................................................................................................................................ 49

Table 5. One-way analyses of variance using type III sums of squares showing non-significant differences in muscle T/S among age groups in 29 male and 10 female polar bears. ............. 49

Table 6. A multi-factor analysis of variance using type III sums of squares showing non-significant effects of age, sex, and the interaction between age and sex and a significant effect of population on skin T/S in 40 polar bears. .............................................................................. 52

Table 7. Interview guideline. .............................................................................................................................. 107

Table 8. Number of interview participants from Gjoa Haven, Arctic Bay, Kimmirut, and Arviat corresponding to participant type, hunting experience, and having mentioned experience guiding sport hunts during interviews .................................................................................................... 110

xiii

List of Appendices

Appendix 1. Mean TRF length in 21 grizzly bears corresponding to mean TRF length, age, sex, and measurements of stress hormones (hair cortisol concentration [HCC] and serum gamma-glutamyltransferase [GGT]). ....................................................................................................................... 28

Appendix 2. Akaike Information Criterion (AIC) and difference in AIC compared to the most parsimonious model for models of mean TRF length in 21 grizzly bears ................................... 29

Appendix 3. Mean TRF length in 9 grizzly bears corresponding to mean TRF length with BAL-31 exonuclease treatment, digesting terminal telomere sequences. ..................................................... 30

Appendix 4. A TRF gel of polar bears samples provided by zoos. Samples are labeled at the top of each lane, as well as a negative control .............................................................................................. 64

Appendix 5. Results from non-significant paired t-tests comparing T/S among polar bear heart, muscle, and skin tissues (N=40, 39, and 40 individuals, respectively). ........................................ 65

Appendix 6. A one-way analysis of variance using type III sums of squares showing the significant effect of population on heart T/S in 39 polar bears (one outlier was excluded from the original sample of 40). ........................................................................................................................... 65

Appendix 7. A multi-factor analysis of variance using type III sums of squares showing significant effects of age, sex, population, and the interaction between age and sex on muscle T/S in 38 polar bears (one outlier was excluded from the original sample of 39). ................... 66

Appendix 8. Blood T/S measured from qPCR and mean TRF length (in kilobase pairs) measured from TRF assays in 17 grizzly bear samples (nine males and eight females) ............................ 68

Appendix 9. A general linear model for the effect of age, sex, HCC, GGT, and the interaction between age and sex on blood T/S in 17 grizzly bears. Effects were not significant. ............. 69

Appendix 10. A graph showing non-significant linear regressions between blood T/S and age in 17 grizzly bears ................................................................................................................................................ 70

Appendix 11. Polar bear samples collected by Inuit hunters for qPCR corresponding to community that provided the sample, population where the sample was harvested, age, and sex diagnoses .................................................................................................................................................... 71

Appendix 12. Cycle threshold values (Ct) for Plate 1 of 6 telomere (telc/telg) and reference (RPLP0-F1/RPLP0-R1) qPCR assays ..................................................................................................... 73



xiv



Appendix 17. Cycle threshold values (Ct) for Plate 6 of 6 telomere (telc/telg) and reference (RPLP0-F1/RPLP0-R1) qPCR assays. .................................................................................................... 91

Appendix 18. Melt curves for seven dilutions ranging from 0.0064 to 10ng per reaction in duplicate (14 reactions) showing a single peak, confirming specificity of telomere (telc/telg) primers. ............................................................................................................................................................... 94

Appendix 19. Melt curves for seven dilutions ranging from 0.0064 to 10ng per reaction in duplicate (14 reactions) generally showing a single peak, confirming specificity of reference (RPLP0-F1/RPLP0-R1) primers. ............................................................................................................... 96

Appendix 20. Characteristics of standard curves six telomere (telc/g) and reference (RPLP0 [F1/R1]) qPCR plates .................................................................................................................................... 97

Appendix 21. Akaike Information Criterion (AIC) and difference in AIC compared to the most parsimonious model (ΔAIC) for models of heart T/S in 40 polar bears ...................................... 97

Appendix 22. Akaike Information Criterion (AIC) and difference in AIC compared to the most parsimonious model (ΔAIC) for models of muscle T/S in 39 polar bears .................................. 98

Appendix 23. Akaike Information Criterion (AIC) and difference in AIC compared to the most parsimonious model (ΔAIC) for models of skin T/S in 40 polar bears ........................................ 98

xv

List of Abbreviations

AB Arctic Bay

AIC Akaike Information Criterion

ANOVA analysis of variance

AR Arviat

BB Baffin Bay

Ct cycle threshold

CV coefficient of variation

DS Davis Strait

EDTA ethylenediaminetetraacetic acid

FB Foxe Basin

GH Gjoa Haven

HCC hair cortisol concentration

HSD Honest Significant Difference

HTO Hunters and Trappers Organization

INAC Indian and Northern Affairs Canada

IQ Inuit qaujimajatuqangit

K Kimmirut

KU Kugaaruk

GGT serum gamma glutamyltransferase

LS Lancaster Sound

PCR polymerase chain reaction

qPCR quantitative polymerase chain reaction

T/S telomere repeat to single copy gene ratio

TEK traditional ecological knowledge

TRF telomere restriction fragment assay

WHB Western Hudson Bay

1

Chapter 1

Introduction and context 1

Polar bear responses to climate-induced habitat changes have been uncertain and subject

to debate among scientific (Dyck et al. 2007, Stirling et al. 2008) and Inuit (Dowsley

2009a) communities. The absence of range-wide data on population size and sustainable

harvest rates may explain these uncertainties (Peacock et al. 2011, Vongraven and

Peacock 2011). Conservation and management of polar bears are based on aerial mark-

recapture surveys of 19 populations defined by a combination of landscape patterns

(Ferguson et al. 1998), genetic differences (Paetkau et al. 1999), and movements of

individuals (Taylor et al. 2001). While useful for projecting sex and age distributions,

mark-recapture surveys are invasive, expensive (Dowsley 2009a), and infrequently

implemented (Peacock et al. 2011). Polar bears from these studies are aged from tooth

growth patterns that vary in accuracy and precision (Christensen-Dalsgaard et al. 2010).

Less-invasive, remote biopsy dart surveys facilitate genetic sexing and genotyping of

individual bears (Wong et al. 2011, Van Coeverden de Groot et al. 2012, Pagano et al.

2014). However, molecular-based methods of age estimation await development.

Age distributions are necessary to predict survival and recruitment (reproductive)

rates (Taylor et al. 2006, Regehr et al. 2007, Hunter et al. 2010) and impacts of

harvesting (McLoughlin et al. 2005, Taylor et al. 2005, Taylor et al. 2008) that together

inform conservation and management policies. The ability to detect rapid changes in age

structure is also critical to monitor long-term impacts of hunting selection on population

dynamics, ensure sustainable yields, and avoid reductions in desirable phenotypes

(Allendorf et al. 2008, Allendorf and Hard 2009). For most long-lived, polygynous

species, harvesting more males than females can presumably evade decreases in

fecundity and protecting young animals can ensure chances of survival to reproduction

(Caughley and Sinclair 1994). In Nunavut, polar bears are harvested at a 2:1 male to

female ratio to protect females and cubs (Taylor et al. 2008, Peacock et al. 2011). While

hunter-selected phenotypes (e.g., large body sizes, fur quality) may correspond to age and

2

sex, it is critical to understand the drivers of hunter selection and the means of accurately

identifying these population parameters, especially for harvested animals.

1.1 Telomeres as an indicator of biological and/or

chronological aging

Over 300 theories of why aging occurs have been proposed yet no theory alone is

sufficient (Medvedev 1990, Kirkwood et al. 2005). A holistic understanding of the

multiple intra- and inter-individual aging phenotypes in nature is inherently complex and

requires an integration of evolutionary and physiological perspectives (Medvedev 1990,

Kirkwood et al. 2005). From an evolutionary standpoint, a question of interest is how and

why forces of selection have not eliminated aging (Medvedev 1990). An explicit theory

was put forth by Medawar (1952) who synthesized ideas from Fisher (1930) and Haldane

(1941), which posits that aging occurs as a result of mutation accumulation; forces of

selection for long life-span weaken with age due to accumulating deleterious mutations

expressed at older ages. Williams (1957) suggested aging might be explained by

antagonistically pleiotropic genes that, while incurring deleterious effects in older

individuals, are maintained due to their contributions to the survival and fecundity of

younger individuals. Kirkwood (1977) proposed an integrative, evolutionary-

physiological theory that posits that organisms must optimize a balance between

maintaining the soma (e.g., against wear-and-tear associated with life itself) and other

activities that maximize Darwinian fitness (e.g., reproduction). In other words, organisms

must allocate limited resources toward activities that minimize versus contribute to aging.

The associated age-related trade-offs should also reflect extrinsic mortality risks (e.g.,

nutrient availability, predation, competition, etc.), which together underlie determinants

of longevity (Ricklefs 1998, Kirkwood 2005, Eisenberg 2010). For example, an

individual would benefit from investing any available energy beyond what is required to

physiologically maintain a reasonable chance of survival in the wild into reproduction,

rather than somatic maintenance, in an environment with high extrinsic risks of mortality.

The free radical theory of aging explains this trade-off. It posits that cellular damage from

reactive oxygen species over time or in response to stress contributes to cellular

3

dysfunction and death (Harman 1956, Kirkwood and Kowald 2012). As a stress response,

reactive oxygen species allow organisms to mobilize energy toward efforts that

encourage immediate survival (e.g., increasing foraging effort and food access in stressful

environments [Romero 2004]), at the expense of biological integrity (Shigenaga et al.

1994, Monaghan et al. 2009). These theories of aging refer to biological senescence,

defined here as progressive physiological deterioration (wear-and-tear) and, hence,

increase in mortality risk (Kirkwood 2005), whereas chronological aging refers to an

external measure of time (since birth).

Telomere attrition may serve as one proximate mechanism that mediates the

trade-off between self-maintenance, or prolonging lifespan, and aging. Telomeres are

repetitive guanine-rich DNA sequences (5’-[TTAGGG]n-3) associated with structural and

regulatory proteins with a 3’ single-stranded overhang at the ends of chromosomes

(Blasco 2005, de Lange et al. 2010, Dunshea et al. 2011, Gomes et al. 2011). Telomeres

shorten with cell division due to the inability of DNA replication machinery (DNA

polymerase) to replicate terminal ends of linear chromosomes (Monaghan and

Haussmann 2006, de Lange et al. 2010, Eisenberg 2010). This progressive shortening

eventually leads to cellular senescence––impairing cell and/or tissue function through the

alteration of gene expression and accumulation of senescent cells, respectively––and

hence aging phenotypes and individual death (Harley et al. 1990; Monaghan and

Haussmann 2006, Dunshea et al. 2011). Telomeres serve as functionally important

“caps” at the ends of chromosomes to protect genome integrity against DNA replication.

Telomeres also protect DNA from oxidative degradation and recognition of chromosomal

ends as double-stranded breaks, which initiates detrimental DNA repair responses

(Harley et al. 1990, Monaghan and Haussmann 2006, Dunshea et al. 2011). Telomeres

are particularly prone to oxidative damage as oxidative intermediates (reactive oxygen

species) preferentially target guanine triplets (GGG) and DNA damage repair is less

efficient along telomeres than along interstitial regions of DNA (Shay and Wright 2007).

Telomere maintenance and elongation occurs by activating the enzyme

telomerase (a reverse-transcriptase enzyme with an RNA template component) or

4

alternative lengthening mechanisms, such as homologous recombination between

telomeres (de Lange et al. 2006, Blasco 2007). Long telomeres are advantageous because

they maximize cell proliferation potential, particularly in tissues where cell regeneration

is needed, for example, in blood cells (lymphocytes) that are required for immune

function (Kaszubowska 2008). However, long telomeres are costly—requiring energy

and resources—to maintain through cell division (de Lange et al. 2006, Kaszubowska

2008, Eisenberg 2010). Continuous cell division associated with long telomere lengths

may also incur damaging (e.g., cancerous) effects (Aviv 2006, Monaghan and

Haussmann 2006, Eisenberg 2010, Gomes et al. 2011). Telomerase activity and

alternative lengthening pathways are activated only in embryonic and germ-line cells—

tissues vital to survival and fecundity—and are generally rare or inactive in most somatic

cells (de Lange et al. 2006, Dunshea et al. 2011).

While evidence for a relationship between telomere length and chronological age

exist, several factors caution against the use of telomere length to predict chronological

age (Horn et al. 2010, Dunshea et al. 2011, Nussey et al. 2014). Evidence for telomere

shortening leading to cellular senescence in humans has been reported extensively

(Harley et al. 1990, de Lange et al. 2006, Eisenberg 2010). Research across taxa––for

example, primates (Herbig 2006), birds (Haussmann et al. 2003, Bize et al. 2009), fish

(Horn et al. 2008), reptiles (Scott et al. 2006, Hatase et al. 2008, Olsson et al. 2011, Plot

et al. 2012), sea lions (Izzo 2011), and whales (Olsen et al. 2014), as well as domestic

sheep, cattle, mice, and dogs (Haussman et al. 2002)––reveal an effect of chronological

age on telomere length. Telomere length has also been linked to survival (by re-sampling

individuals across time; e.g., Foote et al. 2010), lifespan (e.g., Heidinger et al. 2012)

and/or fecundity (e.g., clutch size; Scott et al. 2006, Voillemot et al. 2012, Bauch et al.

2013). However, variation in telomere length among (e.g., Vleck et al. 2003, Juola et al.

2006, Hewakapuge et al. 2008) and within (e.g., Prowse and Greider 1995, Betts et al.

2001, Lin et al. 2010) individuals of the same age across some taxa suggest telomere

patterns may serve as a more appropriate indicator of biological versus chronological

aging. For example, short telomeres have been linked to diseases that increase mortality

such as heart (Oh et al. 2003) and liver (Wiemann et al. 2002) failure and obesity (Valdes

5

et al. 2005), as well as psychological health disorders (e.g., Epel et al. 2004). Telomere

lengths may also vary with tissue-type (Mather et al. 2010), sex (Blasco 2007, Barrett

and Richardson 2011), environment (Monaghan 2010), and/or maternal/paternal

inheritance (Eisenberg 2010, Olsson et al. 2011). Attempts to quantify these patterns in

vivo in ursids—and large carnivores in general––are lacking (but see Lewin et al. 2015,

Beirne et al. 2016).

1.2 Methods of telomere measurement

The “gold standard” of measuring telomeres is the telomere restriction fragment (TRF)

method (Horn et al. 2010, Monaghan 2010, O’Callaghan et al. 2011). TRF assays involve

digesting DNA with restriction enzymes that do not cut within the telomere sequence

(Dunshea et al. 2011, Gomes et al. 2011) and separating the DNA fragments through gel

electrophoresis (Kimura et al. 2010). As restriction enzymes cleave DNA at various

distances from the telomere and telomere lengths vary across all chromosomes, a smear is

produced versus a sharp band to calculate mean telomere length (Juola et al. 2006, Horn

et al. 2010). Telomeres are then detected by hybridizing denaturing probes to telomeric

sequences that have been separated into single strands (Kimura et al. 2010) or non-

denaturing probes to the 3’ single-stranded overhang of telomeres (Herbert et al. 2003);

the latter protocol is applicable for species with interstitial telomeric repeats in non-

telomeric regions of DNA (Herbert et al. 2003). On the one hand, TRF assays are

attractive as they allow for analyses of telomere length distributions across all

chromosomes (Haussmann and Mauck 2008), where mean telomere length measurements

can provide inferences on general phenotypes (e.g., somatic fitness; Aviv 2006). On the

other hand, TRF assays are time-consuming and require large amounts of DNA (from

2µg for denaturing to 10µg for nondenaturing protocols; Monaghan 2010, Dunshea et al.

2011). TRF assays can also vary in choice of restriction enzymes, probes and

hybridization targets, quantification methods, and the analysis window selected (Horn et

al. 2010). Alternative methods based on fluorescent in situ hybridization (FISH) and

polymerase chain reaction (PCR) have been developed, yet FISH (e.g., quantitative or

flow FISH) and some PCR-based (e.g., single telomere length analysis) methods are

6

expensive and require expert knowledge of the associated equipment and protocols

(Nakagawa et al. 2004, Kimura et al. 2010, Dunshea et al. 2011, Montpetit et al. 2014).

Real time quantitative PCR (qPCR; Cawthon 2002, Cawthon 2009) is attractive

because it requires small initial DNA quantities to generate high-throughput data (Kimura

et al. 2010, Dunshea et al. 2011). Using estimates of telomere repeat quantities (T) in

relation to a single copy reference gene (S) across chromosomes and cells, this technique

determines a relative telomere length estimate expressed as a ratio (T/S; Cawthon 2002,

Cawthon 2009, Monaghan 2010). Telomere and reference quantities are determined using

a standard linear curve, which is derived from serial dilutions of a standard (high quality)

sample of known quantity, in relation to the threshold number of cycles that is required to

detect a fluorescent signal released by the amplified products (Ct; Bustin et al. 2009,

Bustin et al. 2013). Larger quantities of a target sequence (longer telomeres) require

fewer cycles for fluorescence detection. For singleplex methods (Cawthon 2002),

variation in telomere and/or single copy gene PCR efficiency influences reliability in the

resulting measurements (Horn et al. 2010, Dunshea et al. 2011) and T/S calculations

must incorporate efficiency (for each reaction plate and primer; Pffafl 2001). While

recent advances allow for multiplex (Cawthon 2009) and absolute quantification

(O’Callaghan et al. 2011) techniques, multiple methods of baseline corrections for qPCR

outputs (Ruitjer et al. 2009) and quantification (Pffafl 2009, Olsen et al. 2012) result in

several possible combinations of telomere measurement procedures (Horn et al. 2010,

Nussey et al. 2014). Any telomere measurement technique must be selected and

optimized according to the resources that are available and the life-history of the species

(Montpetit et al. 2014, Nussey et al. 2014).

1.3 Thesis objectives

At a proximate level, genetic and environmental components shape individual

physiological functioning that may ultimately determine an organism’s life span. In

conservation contexts, understanding the factors that contribute to biological senescence

can provide insight into external mortality risk and population persistence. Using

7

telomeres as an indicator of biological senescence, this thesis examines telomere length

variation as a function of tissue type, chronological age, sex, stress, and environmental

differences using a combination of TRF and qPCR assays. Specifically, I address the

following questions:

• How does telomere length vary with age, sex, and indicators of stress, using a

TRF assay in grizzly bears (Chapter 2)?

• How does telomere length vary with tissue-type, age, sex, and population in

harvested polar bears, using a qPCR assay (Chapter 3)?

Polar bear samples were provided through a community-level, harvest-monitoring

program in Nunavut. To enrich my scientific findings, determine conservation relevance

for management applications, and explore capacity for long-term community-level

collaborative research programs, my thesis includes a qualitative, multidisciplinary

approach to also examine the following topics:

• Inuit methods of identifying polar bear age, sex, body size, and health and the role

of Inuit knowledge in polar bear surveys (Chapter 4).

• Inuit perspectives of and recommendations for polar bear research and

management (Chapter 5).

By addressing these questions, my research not only evaluates telomeres as a marker of

biological aging, but also includes Inuit traditional ecological knowledge (TEK) of polar

bears as a complementary approach to monitoring and conserving threatened species.

While including Inuit experience and perspectives highlights considerations for polar

bear research, monitoring, and management that would not be available through science

alone, TEK offers different and unique interpretations of ecological information than

those based on standard Western scientific methods. In these contexts, my research uses

novel, multidisciplinary methods to link scientific and Inuit knowledge of polar bear

ecology to examine the multiple factors that are involved in biological aging.

8

1.4 Synthesis of chapters

In Chapter 2, I report on efforts to develop a TRF assay using wild grizzly bear samples

that were collected by collaborators from the University of Saskatchewan (M. Cattet) and

Foothills Research Institute (G. Stenhouse) during independent, routine mark-recapture

surveys in 2012 and 2013. Due to relative ease in collecting and storing high quality

grizzly bear samples required for genetic analysis (e.g., fresh blood frozen at -80°C;

Wong et al. 2012) and TRF assays (Kimura et al. 2010), this work serves to initially

characterize telomeres as a marker of aging in ursids. I also explore potential effects of

oxidative stress on telomeres. I test the null hypothesis that age, sex, and indicators of

acute and chronic stress on grizzly bears do not affect telomere length.

In Chapter 3, I describe a qPCR assay of salvaged polar bear heart, muscle, and

skin samples from the same wild individuals provided by Government of Nunavut

Department of Environment collaborators (M. Dyck). These samples do not yield

sufficient DNA quality for TRF assays and, thus, I use qPCR to explore the feasibility of

conducting telomere assays using harvest samples. I test the null hypotheses that telomere

lengths do not differ with tissue-type and across age, sex, and population groups in

different tissues for polar bears.

The inclusion of Inuit TEK of polar bears can enrich scientific findings, ensure

social and policy relevance, and, more importantly, reveal novel ecological perspectives

and monitoring techniques that are not available through conventional scientific methods.

In Chapter 4, I summarize and report Inuit methods of identifying polar bear sex, age,

body size, and health across four Nunavut communities. While Inuit experiences provide

insight into hunter selection and polar bear ecology and behaviour, Inuit methods of

identifying individual characteristics can provide rapid, inexpensive population

information.

As relationships with Inuit communities are necessary to sustain long-term

research collaborations and monitoring programs, as well as encourage support for

9

research outputs (e.g., management decisions), in Chapter 5 I report Inuit experiences

with polar bears and management perspectives. These interviews provide Inuit with the

opportunity to voice their perspectives and concerns, independently from science.

In chapter 6, I summarize major findings and their implications, and discuss

opportunities to build on this research. I discuss scientific and Inuit methods of tracking

biological senescence in polar bears. I also highlight alternative scientific approaches and

potential applications of this work within the context of polar bear monitoring and

management.

10

Chapter 2

Development of a telomere restriction fragment 2

assay in grizzly bears: telomeres as an indicator

of aging, sex, and oxidative stress

2.1 Summary

Accurate and reliable life-history information in addition to data on population dynamics

is critical for grizzly bear management and conservation. As in polar bears (and other

large carnivores of conservation concern), genetic-based methods of collecting these data

are particularly attractive because they are based on noninvasive sampling techniques.

Currently, methods of determining age are still not developed for noninvasive tissues;

telomeres could serve as a biomarker of aging. I report on efforts to develop the first

telomere restriction fragment measurement assay in wild grizzly bears—and ursids in

general—to determine the effect of age, sex, and indicators of stress (hair cortisol [HCC]

and serum gamma-glutamyltransferase [GGT] concentration) on mean telomere length in

21 (14 male and seven female) individuals ranging from 1.4 to 15.7yr old. Sex, HCC and

GGT effects were not significant, though age effects were significant overall. Age effects

were not significant in males but significant in females, who showed a slight increase in

telomere length with age (0.21kb per year). These results are inconclusive due to small

sample sizes and high inter-assay variation (17.80%). Further investigation is warranted

in a larger sample size with the inclusion of additional life-history data, where telomeres

might be more appropriately used to implicate biological senescence versus chronological

age.

2.2 Introduction

Understanding population dynamics as they relate to human activities, ecological and

environmental changes, and management programs is critical for grizzly bear (Ursus

11

arctos) conservation and management (Coleman et al. 2013, Boulanger and Stenhouse,

2014). Grizzly bears are vulnerable to population declines due to their late maturation,

low density of occurrence, large geographic range sizes and low reproductive rates

(Woodruffe 2000, Garshelis et al. 2005, Whittington and Sawaya 2015). Grizzly bear

populations have declined substantially across their range in North America (Mattson and

Merrill 2002, Laliberte and Ripple 2004). In Alberta, where grizzly bears are currently

listed as a threatened species (Alberta Sustainable Resource Development and Alberta

Conservation Association 2010), human-induced mortalities are believed to be the

highest contributing factor to population decline and vulnerability (Nielsen et al. 2004,

Proctor et al. 2012, Apps et al. 2015). At a broad scale, anthropogenic development (e.g.,

resource extraction activities, including oil and gas exploration, timber harvesting, and

mining [Nielsen et al. 2004]) has fragmented habitats (Proctor et al. 2012). At smaller

scales, human-induced mortalities near development sites are frequent due to human-bear

interactions (e.g., human-bear conflicts, legal and illegal harvesting, and bear-vehicle

collisions [Apps et al. 2015]). Human development and exploitation within the broad

range of this species are expected to persist if not increase in the future (Nielsen et al.

2004; Stelfox et al. 2005, Roever et al. 2008, Apps et al. 2015), which will likely

contribute to sink populations (high death and emigration rates; Donovan and Thompson

2001, Naves et al. 2003) and further reduce survival (Garshelis et al. 2005). Indeed, there

is a need for wildlife managers to monitor bear populations in a frequent and cost-

effective way.

For grizzly bears, monitoring life-history traits (e.g., survival and recruitment) in

addition to population growth and occurrence is necessary to identify core habitats of

conservation value and sites of high mortality risk (Naves et al. 2003), as descriptions of

species-occurrence alone do not imply habitat relationships (Nielsen et al. 2003, Nielsen

et al. 2006, Doak and Cutler 2014). Data that can predict population parameters (e.g., sex

and age structure, and morphometry) have been collected through mark-recapture surveys

(e.g., Nielsen et al. 2013, Stenhouse and Graham 2013), telemetry studies (e.g., Mace et

al. 2012, Bourbonnais et al. 2014), and published occupancy records (e.g., government

management databases) as they relate to habitat occurrence (Nielsen et al. 2002, Naves et

al. 2003, Nielsen et al. 2003, Posillico et al. 2004, Nielsen et al. 2006). However, capture

12

and handling of bears is not always favourable due to their potential long-term effects on

physiology and behaviour (Cattet et al. 2003, Arnemo et al. 2006, Cattet et al. 2008a,

Cattet et al. 2008b). Noninvasive alternatives have been developed to estimate population

size and growth (Woods et al. 1999, Mowat and Strobeck 2000, Boulanger et al. 2004,

Macbeth et al. 2010, Sawaya et al. 2012, Rovang et al. 2015, Apps et al. 2015) using

genetic methods of identifying individual (e.g., Paetkau 2003) and sex (e.g., Woods et al.

1999) of bears, as well as parent-offspring relationships (Apps et al. 2015), and by using

endocrine indicators of stress and reproduction (Macbeth et al. 2010, Bryan et al. 2014).

These methods are attractive because they do not require capturing bears, yet can also be

used to link spatial distribution to habitat (e.g., anthropogenic and topographic) features

(Apps et al. 2004, Apps et al. 2015, Rovang et al. 2015). Despite the above, genetic-

based methods of identifying age and stress of individuals have not been developed for

grizzly bears. Current methods of age estimation are based on cementum analysis of pre-

molar teeth extracted during physical capture (Stoneberg and Jonkel 1966, Stenhouse and

Graham 2013). Methods of quantifying stress are based on measuring hormone

concentrations in biological samples, for example, hair snags and blood (Möstl and Palme

2002, Cattet et al. 2003, Macbeth et al. 2010, Beaulieu and Constantini 2014).

Telomeres could serve as a marker of chronological age (Harley et al. 1990,

Haussmann et al. 2002, de Lange et al. 2006, Herbig 2006, Scott et al. 2006, Hatase et al.

2008, Horn et al. 2008, Bize et al. 2009, Eisenberg 2010, Izzo et al. 2011, Olsson et al.

2011, Olsen et al. 2014) and also stress exposure. One response to stress is to stimulate

the hypothalamic-pituitary-adrenal axis to release stress hormones (e.g., glucocorticoids),

which in turn stimulate metabolic responses toward immediate survival (Macbeth 2010,

Beaulieu and Constantini 2014). This results in an increase in the production of reactive

oxygen species as a by-product of mitochondrial metabolism (Mabeth 2010, Beaulieu and

Constantini 2014). Telomeres are particularly prone to oxidative damage by reactive

oxygen species (von Zglinicki 2002, Epel et al. 2004) and indicators of acute (e.g., serum

gamma-glutamyl transferase [Cattet et al. 2003]) and chronic (e.g., hair cortisol [Macbeth

et al. 2010, Beschøft et al. 2011]) oxidative stress could contribute to telomere shortening

(Shalev et al. 2013, Gotlib et al. 2015).

13

To evaluate telomeres as a potential marker of aging and stress in ursids, I report

on efforts to develop a telomere restriction fragment (TRF) assay in grizzly bears of

known age and sex. Tissues of high quality and replicative potential (e.g., fresh, whole

blood) are critical for this initial work (Nussey et al. 2014) prior to applications in other

(e.g., noninvasively) collected tissues. This method has potential to provide inferences on

biological senescence in polar bears, as well as other ursids of conservation concern.

2.3 Development of a TRF assay

The fRI Research Grizzly Bear Program collected whole blood samples from grizzly

bears during independent mark-recapture surveys in 2012 and 2013 (Stenhouse and

Graham 2013). Samples were collected from wild individuals between Grand Prairie and

Grande Cache, Alberta, in an area known as the Grande Cache Bear Management Area

(Stenhouse and Graham 2013). Individuals were captured via remote drug delivery from

ground or helicopter or by culvert traps fitted with satellite trap alarm systems. Cattet et

al. (2008) detailed capture and handling procedures. Animals were sexed visually and

aged by extracting a premolar tooth and counting cementum annuli (Stoneberg and

Jonkel 1996, Stenhouse and Graham 2013). Age was calculated based on the assumption

that all animals were born on January 1st, and converted to a continuous variable (ordinal

day of capture divided by 365 days). Recaptured individuals were identified by detection

of a transponder (microchip), with a unique alphanumeric code that was inserted by

subcutaneous injection at first capture. Each blood sample was also associated with

serum gamma-glutamyltransferase (GGT; Cattet et al. 2003) and hair cortisol (HCC)

concentration measurements as indicators of acute and chronic oxidative stress,

respectively (Macbeth et al. 2010, Bechøft et al. 2011, Cattet et al. 2014). Cattet et al.

(2003) and Cattet et al. (2014) detailed methods for GGT and HCC quantification. For

TRF assays, from 3 to 6ml of blood was collected from the medial saphenous or jugular

vein by venipuncture, transferred to a vacutainer (BD Vacutainer®, BD Diagnostics,

Preanalytical Systems, Franklin Lakes, NJ, USA) containing ethylenediaminetetraacetic

acid (EDTA) as a preservative, and then stored at -80°C until processing.

14

I isolated genomic DNA from blood samples using a Gentra Puregene Blood

extraction kit (QIAGEN 158389) following manufacturer’s instructions at the University

of Toronto (J. Stinchcombe Lab). I ran the DNA samples out on 1% (w/v) agarose gels to

ensure they were of sufficient quality (no evidence for degradation; Kimura et al. 2010)

at the Royal Ontario Museum Laboratory of Molecular Systematics and quantified them

using a Nanodrop spectrophotometer (University of Toronto M. Sokolowski Lab). To

avoid degradation due to repeated freeze-thaw, I divided samples into 2µg aliquots before

storage at -20°C for TRF assays.

I set up TRF assays at the Royal Ontario Museum Laboratory of Systematics;

subsequent labeling, hybridization, and visualization occurred at Princess Margaret

Hospital Ontario Cancer Institute (H. Okada Lab) or University of Toronto (L. Frappier

Lab). TRF assays followed a modification of Kimura et al. (2010)’s Southern blot

analysis technique. Briefly, I digested 2µg samples overnight with HinfI (New England

BioLabs Inc. R0155L) and RsaI (New England Biolabs Inc. R0167L) and ran them on

0.5% agarose gels alongside a high molecular weight ladder (7 to 49kb in range; Sigma-

Aldrich 11721615001) flanking the samples. I ran gels overnight (approximately 20hr) at

40 to 45V to produce a smear of the range of telomere lengths across cells and

chromosomes (Kimura et al. 2010). I transferred the digested DNA to positively charged

Hybond N+ membranes (GE Healthcare Lifesciences RPN119B) through capillary action

(versus suction). I prepared radioactively labeled (P-32 gamma ATP) ladder and telomere

([CCATTT]3) probes and hybridized them to the membranes for 24hr at 37°C. I then

washed the membranes, exposed them to phosphor imager screens for 24hr, and scanned

the imager screens on a Typhoon 9400 Variable Mode Imager (Amersham Biosciences)

to produce images of TRF smears in ImageQuant TL 8.1 (GE Healthcare Lifesciences

29000605). I ran a control human blood sample alongside each TRF assay to determine

inter-assay, coefficient of variation (CV) among replicate TRF assays.

I quantified TRF lengths by densitometry in ImageJ v 1.49 using the equation

telomere length = Σ(ODi)/ Σ (ODi/MWi) for denaturing gels, where ODi and MWi refer to

15

optical density and molecular weight, respectively, at position i (Horn et al. 2010,

Kimura et al. 2010). For each blot, I used the same analysis window for all samples and

ladders, which contained the whole lane excluding regions near the top of the loading

area (undigested DNA). I calculated mean TRF length for each sample twice (one for

each of the two ladders that were run alongside the samples) and calculated weighted

means by horizontal position from each ladder for each sample. I quantified each blood

sample through this full procedure at least three times and included a mean TRF length

across these replicates in subsequent analyses. For samples with more than three

replicates, I selected three replicates at random for inclusion.

To determine the effect of aging and stress, as well as sex, on telomere length, I

determined the most parsimonious model for mean TRF length, using age, sex, HCC, and

GGT as predictors and evaluated their effects. I conducted model selection and all

statistical analyses in R. I began with a saturated model: age, sex, HCC, or GGT and all

two-way interactions, excluding higher-order interactions due to small sample sizes. I

eliminated non-significant predictors using backward selection and maximum likelihood

ratio tests (drop1 in R). I selected the model structure with the lowest Akaike Information

Criterion (AIC; Hurvich and Tsai 1989, Burnham and Anderson 2004). Using plots, I

examined resulting regressions for outliers, normality (e.g., fitting quantile-quantile plots

with normal lines and 95% confidence intervals), and homoscedasticity (e.g., examining

residual plots for random spread of residuals) to determine if data transformations would

be necessary. I used plots instead of statistical tests due to small sample size and, thus,

low power for detecting significance. I tested significant effects of predictors in the final

model using an ordinary least squares linear regression. I also determined the effect of

age on mean TRF length separately in males and females through linear regression.

Significant levels were set at an alpha (P) of 0.05.

To confirm if interstitial telomeric sequences were present in grizzly bears and

would thus affect telomere measurements, I compared TRF lengths with and without

BAL-31 exonuclease digestion—an enzyme that digests terminal (telomeric) ends of

DNA (Bassham et al. 1998, Sykorová et al. 2013)—in a small subgroup of samples that

16

provided sufficient DNA for this analysis. These TRF assays followed the above protocol

except for digestion with BAL-31 following HinfI and RsaI digestion, following

manufacturer instructions (New England Biolabs Inc. M0213S). I conducted a paired t-

test to test for significant differences in mean TRF length with and without BAL-31

treatment. I also conducted a model II regression to examine the relationship between

mean TRF length with and without BAL-31 treatment and tested for significant

differences from a slope of 1 and intercept of 0 using linear regression t-tests.

2.4 Results

A total of 30 grizzly bear blood samples comprising 24 individuals were collected. I

excluded nine samples because three replicate measurements (asssays) were not possible

(insufficient DNA quantity or quality). Twenty-one samples corresponding to unique

individuals (14 males and seven females) ranging from 1.4 to 15.7yr of age were included

in the TRF assay (Appendix 1). Data on HCC and GGT were not available for one and

two of these individuals, respectively. For 11 samples where more than three replicate

TRF measurements were made, I selected three replicates at random for inclusion in

statistical analyses.

I ran a total of eight TRF assays. Two blots were missing a human blood sample

control and I did not discard TRF measurements from these blots because it would

compromise my sample size. Inter-assay variation based on CV in mean TRF of the

human blood control (six blots) was 17.80%. Qualitatively, grizzly bear telomere smears

had wider distributions of lengths, which appeared to be bimodal, in comparison to the

human control (Figure 1). Mean TRF length ranged from 11.75kb to 14.13kb. Based on

AIC, the most parsimonious model for mean TRF length comprised age, sex, HCC, and

GGT, and the interaction between age and sex, age and HCC, and HCC and GGT as

predictors (Appendix 2). There was no evidence for outliers, non-normality or

heteroscedasticity. There was evidence for collinearity between age and HCC and

between HCC and GGT (variance inflation factor >10; O’Brien 2007) and these terms

were removed from the model. In the final model (age, sex, HCC, GGT and the

17

interaction between age and sex), the effect of age on mean TRF was significant (Table

1). The effect of the interaction between age and sex was marginally significant. The

effect of age on mean TRF was not significant in males (r2=0.0046, F1,12=0.056, P=0.82),

but significant in females (r2=0.89, F1,5=41.51, P=0.0013; Table 2), who showed an

increase in mean TRF with age (0.21kb per year; Figure 2).

Due to small DNA quantities, I conducted two TRF assays on a small subset of

nine samples with and without BAL-31 treatment. DNA quantities were not sufficient to

allow for replicates. CV in mean TRF of the human blood control in these two assays was

0.048%. Qualitatively, southern blots of TRFs with and without BAL-31 treatment

revealed little to no visible signal for TRFs treated with BAL-31 (Figure 3; Appendix 3).

For four samples, BAL-31 treatment unexpectedly resulted in mean TRFs that were

longer than controls after averaging the two individual TRF measurements (one for each

ladder). These samples were run on the same blot and CV between the measurements was

high (mean CV across four samples=12.69%). For each ladder, mean TRF lengths of

controls were always comparably longer than BAL-31 treated samples and this

comparison was reversed when TRFs were averaged. Even with the high CV, I did not

discard this blot so that the effect of BAL-31 could be explored. Differences between

mean TRFs with and without BAL-31 treatment were marginally non-significant (paired

t-test, t=2.22, df=8, P=0.057). The relationship between mean TRF with and without

BAL-31 was significant (r2=0.94, P=1.84x10-5), with a slope (1.71±0.21) and intercept (-

9.48±3.39) that was significantly different from 1 (t=3.39, P=0.012) and 0 (t=-3.30,

P=0.013), respectively (Figure 4). DNA quantities were insufficient to increase sample

size and, without replicates, these findings are inconclusive.

18

Table 1. A general linear model for the effect of age, sex, HCC, GGT, and the interaction

between age and sex on mean TRF length in 21 grizzly bears. The effect of age was

significant and the effect of the interaction between age and sex was marginally

significant.

Term Estimate Standard error t value Probability

Intercept 12.05 0.69 17.36 7.23x10-6

Age 0.19 0.070 2.75 0.018

Sex 1.00 0.68 1.47 0.17

HCC -0.12 0.063 -1.90 0.082

GGT -0.0068 0.017 -0.40 0.70

Age*sex -0.20 0.094 -2.12 0.056

Table 2. Linear regressions for the effect of age on mean TRF length in 14 male and

seven female grizzly bears. The relationship between age and mean TRF length was not

significant in males but was significant in females.


M F M F M F M F

Intercept 12.52 11.45 0.39 0.26 32.28 44.55 4.94x10-13 1.08x10-7

Age -0.015 0.21 0.064 0.033 -0.24 6.44 0.82 0.0013

19

Figure 1. A sample TRF gel of 18 grizzly bear samples showing a sample analysis

window (red rectangle). Labels on the top of each lane correspond to sample

identification. A high molecular weight ladder is shown on the first lane from the right

(MW) with fragment lengths labeled in kilobase pairs (kb). A human blood control was

loaded on the second lane (HB). Mean TRFs across all grizzly bear samples in this work

(N=21) ranged from 11.75kb to 14.13kb.

20

Figure 2. Non-significant and significant linear regressions of age on mean TRF length

(in kilobase pairs) in 14 males and seven females, respectively. A dashed line represents

the linear regression of age on mean TRF length in males (open circles) while a solid line

represents the linear regression of age on mean TRF length in females (filled circles).

5 10 15

24

68

1012

14

Age (years)

Mea

n TR

F (k

b)

21

Figure 3. A sample gel showing little to no signal in samples with (1, 2) compared to

samples without (1a, 2a) BAL-31 exonuclease digestion. A high molecular weight ladder

is shown on the right lane alongside the samples (MW), with fragments labelled in

kilobase pairs (kb).

1 1a 2 2a MW kb

– 48.5 – 38.4 – 24.9 – 15.3

– 16.7!

– 14.1!

– 13.3!

– 7.6!– 8.1!

– 9.7!

– 10.8!

– 11.2!

– 11.8!– 12.3!

– 22.0!

– 29.0!

– 26.7!

22

Figure 4. A graph showing a significant model II regression between mean TRF length

with and without BAL-31 exonuclease digestion in nine grizzly bear samples. The slope

and intercept were significantly different from 1 and 0, respectively. A major axis

regression line (red) and 95% confidence intervals (grey lines) are shown. A dashed line

with a slope of 1 and intercept of 0 is also shown.

2.5 Discussion

Based on a small sample of 21 grizzly bears, this preliminary work suggests significant

13.0 13.2 13.4 13.6 13.8 14.0 14.2

13.0

13.5

14.0

14.5

Mean TRF with BAL-31 treatment (kb)

Mea

n TR

F of

con

trol (

kb)

MA regression

23

effects of age and marginally significant effects of the interaction between age and sex on

grizzly bear telomere length. More specifically, the effect of age on telomere length is

significant in females, but not significant in males. Indicators of acute (GGT) and chronic

(HCC) stress are not significant predictors of telomere length. Telomere lengths also

appear to be bimodal in distribution within individuals. Telomere length measurements

with and without terminal telomere digestion (isolating interstitial sequences) are not

significantly different. It is unlikely that the indices reported here could be used to

reliably estimate age or stress hormones in unknown grizzly bear samples. However, a

more comprehensive study in a larger set of samples is necessary to test this conclusion.

Any significant relationships obtained in a larger data set could be assessed for

predictability against an independent set of samples associated with known age, sex, and

concentrations of GGT and HCC (Dunshea et al. 2011, Pauli et al. 2011). This

exploratory work indicates TRF assays of wild grizzly bear blood samples are feasible

and facilitated through research collaborations with ongoing monitoring initiatives that

provide samples associated with age, sex, and stress data.

This study reveals an unexpected increase in telomere length with age in females

versus no change in males, which suggests telomere lengthening (e.g., telomerase

activity) or preservation might be occurring (de Lange et al. 2006). Longer telomeres are

expected in females versus males of the same age due to better ability to metabolize

reactive oxygen species because of the antioxidant properties of estrogen (Nawrot et al.

2004). In grizzly bears, this might occur after 5yr (Figure 2), when females are

reproductively mature (at approximately 6yr old [Ferguson and McLoughlin 2000]).

Estrogen could also mediate different telomere rates of change, which differ among sexes

in humans (Nordfjäll et al. 2005), mice (Ilmonen et al. 2008), and rats (Cherif et al.

2003). While blood telomere lengthening with age has been observed in American

redstarts (Bize et al. 2009), Leach’s storm petrels (Haussmann et al. 2003), water pythons

(Ujvari and Madsen 2009), and Pacific martens (Pauli et al. 2011), it is unknown whether

the observations reported here reflect a true pattern in grizzly bears due to small sample

size (N=7) and variation across blots; a larger study is necessary to confirm these

findings. A longitudinal study where multiple TRF measurements in recaptured

24

individuals are made could also determine if telomere attrition varies across age and sex,

and within individuals (e.g., nonlinear change over time). These models could have

important implications for individual life spans (Haussmann et al. 2003, Gomes et al.

2011, Dantzer and Fletcher 2015) as well as survivorship (Haussmann et al. 2005, Foote

et al. 2010, Heidinger et al. 2012, Barrett et al. 2013).

For grizzly bears, it is possible that telomeres will serve as a more suitable indicator

of biological (e.g., wear and tear; Plot et al. 2012, Pauliny et al. 2006) versus

chronological aging and stress. Sampling methods (e.g., darting versus culvert traps) and

frequency could also contribute to stress (Cattet et al. 2014) and, thus, impact telomeres.

Previous studies have shown that grizzly bears captured on multiple occasions were in

poorer age-specific body condition due to sampling in comparison to bears that were only

captured once (Cattet et al. 2008a). A larger set of samples could allow mixed effects

models for telomere length incorporating these random effects to be explored. Analyses

can also determine if muscle damage due to stress (Cattet et al. 2008b) can serve as an

indicator of biological senescence. The effects of oxidative stress on telomeres might also

be mediated by dietary (Jennings et al. 2000, Paul 2011), psychological (Epel et al. 2004)

and reproductive (Heidinger et al. 2012) stress, as well as social contact (Kotrschal et al.

2007). Relevant to grizzly bear conservation, telomere patterns could be linked to habitat

characteristics (Angelier et al. 2013, Mizutani et al. 2013) to predict or characterize

anthropogenic interactions leading to stress as effects on biological senescence. For

grizzly bears, pedigree data from genotyping samples (Craighead et al. 1995) could allow

for the exploration of potential effects of reproduction and heritability on telomere length

(Bakaysa et al. 2007, Njajou et al. 2007, Broer et al. 2013). Heritability might also

explain bimodal distributions of telomere length within individual grizzly bears, which

might result from hybridization between parents with disparate telomere lengths. Such

has been observed in zebrafish (Henriques et al. 2013), mice (Zhu et al. 1998, Dejager et

al. 2009) and dasyurid marsupials (Bender et al. 2012). Bimodal telomere lengths could

also be maintained through differential telomere processing in germ line cells among

sexes as a response to differences in stress exposure (Bender et al. 2012, Ingles and

Deakin 2016). Fluorescence in situ hybridization assays for telomere length can more

25

closely quantify and examine these characteristics (Bender et al. 2012, Ingles and Deakin

2016). However, these assays will require high-quality tissues that allow for cell culturing

(Wong et al. 2012).

Limited DNA quantities did not allow for multiple replicates on reliable blots for

all samples. Large samples are necessary to develop and optimize TRF assays. For

example, it is necessary to determine the species-specific range in telomere lengths

(11.75 to 14.13kb; Gomes et al. 2011) to choose appropriate ladders that span this range,

agarose gel concentrations (Kimura et al. 2010) and gel run times. My high inter-assay

variation (17.80%) suggests a substantial increase in sample size or number of replicates

for each individual will be necessary to increase precision (repeatability) across assays

(Eisenberg et al. 2015, Verhulst et al. 2015). However, my inter-assay variation uses a

subset of all blots (six of eight). Thus, it is unknown if the remaining blots would have

increased or decreased this estimate. My coefficient of variation between assays (that

occurred in different laboratories) is low relative to across-lab variation reported

elsewhere (from 10% to 69%; Martin-Ruiz et al. 2015). Within a lab, inter-assay

variation is also as high as 15.30% (Martin-Ruiz et al. 2015). Conducting TRF assays in

the same lab will likely decrease inter-assay variation. It is also possible that inadequate

digestion (e.g., presence of dark bands in the gel close to loading areas) could have

contributed to this variation. Additional optimization of TRF assays while ensuring

adequate enzymatic digestion could increase precision in TRF measurements and confirm

the relationships reported here. The use of additional enzymes can also ensure that

noncanonical telomeric sequences—that might vary in length across individuals—are

fully digested (Kimura et al. 2010). Unfortunately, logistical constraints (e.g.,

decommissioning radioactive materials permits, limited time and space available in

collaborating labs to develop nonradioactive protocols) precluded conducting multiple

assays in the same lab.

Taking into account variation across blots, my mean grizzly bear telomere length is

12.68±0.16kb and telomere length measured from a single polar bear cell culture falls

within this range (12kb; Gomes et al. 2011). This suggests my reported values and

26

technique are potentially relevant for polar bears. While differences in telomere length

measurements with and without telomere digestion are not significant, blots with

telomere digestion (targeting interstitial sequences only) reveal little to no signal,

qualitatively. These results are inconclusive due to small sample size and lack of

replicates. A posterior power analysis suggests a sample size of 300 paired comparisons

will be necessary to confirm my effect sizes (at a significant and power level of 0.05 and

0.80, respectively); including replicates will likely increase precision in TRF

measurements and reduce this number. Larger quantities of DNA collected in grizzly

bears will increase precision in telomere length estimates and confirm any effect of

interstitial sequences on telomere measurements. Alternative methods, such as

fluorescence in situ hybridization or single telomere length analysis, could more

accurately visualize and quantify interstitial telomeres in vitro (Meyne et al. 1990, Aubert

et al. 2012a, Montpetit et al. 2014), as well as examine telomere distributions among

cells or chromosomes within tissues and individuals. Previous in vitro assays in panda

bears have revealed no interstitial telomeres, but they were present in some carnivores

(e.g., leopards, ocelots, and ferret badgers [Meyne et al. 1990]). In vitro assays could also

determine differences in telomere lengths across blood cell types, which could vary in

composition throughout age (Aviv et al. 2006).

TRF assays are low throughput, time and labour intensive, and expensive for

frequent runs of large datasets (requiring seven to 10 days per assay; Kimura et al. 2010,

Nussey et al. 2014). TRF assays also require high-quality tissues that are not always easy

or logistically feasible to collect in all wild animals (Horn et al. 2010, Nussey et al.

2014). For applications in noninvasive sampling, a quantitative polymerase chain reaction

(qPCR)-based method for telomere quantification (Cawthon 2002, Cawthon 2009) will

be necessary as this method requires smaller DNA quantities and has higher throughput,

is less intensive, and is likely more practical (Cawthon 2002, Cawthon 2009, Kimura et

al. 2010; Chapter 3). This technique could also allow for comparisons across tissue types,

which could implicate which samples will be most informative for telomere assays.

As a first step to evaluating telomeres as a marker of aging and oxidative stress in

27

ursids, this work reveals validity of TRF assays for wild, frequently monitored animals.

Age, sex, and indicators of acute and chronic stress could explain variation in telomere

length in wild animals. While further development of telomere measurement assays to

minimize inter-assay variation in a larger set of samples will be required to confirm these

findings, the inclusion of additional physiological factors affecting telomere length could

provide further insight into telomere ecology.

28

2.6 Appendix

Appendix 1. Mean TRF length in 21 grizzly bears corresponding to mean TRF length,

age, sex, and measurements of stress hormones (hair cortisol concentration [HCC] and

serum gamma-glutamyltransferase [GGT]).

Sample

Mean TRF

length (kb) Sex Age (years)

HCC

(pg/mg) GGT (U/L)

G275 12.4 F 4.34 0.53 24

G278 12.55 M 6.39 1.21 30

G279 12.72 M 5.4 0.81 13

G283 12.80 M 15.71 4.67 42

G284 12.55 M 3.72 3.01 23

G285 12.56 M 2.73 2.03 19

G126 12.03 F 2.76 3.06 15

G119 12.46 F 5.78 4.11 NA

AB5299X 11.61 M 2.41 NA 10

ABNW4678 11.75 F 1.36 4.05 29

G111 14.14 F 9.44 1.19 26

G127 13.21 M 3.38 1.34 10

G128 12.45 M 2.76 0.89 27

G129 12.76 M 4.77 0.65 16

G150 12.56 M 2.45 0.33 NA

G151 11.35 M 6.46 3.53 42

G152 11.06 M 4.51 12.54 13

G260 13.66 F 11.38 0.94 46

G270 11.91 M 7.37 1.61 10

G287 14.13 M 2.4 3.48 19

G288 13.77 F 11.66 1.48 13

29

Appendix 2. Akaike Information Criterion (AIC) and difference in AIC compared to the

most parsimonious model for models of mean TRF length in 21 grizzly bears. Backwards

model selection began with age (A), sex (S), HCC, GGT, and all two-way interactions as

predictors and ended with a null (intercept-only) model. The most parsimonious model is

indicated in bold.

Model df AIC ΔAIC

A+S+HCC+GGT+A*S+A*HCC+A*GGT+S*HCC+S*GGT+

HCC*GGT

12 46.24 5.91

A+S+HCC+GGT+A*S+A*HCC+A*GGT+S*GGT+HCC*GGT 11 44.24 3.91

A+S+HCC+GGT+A*S+A*GGT+S*GGT+HCC*GGT 10 42.25 1.92

A+S+HCC+GGT+A*S+A*GGT+HCC*GGT 9 40.33 0.00

A+S+HCC+GGT+A*S+A*GGT 8 42.06 1.73

A+S+HCC+GGT+A*S 7 44.46 4.12

A+S+HCC+A*S 6 44.28 3.94

A+S+HCC 5 49.09 8.76

A+HCC 4 48.12 7.79

HCC 3 48.66 8.33

Null 2 55.36 15.03

30

Appendix 3. Mean TRF length in 9 grizzly bears corresponding to mean TRF length with

BAL-31 exonuclease treatment, digesting terminal telomere sequences.

Sample Mean TRF length of control

(kb)

Mean TRF length with

BAL-31 treatment (kb)

ABNW4678 13.12 13.23

AB5299 12.85 12.95

G129 13.39 13.45

G150 13.73 13.83

G260 14.67 14.01

G270 14.49 14.08

G280 14.66 14.08

G287 14.86 14.24

G288 14.41 14.05

31

Chapter 3

A qPCR assay of telomeres comparing tissue-3

type, age, sex, and population in polar bears

3.1 Summary

Telomeres potentially serve as a genetic marker of biological aging in response to age

and sex, as well as environmental stress. For sampling polar bears, quantitative

polymerase chain reaction (qPCR) assays of telomere length are likely more useful and

appropriate in comparison to other conventional methods, such as Southern blotting of

telomere restriction fragments. The latter methods require fresh, high-quality tissue

samples that are difficult to acquire from wild animals. Using the first telomere qPCR

assay in polar bears, I characterize differences in relative telomere length (ratio between

sample telomere and single copy gene quantities; T/S) attributable to age (cub, subadult,

and adult categories) and sex, and between populations (Baffin Bay, Davis Strait, Foxe

Basin, Lancaster Sound, and Western Hudson Bay). Analyses use 40 (10 females and 30

males) samples of heart, muscle, and skin collected from the same bears by Inuit hunters

across Nunavut during harvests in 2014. T/S ranges from 0.58 to 2.39, 0.48 to 3.19, and

0.58 to 2.37 for heart, muscle, and skin, respectively. No significant differences in T/S

occur across tissue types within individuals. Age, sex, and the interaction between age

and sex are significant predictors of telomere length in muscle, and potentially skin

samples. Significant differences occur among populations for all tissue-types; T/S in

Baffin Bay polar bears are significantly larger than T/S from Western Hudson Bay polar

bears. These results warrant further investigations involving larger sample sizes within

groups. Traditional knowledge and interpretations of biological senescence reported by

Inuit hunters could inform these results. Telomeric indices of age, sex, and population

may serve as novel, molecular tools for harvest monitoring and population management.

32

3.2 Background

Genetic-based methods of monitoring polar bear populations and their harvests continue

to hold promise for immediate conservation and management, especially in the face of

rapid climate-induced habitat changes. Across their range, polar bear populations have

been delineated and individually monitored using a combination of genetic (Paetkau et al.

1999, Peacock et al. 2015), aerial (e.g., Stapleton et al. 2014, Stapleton et al. 2016),

mark-recapture (e.g., Taylor et al. 2005, Taylor et al. 2006) and satellite telemetry (e.g.,

Taylor et al. 2001, Mauritzen et al. 2002) methods. These methods collect information on

population abundance, sex and age structure, survival, and indicators of health, which

serve to predict probabilities of decline and sustainable harvest rates (e.g., Taylor et al.

2006). In spite of these efforts, these surveys occur infrequently (Peacock et al. 2011),

and are expensive (Dowsley 2009a) and often dangerous to conduct. Comprehensive

surveys of each of Canada’s polar bear populations (Figure 5) occur once every 10 to 15

years (Peacock et al. 2011) and require three to four years to conduct, plus additional

time for data analysis and reporting (M. Dyck, Government of Nunavut, personal

communication). In addition, local communities do not always support these methods,

which has led to unique conflicts in co-management (Clark et al. 2008, Tyrell and Clark

2014). Thus, less invasive biopsy-based darting methods have been developed because

they do not require physical capture of individuals (Pagano et al. 2014) to which Inuit

object (Tyrell 2006). However, these methods still require expensive aerial support to

complete and must be coupled with genetic methods to identify (Van Coeverden de Groot

et al. 2013) and sex (Pagès et al. 2009) individuals to estimate demographic parameters.

Unpredictable field weather conditions also increase difficulty in collecting these data for

timely management applications (Government of Nunavut 2015). Molecular-based

methods of estimating age and/or inferring population health would certainly improve, if

not complement, the utility of using less invasive survey methods.

Inuit communities that harvest polar bears participate in surveys and collect data

from harvests throughout and between survey years (Dowsley 2009b, Peacock et al.

2011, Vongraven and Peacock 2011). Community Hunters and Trappers Organizations

33

and the Government of Nunavut Department of Environment gather information on the

date, location, and sex of killed bears by collecting the baculum from hunters (Brower et

al. 2002) and reporting ear tags and tattoo markings for bears that were previously

captured. The lower jaw or first premolar tooth from each harvested bear is also collected

for age determination (Calvert and Ramsay 1998). Polar bears are harvested from

populations following quotas for each population and these records are necessary to

monitor and confirm numbers, sex, and spatial distributions of bears that are harvested

(Brower et al. 2002).

Population and harvest monitoring of polar bears could benefit from telomere-based

information on biological senescence (wear-and-tear), as well as chronological aging.

Telomeres could also serve to determine environmental effects on senescence.

Environmental perturbations have been found to contribute directly to telomere

shortening (Mitzutani et al. 2013), or through effects on body fat accumulation (Hall et

al. 2004) and early growth (Watson et al. 2015). Estimations of telomere length usually

involve Southern blotting of telomere restriction fragments (TRF; Kimura et al. 2010).

However, this approach has low-throughput, is time-intensive, and for repeatability

requires high-quality samples, such as fresh and/or frozen blood samples stored at -80°C

or below (Horn et al. 2010, Kimura et al. 2010, Aubert et al. 2012b, Nussey et al. 2012).

For species where TRF assays have not been developed, such samples are critical to

ensure resulting measurements and telomere characteristics, such as distribution of

lengths, are reliable and accurately represent the species. This constraint creates logistic

challenges for the collection of tissue samples from polar bears. Such initiatives require

governmental wildlife sampling, research, and transport permits (Wong et al. 2012) and

knowledge and experience in tracking and locating individual animals across remote sea

ice environments. Further, veterinary experience in anaesthetizing is necessary, as are

handling and monitoring individual polar bears. Add to this the general lack of -80°C

and/or below storage freezers and transport materials (e.g., dry ice and/or liquid nitrogen)

in arctic communities. Even when these are available, it takes at least two days to ship

samples to laboratories (outside of Nunavut) where adequate storage conditions exist.

Such challenges are more often insurmountable than not.

34

For polar bears, an alternative method is necessary. Quantitative polymerase chain

reaction (qPCR) can quantify telomeres (Cawthon 2002, Cawthon 2009) and this method

is preferable to TRF assays because it is less sensitive to tissue degradation (Aviv et al.

2011) and requires small DNA quantities (Cawthon 2002, Cawthon 2009, Kimura et al.

2010). These attributes permit the use of noninvasively collected samples. This chapter

describes my efforts to characterize telomeres as potential monitoring tools in wild polar

bears. Using captive zoo samples, I initially developed a TRF assay to examine telomere

lengths in fresh, high-quality polar bear samples collected opportunistically during

routine veterinarian exams. Small sample sizes and time limit the approach (Appendix

3.6.1). Using a larger dataset consisting of heart, muscle, and skin samples collected from

wild, harvested polar bears across Nunavut, I used a qPCR assay to examine the effects of

age, sex, and population on telomere length. I also compared telomere lengths derived

from qPCR and TRF assays using a small number of grizzly bears.

35

Figure 5. A map showing distributions of Nunavut communities among 16 of 19 global

polar bear populations (Laptev, Kara, and Barents Sea populations not shown). EG=East

Greenland, AB=Arctic Basin, CS=Chukchi Sea, SB=Southern Beaufort, NB=Northern

Beaufort Sea, VM=Viscount Melville, NW=Norwegian Bay, KB=Kane Basin,

LS=Lancaster Sound, BB=Baffin Bay, MC=M’Clintock Channel, GB=Gulf of Boothia,

FB=Foxe Basin, WH=Western Hudson Bay, SH=Southern Hudson Bay, and DS=Davis

Strait. Map reproduced by the Department of Environment, Government of Nunavut.

3.3 Methods

3.3.1 QPCR in samples of wild polar bears

Through research agreements with the Government of Nunavut Department of

Environment, I assembled a database of 368 (166 muscle, 86 heart, and 116 hair attached

to skin) polar bear samples from 192 harvested bears (132 males and 60 females) in 2014.

36

For each sample, the local hunter and/or conservation officer visually sexed and aged the

bear according to “adult”, “subadult”, “2 year old cub”, “one year old cub”, and “cub of

year” categories based on body size and teeth eruption. I combined the latter three age

categories into a single “cub” category to allow for multiple young bears to be included in

subsequent comparisons. Samples were stored in local community freezers until transport

to the Department of Environment, Government of Nunavut in Igloolik. Upon receipt,

samples were stored at -20°C and subsequently shipped to Ottawa in coolers with ice

packs. I picked the samples up and transported them to the Royal Ontario Museum for

storage at -80°C in the Laboratory of Molecular Systematics. As samples were fairly

large in size (ranging from 5cm3 to 10cm3), I subsampled 1cm3 from the center of each

tissue to facilitate archiving, identification, and retrieval of samples and to avoid tissue

damage owing to repeated freeze-thaw.

I isolated genomic DNA from the tissue samples using a standard salt extraction

method (Bruford et al. 1992) and ran DNA samples out on 1% (w/v) agarose gels to

examine DNA quality. I quantified all samples using a Nanodrop spectrophotometer

(University of Toronto, M. Sokolowski Lab). TRF assays could not be completed on

these samples due to insufficient DNA quality; some evidence for degradation appeared

on agarose gels and this would have impacted measurements of telomere length (Kimura

et al. 2010). Because qPCR targets short fragments, it was presumed to be less sensitive

to degradation (Aviv et al. 2011). Though qPCR might be unable to discount interstitial

telomeric repeats (Haussman and Mauck 2008, Monaghan 2010), I assumed interstitial

sequences in all individuals would be of the same length and, thus, would have had

negligible effects on telomere length estimation.

Because this study was exploratory, I selected a subset of 120 samples (40

muscle, heart, and skin from the same individuals) for telomere qPCR instead of the

entire database. Samples were chosen on the basis of highest quality and quantity and

allowing for intra-individual tissue comparisons (heart, muscle, and skin from the same

individual). The University of Guelph Agriculture and Food Laboratory Service (S.

Chen) analyzed these tissues, using primers and protocols that I recommended to them

37

(Cawthon 2002, Cawthon 2009). Telomere primers were previously published: telg (5’-

ACACTAAGGTTTGGGTTTGGGTTTGGGTTTGGGTTAGTGT-3’) and telc (5’-

TGTTAGGTATCCCTATCCCTATCCCTATCCCTATCCCTAACA-3’), producing an

amplicon size of 79bp (Cawthon 2009). I chose RPLP0 in polar bears (accession

XM_008707681) as a single copy reference gene following previous telomere qPCR

assays in mice (Callicott and Womack 2006), humans (Hewakapuge et al. 2008,

O’Callaghan et al. 2011), cetaceans (Olsen et al. 2012) and carnivores (Pacific marten;

Pauli et al. 2011). Reference primers were designed using Primer Express® Software

(Applied Biosystems) synthesized using an ABI 3900 HT DNA synthesizer (Applied

Biosystems): RPLP0-F1 (5’-AATGCTTCATTGTGGGAGCA-3’) and RPLP0-R1 (5-

TCATGGTGTTCTTGCCCATC-5’), producing an amplicon of 105bp.

I initially tested telomere primers (telc/telg [Cawthon 2009]) and developed a

combination of RPLP0 primers using conventional polymerase chain reaction (PCR). I

designed RPLP0 primers using AmplifX 1.5.4 and optimized them by varying annealing

temperatures in PCR and sequencing amplicons using ABI BigDyeTM Terminator v3.1

(Heiner et al. 1998) on an ABI 3130 (Applied Biosystems) to confirm primer specificity.

I performed all PCRs on an Eppendorf AG 5345 thermal cycler and ran reaction products

out on 1.5% agarose gels to confirm amplicon sizes. Each 25µL PCR reaction contained

10mM dNTP, 10µM of each primer, 1xPCR buffer (1.5mM MgCl2; Fisherbrand), 0.75U

of Taq DNA polymerase (New England Bioilabs Inc.), and 15–20ng of DNA. Cycling

conditions were as follows: 94°C for 2min, followed by 40 cycles of 94°C for 30s,

annealing for 45s, and 72°C for 45s, with a final extension at 72°C for 7min. Annealing

temperatures were 62°C and 54–62°C for telomere and reference primers, respectively. I

conducted initial qPCR trials (University of Toronto, J. Mitchell and M. Sokolowski

Labs) using telomere and resulting RPLP0 primers to examine melt curves for primer

specificity (Ririe et al. 1997). However, to increase objectivity and minimize time and

financial costs required to develop and optimize qPCR, I commissioned the University of

Guelph Agriculture and Food Laboratory Service (S. Chen) for their technical expertise

in primer design and general qPCR optimization to analyze my data set.

38

Singleplex qPCR amplifications were carried out on a PCR MicroAmpTM Fast 96-

well Reaction plate sealed with MicroAmpTM Optical Adhesive Film (Applied

Biosystems). Samples were run in triplicate along with a serial dilution of a standard

(100.00, 20.00, 4.00, 0.80, and 0.16ng per reaction) run in duplicate on each plate. This

standard comprised DNA isolated from liver sampled from a deceased captive neonate

polar bear at the Toronto Zoo. Each 25µL reaction contained: 1xSYBR Green PCR

master mix (Invitrogen), 0.7mM MgCl2, 400nM of each primer, 0.6U AmpliTaq Gold

DNA polymerase (Applied Biosystems), 1x Q-solution (Qiagen; for telg and telc

reactions only), and 20–30ng of genomic DNA. Amplifications were conducted using

7500 Fast Real-Time PCR (Applied Biosystems). For each reaction, singleplex

amplifications were carried out at the same time (e.g., two plates, one for telc/g and one

for RPLP0) on two qPCR machines using the same well position. Cycling conditions for

telg/telc were 15min at 95°, 2 cycles of 15s at 94°C, 15s at 49°C, 32 cycles of 15s at

94°C, and 30s at 62°C with signal acquisition. Cycling conditions for RPLP0 primers

were 10min at 95°C, 32 cycles of 20s at 95°C, and 30s at 60°C with signal acquisition.

Upon completion, amplification signals were acquired using the 7500 software v.2.01

(Applied Biosystems) and reported as baseline corrected Ct values (versus correction

using LinRegPCR [Ruitjer et al. 2009], which could result in variation in efficiencies

across dilutions [Olsen et al. 2012]). Two non-template controls were run on each plate to

detect contamination and melt curves for the first 30 samples were examined to confirm

primer specificity (Ririe et al. 1997).

Mean Ct values for each sample and standard dilution (three and two technical

replicates, respectively) were used to calculate telomere to single copy gene quantities

(T/S). I calculated qPCR efficiency for each plate by running a linear regression to

generate a standard curve (the effect of log concentration on Ct) and using the equation

10-1/slope –1, where a value of 1 indicates 100% efficiency (Pffafl 2001). Because

efficiency differed between plates for each singleplex reaction, I determined T/S using

the equation 10(b-Ct)/a for telomere and reference quantities, where b and a referred to

intercept and slope, respectively, of the corresponding standard curve (Pffafl 2001, Olsen

et al. 2012).

39

To determine assay repeatability, I calculated mean standard deviation of Ct

values (versus coefficients of variation [CV] in Ct values, which are inherently lower

[Bustin et al. 2009]) for telomere and reference primers across technical replicates (Olsen

et al. 2012) for each heart, muscle, and skin data set. To determine assay reproducibility,

I calculated mean standard deviations in Ct for each standard dilution sample across

plates. Heart, muscle, and skin samples could not be used because technical replicates for

these samples were made on the same plate. To calculate overall telomere and reference

qPCR efficiency, I calculated mean r2 and mean efficiency across plates. To standardize

and calculate means of standard deviations and efficiencies, I z-transformed values,

calculated the mean of z-transformed values, and then back-transformed the calculated

mean. Similarly, to calculate mean r2, I transformed r2 to Fisher’s z’ (normal

distribution), calculated the mean of z’-transformed values, and back-transformed the

calculated mean (Clayton and William 1987).

All statistical procedures were performed in R. To determine biological variability

in T/S across individuals, I determined CV for heart, muscle, and skin data sets. To

determine differences in T/S across tissues, I compared T/S in heart versus muscle, heart

versus skin, and muscle versus skin using major axis model II regressions (lmodel2

package in R; Sokal and Rohlf 1969, Legendre and Legendre 1998). I tested for

significant differences from slopes and intercepts of 1 and 0, respectively, using linear

regression t-tests. I also conducted paired t-tests (Appendix 5). Using plots, I examined

the data set for outliers and model assumptions (normality, constant error variance

[homoscedasticity], and collinearity) to determine if transformations were necessary.

Slopes and intercepts were reported as values ± standard error.

For each set of heart, muscle, and skin samples, the effect of age, sex, population,

and interactions between age and sex on T/S was determined using type III sums of

squares in a multi-factor ANOVA (car package in R; Hector et al. 2010). To find the

most parsimonious model (model that best explained variation in T/S), I began with a full

model (age, sex, population, and the interactions between age and sex) and eliminated

non-significant variables using backward selection and F tests (drop1 function in R),

40

finishing with the null (intercept only) model. I selected the model structure with the

lowest Akaike Information Criterion as the most parsimonious model (Hurvich and Tsai

1989, Burnham and Anderson 2004). The resulting model was examined for outliers,

normality, and homoscedasticity (constant error variance), as well as collinearity.

Significant effects were further examined using post-hoc Tukey’s Honest Significant

Difference (HSD) tests (agricolae package in R, for unbalanced sample sizes). Due to

small sample sizes within groups that limit the ability to detect violations of model

assumptions, nonparametric Kruskal-Wallis rank sum tests were also used to detect

significant differences among groups.

I did not test for the effect of sex and population interactions because there were

no females from one population (Davis Strait) sampled for my data set. For the same

reason, I did not test the effect of age and population interactions, as there were no

samples for some age and population combinations. Due to small degrees of freedom

(N≤7 provided by most communities), I examined differences in T/S among communities

qualitatively using boxplots.

3.3.2 Comparisons between TRF and qPCR assays

In the absence of polar bear samples that allowed for TRF assays to be conducted (e.g.,

high-quality samples from captive polar bears at zoos), TRF and qPCR assays were

compared in the same set of grizzly bear blood samples with sufficient DNA quantities

for these analyses. Methods for grizzly bear blood sampling and DNA isolation were

described in Chapter 2. Quantitative PCR of grizzly bear samples followed the same

primers and procedures as above and were run on a single plate (for each telomere and

reference primer set) with polar bear samples. The relationship between mean TRF length

and T/S was tested using a standard major axis model II regression (Sokal and Rohlf

1969, Legendre and Legendre 1998) and t-tests for significant differences in slope and

intercept from 1 and 0, respectively. Values were reported as means ± standard error. As

in Chapter 2, I also determined if the effect of age, sex, and indicators of acute (serum

gamma-glutamyltransferase) and chronic (hair cortisol concentration) stress on grizzly

41

bear telomere length was significant, using blood T/S (Appendix 3.6.3).

3.4 Results

3.4.1 Telomeres in harvested polar bears based on qPCR

From the full database of salvaged samples, a subset of the highest quality DNA from

120 (40 each of muscle, heart, and skin) tissues from 40 individuals (10 females and 30

males) was selected for qPCR analysis (Appendix 11). These samples comprised 29

adults, six sub-adults, and four cubs across Baffin Bay (N=10), Davis Strait (N=6), Foxe

Basin (N=5), Lancaster Sound (N=8), and Western Hudson Bay (N=10) populations.

Samples were collected during harvests by Arctic Bay (N=7), Arviat (N=7), Clyde River

(N=3), Hall Beach (N=1), Iqaluit (N=6), Igloolik (N=4), Grise Ford (N=2), Pond Inlet

(N=7), and Rank Inlet (N=3) communities (Figure 5). Age was not available for tissues

collected from a single male in Lancaster Sound by Arctic Bay.

Twelve qPCR plates (six plates for each primer) were run for the 120 samples

(Appendix 12 to 17). Melt curves for seven sample dilutions ranging from 0.0064 to 10ng

per reaction in duplicate (14 reactions) confirmed specificity of telomere and reference

primers; a single peak for melting temperatures occurred for each primer set (Ririe et al.

1997; Appendix 18 and 19). Two samples produced Ct values that fell outside the

standard range and, thus, were re-run; one sample was diluted 10X before the second run

and the other was increased in concentration (by making a smaller dilution from the

original sample). There was no evidence of contamination, as Ct values for non-template

controls were either not detected or exceeded the highest Ct value for the other samples

by at least five cycles. For the 40 individuals, mean standard deviations of telomere Ct

across technical replicates were 0.24, 0.27, and 0.13 for heart, muscle, and skin data sets,

respectively. Mean standard deviations of reference Ct were 0.16, 0.27, and 0.11 for

heart, muscle, and skin, respectively. Using the five sample-dilutions replicated on each

plate, mean standard deviation of Ct across the six plates was 0.51 and 0.27 for telomere

and reference primers, respectively. Mean r2 across plates was 1.00 and 1.00 for telomere

42

and reference primers, respectively (Appendix 20). Mean efficiency across plates was

0.85 and 1.02 for telomere and reference primers, respectively.

Across individuals, T/S ranged from 0.58 to 2.39, 0.48 to 3.19, and 0.58 to 2.37 in

heart, muscle, and skin, respectively. CV in T/S was 0.33, 0.41, and 0.36 in heart, muscle,

and skin, respectively. One outlier in the muscle data set was removed (T/S of 23.20

standard deviations from the mean of the other values) resulting in 40 T/S observations

for heart and skin and 39 T/S observations for muscle in the analyzed data set. The

relationship between heart and muscle T/S was significant (r2=0.27, P=6.53x10-4); the

slope (0.67±0.20) and intercept (0.39±0.25) were not significantly different from 1 (t=-

1.69, P=0.099) and 0 (t=1.52, P=0.14), respectively (Figure 6). The relationship between

heart and skin T/S was significant (r2=0.21, P=0.0032); the slope (0.95±0.37) and

intercept (0.13±0.44) were not significantly different from 1 (t=-0.13, P=0.90) and 0

(t=0.29, P=0.77), respectively (Figure 7). The relationship between muscle and skin T/S

was significant (r2=0.13, P=0.026); the slope (1.67±1.57) and intercept (-0.68±1.85) were

not significantly different from 1 (t=0.43, P=0.67) and 0 (t=-0.37, P=0.72), respectively

(Figure 8). For all three models, there was no evidence for outliers, non-normality, or

heteroscedasticity.

For heart T/S, population was the only predictor in the most parsimonious model

(Appendix 21). One outlier was detected falling outside 95% confidence intervals in the

quantile-quantile plot fitted for normality. This outlier did not affect subsequent analyses

(Appendix 6). There was no evidence for non-normality, heteroscedasticity, or

collinearity. The effect of population on heart T/S was significant (Table 3). A Kruskal-

Wallis test also confirmed significant differences in heart T/S across populations

(χ2=18.62, df=4, P=9.33x10-4). A post-hoc Tukey’s HSD test indicated heart T/S in

Western Hudson Bay was significantly shorter than Baffin Bay and Foxe Basin

populations (Figure 9).

For muscle T/S, the full model (age, sex, population, and the interaction between

age and sex) was the most parsimonious model (Appendix 22). Two outliers fell outside

43

the 95% confidence interval on the quantile-quantile plot; one outlier was clearly evident

through a plot for Cook’s distance. This outlier did not affect subsequent analyses

(Appendix 7). There was no evidence for non-normality or heteroscedasticity. The effect

of all predictors (age, sex, population and the interaction between age and sex) on muscle

T/S were significant (Table 4). ANOVAs examining differences among age groups in

males and females did not detect any significant differences (Table 5; Figure 10), likely

due to lack of statistical power (small N within groups). A post-hoc Tukey’s HSD test

indicated muscle T/S in Western Hudson Bay was significantly shorter than Baffin Bay

and Lancaster Sound (Figure 11). Kruskal-Wallis tests did not detect significant

differences in muscle T/S across age groups in males (N=30; χ2=2.98, df=2, P=0.23) and

females (N=10, χ2=3.33, df=2, P=0.19), as well as across populations (χ2=8.93, df=4,

P=0.063), likely due to lower statistical power in this test and testing for these terms

alone.

For skin T/S, the full model was also the most parsimonious model (Appendix

23). One outlier fell within the 95% confidence interval in the quantile-quantile plot and

was, thus, not removed. There was no evidence for non-normality, homoscedasticity, or

collinearity. The effect of population on skin T/S was significant; all other terms in the

model were not significant (Table 6). A Kruskal-Wallis test confirmed significant

differences among populations (χ2=16.57, df=4, P=0.0023). A post-hoc Tukey’s HSD test

indicated skin T/S in Western Hudson Bay was significantly shorter than Baffin Bay and

Davis Strait populations (Figure 12).

Based on boxplots and qualitative interpretations, heart, muscle, skin T/S, varied

across communities in a relatively consistent manner (Figure 13). Longer T/S were

associated Clyde River and Pond Inlet communities, while shorter T/S were associated

with Arviat and Rankin Inlet.

44

Figure 6. A graph of a significant model II regression between heart and muscle T/S in 39

polar bears. The slope and intercept were not significantly different from 1 and 0,

respectively. A major axis regression line (red) and 95% confidence intervals (grey lines)

are shown. A dashed line with a slope of 1 and intercept of 0 is also shown.

0.5 1.0 1.5 2.0 2.5 3.0

0.5

1.0

1.5

2.0

2.5

3.0

Muscle T/S

Hea

rt T/

S

MA regression

45

Figure 7. A graph of a significant model II regression between heart and skin T/S in 40




1.0 1.5 2.0

1.0

1.5

2.0

Skin T/S

Hea

rt T/

S

MA regression

46

Figure 8. A graph of a significant model II regression between muscle and skin T/S in 39




0.5 1.0 1.5 2.0 2.5 3.0

0.5

1.0

1.5

2.0

2.5

3.0

Skin T/S

Mus

cle

T/S

MA regression

47

Table 3. A one-way analysis of variance using type III sums of squares showing

significant differences in heart T/S among Baffin Bay (N=10), Davis Strait (N=6), Foxe

Basin (N=5), Lancaster Sound (N=9), and Western Hudson Bay (N=10) polar bear

populations.

Factor Type III sums of

squares

df F value Probability

Population 2.95 4 6.55 4.81x10-4

Residuals 3.94 35

48

Figure 9. A graph showing significant differences in heart T/S across polar bear

populations. BB=Baffin Bay, FB=Foxe Basin, DS=Davis Strait, LS=Lancaster Sound,

and WHB=Western Hudson Bay. Letters represent significant groupings based on post-

hoc multiple comparisons.

BB FB DS LS WH

0.0

0.5

1.0

1.5

2.0

2.5

Population

Hea

rt T/

S

a a a b a b b

49

Table 4. A multi-factor analysis of variance using type III sums of squares showing

significant effects of age, sex, population, and the interaction between age and sex on

muscle T/S in 39 polar bears.


squares


Age 2.94 2 15.87 2.47x10-5

Sex 4.67 1 50.50 9.87x10-8

Population 3.94 4 10.63 2.28x10-5

Age*sex 3.90 2 21.051 2.63x10-6

Residuals 2.59 28

Table 5. One-way analyses of variance using type III sums of squares showing non-

significant differences in muscle T/S among age groups in 29 male and 10 female polar

bears.


squares


M F M F M F M F

Age 0.37 2.59 2 2 1.68 2.38 0.21 0.16

Residuals 2.73 3.80 25 7 - - - -

50

Figure 10. A box plot comparing muscle T/S among age groups in 10 females (F) and 30

males (M).

0.5

1.0

1.5

2.0

2.5

3.0

Cub Subadult Adult Cub Subadult Adult

F M

Mus

cle

T/S

51

Figure 11. A graph showing significant differences in muscle T/S across polar bear

populations. BB=Baffin Bay, LS=Lancaster Sound, DS=Davis Strait, FB=Foxe Basin,

and WH=Western Hudson Bay. Letters represent significant groupings based on post-hoc

multiple comparisons.

BB LS DS FB WH

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

Population

Mus

cle

T/S

a a a b a b b

52

Table 6. A multi-factor analysis of variance using type III sums of squares showing non-

significant effects of age, sex, and the interaction between age and sex and a significant

effect of population on skin T/S in 40 polar bears.


squares


Age 0.48 2 2.55 0.095

Sex 0.26 1 2.82 0.10

Population 2.41 4 6.42 7.93x10-4

Age x sex 0.48 2 2.55 0.096

Residuals 2.72 29

53

Figure 11. A graph showing significant differences in muscle T/S across polar bear

populations. BB=Baffin Bay, DS=Davis Strait, LS=Lancaster Sound, FB=Foxe Basin,

and WH=Western Hudson Bay. Letters represent significant groupings based on post-hoc

multiple comparisons.

BB DS LS FB WH

0.0

0.5

1.0

1.5

2.0

2.5

Population

Ski

n T/

Sa a b a b c b c c

54

Figure 12. A qualitative comparison of heart, muscle, and skin T/S across communities.

AB=Arctic Bay (N=7), AR=Arviat (N=7), CR=Clyde River (N=3), GF=Grise Ford

(N=2), HB=Hall Beach (N=1), IG=Igloolik (N=4), IQ=Iqaluit (N=6), PI=Pond Inlet (N=7

for heart and skin, N=6 for muscle) and RI=Rankin Inlet (N=3).

AB AR CR GF HB IG IQ PI RI

1.0

1.5

2.0

Community

Hea

rt T/

S


0.5

1.0

1.5

2.0

2.5

3.0

Community

Mus

cle

T/S


1.0

1.5

2.0

Community

Ski

n T/

S

55

3.4.2 Comparisons between TRFs and T/S

Fourteen grizzly bear blood samples allowed for mean TRF and blood T/S comparisons

to be made (Appendix 3.6.3). Mean standard deviation of Ct across three technical

replicates was 0.13 and 0.050 for telomere and reference primers, respectively.

Quantitative PCR efficiency was 0.78 and 0.97 for telomere and reference, primers,

respectively. Coefficients of determination (r2) for standard curves were 1.00 and 1.00 for

telomere and reference primers, respectively. Across grizzly bears, blood T/S ranged

from 0.69 to 1.01. CV of blood T/S across individuals was 0.094. The relationship

between blood T/S and mean TRF length was not significant (r2=2.23x10-6, P=1.00). The

slope (-0.099±0.032) and intercept (-5.65±0.40) differed significantly from 1 (t=-34.61,

P<1.0x10-4) and differed marginally non-significantly from 0 (t=5.28, P=2.0x10-4),

respectively (Figure 14).

56

Figure 13. A graph of a non-significant model II regression between mean TRF length

and blood T/S measured in 14 grizzly bears. The slope and intercept were significantly

different from 1 and marginally significantly different from 0, respectively. A standard

major axis regression line (red) and 95% confidence intervals (grey lines) are shown.

3.5 Discussion

In this study, telomere lengths do not differ across heart, muscle, and skin tissues within

40 individual polar bears. Analyses of muscle and skin samples reveal potential effects of

age, sex, and the interaction between age and sex on telomere length. These effects are

only significant in muscle samples. Analyses of all three tissues reveal significant

11.0 11.5 12.0 12.5 13.0 13.5 14.0

0.70

0.75

0.80

0.85

0.90

0.95

1.00

Mean TRF length (kb)

Blo

od T

/S

SMA regression

57

differences across Baffin Bay, Davis Strait, Foxe Basin, Lancaster Sound, and Western

Hudson Bay populations, with longer telomere lengths in Baffin Bay versus Western

Hudson Bay. Small sample sizes preclude the ability to further examine differences in

telomere length across age groups in males and females, and across communities. Using

grizzly bear samples, no relationship exists between telomere lengths reported in TRF

and qPCR assays. However, my results suggest qPCR can distinguish telomere lengths in

tissues salvaged from harvested polar bears that vary with age, sex, and population.

Despite differences in replicative potential (Friedrich et al. 2000, de Lange et al.

2006), range in telomere length is similar across heart, muscle, and skin. While age and

sex do not explain variation in telomere length in heart tissues, they do so in muscle and

potentially skin samples from harvested bears. It is possible that age is an important

predictor of telomere length in muscle and skin, due to higher proliferation rates of these

tissues in comparison to heart (Friedrich et al. 2000, de Lange et al. 2006). However,

only muscle samples show a significant effect of age and sex on telomere length.

Unfortunately, small sample sizes within age and sex groups (cub, subadult, and adult

N=2, 3, and 5, respectively for females and N=2, 3, and 25, respectively, for males) do

not allow for meaningful comparisons among female and male age groups. Based on

qualitative observations (Figure 10), adult females might have longer telomeres than

adult males due to estrogen levels that mediate shortening due to oxidative damage

(Nawrot et al. 2004), as I observed in grizzly bears (Chapter 2). Increasing sample sizes

within age and sex groups in the same population can further explore these findings.

Posterior power analyses suggests a minimum of 5 males and 4 females in each age group

will be necessary (for significant and power levels of 0.05 and 0.80, respectively, in

groups of equal sample size) to confirm my effect sizes. Indices describing relationships

between age and telomere length could be developed by including continuous age-

estimates derived from premolar tooth growth patterns in harvested bears (Calvert and

Ramsay 1998), which will be available for my dataset in 2017. Increasing sample sizes in

skin samples will also increase statistical power to confirm and/or determine age and sex

effects, which have important implications for the utility of biopsy-based population

surveys (Pagano et al. 2014). Obtaining larger samples of genomic material across age

58

and sex groups are also relatively easier to achieve through noninvasive tissue sampling

(for the M’Clintock Channel population; van Coeverden de Groot et al. 2013) and

telomere assays of such samples will have direct implications for noninvasive surveys. It

is also likely that DNA quality and quantity and, thus, estimates and resulting indices of

telomere length will be improved with the use of commercially available kits (e.g.,

QIAGEN DNeasy Blood and Tissue Kit; QIAGEN 69506), versus the salt extraction

protocol used here. If relationships are significant, telomeres can be used to potentially

predict age and/or sex groupings of harvested and/or noninvasively sampled polar bears.

This will require evaluating accuracy in classifying an independent sample of known

samples according to T/S characteristics (Dunshea et al. 2011, Pauli et al. 2011). For

noninvasive samples, known individuals can be identified by sampling and genotyping

previously captured and aged bears (van Coeverden de Groot et al. 2013).

Given small sample sizes and additional factors contributing to variation in

telomere length, telomere qPCR of tissue samples reported here will likely not serve to

accurately determine the chronological ages of polar bears. Notwithstanding, my results

provide insights into additional factors that affect telomere length as an indicator of

biological senescence. Even with small within-group sample sizes, significant differences

in telomere lengths exist among populations in three types of tissues. Significantly longer

telomere lengths occur in polar bears from Baffin Bay versus Western Hudson Bay. In

muscle, post-hoc comparisons among populations correspond to ecologically-defined

designated units for conservation, where Western Hudson Bay, Foxe Basin, and Davis

Strait form one cluster and Baffin Bay and Lancaster Sound form another (Thiemann et

al. 2008a). Western Hudson Bay is also associated with lower prey diversity than the

other four populations, though, interestingly, a lower hunting pressure index (Thiemann

et al. 2008a). Differences in muscle telomere length also correspond to differences in

heterozygosity, with lower rates in Western Hudson Bay versus Baffin Bay and Lancaster

Sound and intermediate rates in Davis Strait and Foxe Basin (Peacock et al. 2015). Lower

heterozygosity rates might limit telomere lengthening from homologous recombination

(de Lange et al. 2006, Blasco 2007). Higher reproductive and growth rates in Western

Hudson Bay compared to the other populations (Derocher and Stirling 1998) could also

59

be contributing to higher rates of cellular turnover and, thus, shorter telomere lengths.

Globally, Western Hudson Bay is the most extensively researched polar bear

population (e.g., Taylor and Lee 1995, Lunn et al. 1997, Regehr et al. 2007). Over 80%

of the population has been marked in the past (Peacock et al. 2011, Vongraven and

Peacock 2011). This population, as well as Davis Strait, faces an annual ice-free season,

where bears must fast ashore for at least four months and eight months for denning

females (Ramsay and Stirling 1988, Stirling and Parkinson 2006). With earlier sea-ice

break up due to climate change, significant relationships with declining body condition

have been reported (Stirling et al. 1999, Regehr et al. 2007), particularly in females

(Stirling and Parkinson 2006), who also show evidence for reproductive failure (Derocher

et al. 1992). Western Hudson Bay bears have also been reported entering communities as

rogue or problem bears (Stirling and Parkinson 2006, Dowsley 2009a; Chapters 4 and 5),

facing unique stressors in comparison to other populations. Conversely, for Baffin Bay,

Inuit communities have reported population increases due to immigration from Lancaster

Sound (Dowsley 2007).

If larger sample sizes distinguish populations, telomeres may serve to implicate

unique population-specific stressors that individuals might be facing; this has important

implications for managing quotas. At a minimum, qPCR of tissues from harvested

samples can provide useful information on age, sex, and population-level differences in

telomere length. Harvested samples can also be coupled with genetic indices of

relatedness or heterozygosity of larger population groups (Cronin et al. 2009, Zeyl et al.

2009) to quantify their effects on telomere length. It is also possible to include indices of

stress and/or health, such as hair cortisol (Beschøft et al. 2011), contaminants measured

from body fat (Verreault et al. 2005), body size, and condition (Rode et al. 2010).

Ecological observations of Inuit hunters collecting samples (e.g., traditional knowledge of

bear health and condition) can also enrich this information. Determining hunter

selectivity (Chapter 4) associated with harvest samples can provide inferences on whether

telomere patterns are generalizable to polar bear populations as a whole. Increasing

sample sizes among communities can also confirm differences in telomere length that

60

correspond geographically to populations, or potential differences in hunting selection

across communities. With more comprehensive studies, population differences in

telomere length can be evaluated for predictability in an independent sample of harvested

bears.

Despite the potential utility of qPCR in polar bears, telomere lengths determined

using qPCR and TRF in grizzly bears are not comparable. This is likely an artefact of

small sample size and high coefficient of variation in the TRF assays (17.80%; Chapter

2), as qualitative trends between telomere length and age are still comparable (e.g.,

unexpected increase in telomere length with age in females versus no change in males;

Appendix 3.6.3). While TRF assays have been referred to as the “gold standard” for

telomere length measurements, this technique will have little applicability or feasibility

for polar bear monitoring programs. It is unknown how sensitive qPCR is to varying

degrees of tissue degradation that might be expected from harvest sampling across

communities. The effect of tissue and/or DNA degradation and different storage methods

(Wong et al. 2012) could certainly be explored. Obtaining a range of high quality and

quantities of genomic material is difficult in polar bears because most invasive samples

are dependent on harvest-based sampling by hunters. Where freezing below conventional

deep freezer or ambient freezing temperatures are not available, quality of salvaged polar

bear tissues might be improved with alternative methods such as storing samples in

DNAgard (Wong et al. 2012). It is unknown how effective these chemicals are at high-

arctic temperatures (e.g., freezing during travel to sampling sites), and effects of freezing

on storage quality could be evaluated prior to field sampling. Isolating DNA from

samples immediately or as soon as possible after collection can also improve sample

quality (Wong et al. 2012), for example, at research centers in larger communities. DNA

extractions could be conducted with relative ease using non-toxic salt extraction methods

(Bruford et al. 1992). However, this would require substantial funding to operate

facilities, engage communities, and educate hunters to coordinate sampling and storage

according to standards (Wong et al. 2012). For polar bears, TRF assays could still be

developed in captive animals, but this would require long-term collaborations with zoos

to acquire adequate sample sizes that vary in age and sex, and population and/or origin, as

61

sampling usually occurs on an opportunistic basis. Assays in captive polar bears would

also likely be the most practical opportunity for longitudinal studies. Still, it is unknown

how applicable or useful telomere indices found in captive animals will be for wild

animals without comparisons.

In initiating efforts to characterize telomeres across different age, sex, and

population groups of polar bears, this work demonstrates the utility of qPCR in detecting

differences in telomere length using heart, muscle, and skin tissues salvaged from

harvested animals. While significant differences in telomere length across polar bear

populations could reflect local genetic and ecological stressors, differences among age

groups and sex require further investigations using larger sample sizes. With the inclusion

of additional scientific data on life-history and ecological observations provided by

hunters, a more comprehensive evaluation of telomeres as a marker of biological

senescence across polar bear populations will be enabled.

62

3.6 Appendix

3.6.1 Development of a TRF assay of captive (zoo) polar bear

samples

Samples for TRF assays were collected through individual research agreements with

Toronto Metro, Albuquerque Biopark, Cleveland Metroparks, Brookfield, Buffalo, North

Carolina, SeaWorld (San Diego), and San Diego zoos and the U.S. Fish and Wildlife

Service to transport samples. After research agreements were established, I distributed

instructions for sampling, storage, and transport (10mL of fresh blood collected into

vacutainers with EDTA, stored at -80°C, transported via FedEx Priority Overnight on dry

ice) to each zoo. Samples were previously or opportunistically collected during routine

exams by zoo veterinarians and shipped to the University of Texas Southwestern Medical

Center. For each sample, I distributed sample information sheets to each institution to

collect information on sex and age of the originating specimen, specimen numbers,

birthplace and/or length in captivity, any previous zoo (holding) locations, past health

conditions of concern, and purpose of anaesthesia or exam during which the sample was

collected. I processed and analyzed samples at the University of Texas Southwestern

Medical Center (Shay/Wright Lab) over three weeks in July 2013.

I isolated, visualized, quantified, and aliquoted DNA samples using methods

described in Chapter 2. TRF assays followed a modified protocol described by Herbert et

al. (2003). These procedures differed from TRF assays conducted in grizzly bears

(Chapter 2) due to differences in local laboratory TRF protocols and availability of

samples, materials, and/or equipment. Briefly, samples were digested with six enzymes

(HinfI, HaeIII, AluI, RsaI, MspI and HhaI) instead of two (RsaI and HinfI) and run out on

0.7% (w/v) agarose gels. I ran TRFs on a single gel that was denatured prior to in-gel

hybridization to a radioactive telomere repeat probe, which reduces background noise in

comparison to Southern blot hybridization (Herbert et al. 2003).

A total of 14 blood and eight DNA samples were collected opportunistically from

63

18 captive polar bears. Nineteen samples (14 individuals) provided sufficient DNA

quantities for TRFs (at least 2µg per assay), as several preliminary trials were required to

develop the technique. Due to limited time and funding available to process and complete

these optimizations abroad, only one gel (Appendix 4) was completed. TRF distributions

fell beyond the ladder range (10kb to 0.50kb; Bionexus Hi-LoTM DNA marker) and, thus,

could not be quantified (Horn et al. 2010). Without a control (sample of known TRF

range) or replicate assays, results from these trials are inconclusive.

64

Appendix 4. A TRF gel of polar bears samples provided by zoos. Samples are labeled at

the top of each lane, as well as a negative control (NEG). Two grizzly bear samples

(GB16274 and GB16273) were included for comparison. AK741 and AL063 produced

no signal. PB9769, PB5579, AK732, AK731, AK734, and M0211A produced weak

signals. A high molecular weight ladder is shown on the right lane alongside the samples

(MW), with fragments labelled in kilobase pairs (kb).

65

3.6.2 Supplementary analyses

Appendix 5. Results from non-significant paired t-tests comparing T/S among polar bear

heart, muscle, and skin tissues (N=40, 39, and 40 individuals, respectively).

Comparison t value df Probability

Heart and muscle -0.60 38 0.55

Heart and skin 1.02 39 0.31

Muscle and skin 1.29 38 0.21

Appendix 6. A one-way analysis of variance using type III sums of squares showing the

significant effect of population on heart T/S in 39 polar bears (one outlier was excluded

from the original sample of 40).

Predictor Type III sums of

squares


Population 2.88 4 9.011 4.50x10-5

Residuals 2.71 34

66

Appendix 7. A multi-factor analysis of variance using type III sums of squares showing

significant effects of age, sex, population, and the interaction between age and sex on

muscle T/S in 38 polar bears (one outlier was excluded from the original sample of 39).

Predictor Type III sums of

squares


Intercept 17.31 1 196.55 6.53x10-14

Age 3.13 2 17.76 1.20x10-5

Sex 4.49 1 51.018 1.11x10-7

Population 4.14 4 11.76 1.16x10-5

Age*sex 4.066 2 23.078 1.43x10-6

Residuals 2.38 27

67

3.6.3 Age, sex, and stress effects on grizzly bear telomere length

using qPCR

QPCR was conducted for 17 grizzly bear blood samples (from nine males and eight

females) that provided enough DNA for this analysis. Fourteen of these samples were

associated with TRF measurements (see text). Using the model for telomere length that I

developed with TRF assays (Chapter 2), I determined the effect of age, sex, HCC, and

GGT, and the interaction between age and sex on blood T/S using an ordinary least

squares linear regression. I examined the data set for outliers and model assumptions

(normality, constant error variance [homoscedasticity], and collinearity). I also

determined the effect of age on blood T/S separately in males and females through linear

regression. Significant levels were set at an alpha (P) of 0.05.

Blood T/S ranged from 0.69 to 1.015 (Appendix 8). Effects of age, sex, HCC,

GGT, and the interaction between age and sex on blood T/S were not significant

(Appendix 9). There was no evidence for outliers, departures from normality,

heteroscedasticity, or collinearity. The effect of age on blood T/S was not significant in

nine males (r2=2.35x10-7, F1,7=1.65x10-6, P=1.00) and eight females (r2=0.0056,

F1,6=0.034, P=0.86). Qualitatively, the relationship between age and telomere length

using qPCR (blood T/S) in males and females followed a similar trend to that using TRF

assays (mean TRF; Appendix 10, Figure 2).

68

Appendix 8. Blood T/S measured from qPCR and mean TRF length (in kilobase pairs)

measured from TRF assays in 17 grizzly bear samples (nine males and eight females).

“NA” refers to data that were not available.

Sample Blood T/S Mean TRF (kb)

AB5299X 1.01 11.61

ABNW4678 0.77 11.75

G016 0.78 NA

G119A 0.77 12.57

G120 0.81 NA

G126 0.95 12.03

G129 0.80 12.76

G150 0.69 12.56

G151 0.75 11.35

G152 0.92 11.06

G260 0.89 13.66

G270 0.87 11.91

G275 0.85 12.40

G278 0.92 12.55

G280 0.76 NA

G287 0.85 14.13

G288 0.94 13.77

69

Appendix 9. A general linear model for the effect of age, sex, HCC, GGT, and the

interaction between age and sex on blood T/S in 17 grizzly bears. Effects were not

significant.


Intercept 0.87 0.073 12.01 2.13x10-6

Age 5.99x10-4 0.0052 0.12 0.91

Sex -0.067 0.12 -0.56 0.59

HCC 0.0063 0.0080 0.79 0.46

GGT -0.0012 0.0011 -1.063 0.32

Age*sex 0.0070 0.020 0.36 0.73

70

Appendix 10. A graph showing non-significant linear regressions between blood T/S and

age in 17 grizzly bears. Trends are similar to relationships using TRF assays (Chapter 2,

Figure 2). A dashed line represents the linear regression between blood T/S and age in

nine males (open circles) while a solid line represents the linear regression between blood

T/S and age in eight females (filled circles).

0 5 10 15 20

0.70

0.75

0.80

0.85

0.90

0.95

1.00

Age (years)

Blo

od T

/S

71

3.6.4 QPCR data and standard curves for six telomere and

reference primer plates

Appendix 11. Polar bear samples collected by Inuit hunters for qPCR corresponding to

community that provided the sample, population where the sample was harvested, age,

and sex diagnoses. DS=Davis Strait, WHB=Western Hudson Bay, LS=Lancaster Sound,

FB=Foxe Basin, and BB=Baffin Bay. “NA” refers to a single case where age data was

not available. Heart, muscle, and skin samples were collected from each individual.

Sample Community Population Age Sex

L39002 Iqaluit DS Adult Male


L39019 Arviat WHB Adult Male

L39020 Rankin Inlet WHB Adult Male

L39021 Arviat WHB Subadult Female

L39022 Arviat WHB Subadult Female




L39027 Arviat WHB Cub Female

L39044 Rankin Inlet WHB Subadult Male

L39046 Rankin Inlet WHB Adult Male

L39056 Iqaluit DS Subadult Male


L39206 Grise Ford LS Adult Male

L39211 Grise Ford LS Adult Male



L39220 Igloolik FB Cub Male

L39223 Igloolik FB Cub Male

L39224 Igloolik FB Cub Female

L39231 Hall Beach FB Adult Female

72

L39254 Igloolik FB Adult Female

L39258 Arctic Bay LS Adult Male

L39260 Arctic Bay LS Adult Female


L39266 Arctic Bay LS NA Male

L39267 Arctic Bay LS Adult Female

L39271 Arctic Bay LS Subadult Male


L39283 Clyde River BB Adult Male

L39291 Clyde River BB Subadult Female

L39294 Clyde River BB Adult Male

L39307 Pond Inlet BB Adult Male





L39325 Pond Inlet BB Adult Female


73

Appendix 12. Cycle threshold values (Ct) for Plate 1 of 6 telomere (telc/telg) and

reference (RPLP0-F1/RPLP0-R1) qPCR assays. Telomere and reference primers were

run in singleplex; both plates were run at the same time on separate machines. Samples

were run in triplicate while five standard dilutions (Z19312D) were run in duplicate.

Sample identification ending in “HG”, “MG”, and “SG” denote heart, muscle, and skin

samples, respectively.

Sample Telomere Ct Reference Ct

L39002HG 15.41 22.71

15.23 22.66

15.13 22.62

L39002MG 15.14 22.71

15.08 22.68

15.15 22.60

L39002SG 16.31 23.77

16.31 23.79

16.29 23.67

L39014HG 14.55 22.67

14.62 22.56

14.62 22.56

L39014MG 15.18 21.64

15.11 22.47

15.27 23.02

L39014SG 14.12 22.35

14.03 22.26

14.08 22.30

L39019HG 15.22 22.94

15.33 23.16

15.29 23.22

L39019MG 14.93 24.13

16.00 23.94

74

15.90 24.07

L39019SG 14.42 22.77

14.62 22.69

14.64 22.78

L39020HG 13.69 22.21

13.88 22.23

13.92 22.21

L39020MG 16.27 23.46

16.29 24.00

16.47 24.20

L39020SG 14.13 22.34

14.19 22.43

14.23 22.43

L39021HG 13.84 20.70

14.05 22.18

14.14 22.17

L39021MG 12.97 22.72

14.45 22.75

14.73 22.90

L39021SG 14.04 22.52

14.12 22.57

14.24 22.50

L39022HG 15.04 22.93

15.20 23.04

15.24 22.97

L39022MG 16.56 24.28

16.50 24.19

16.53 24.06

L39022SG 13.78 22.04

13.95 21.99

13.89 22.05

75

L39023HG 15.54 23.04

15.44 23.10

15.37 23.10

L39023MG 14.81 23.32

15.33 23.39

15.46 23.39

L39023SG 14.19 22.28

14.16 22.29

14.09 22.26

L39024HG 14.93 23.58

15.61 23.50

15.71 23.38

L39024MG 16.34 23.95

16.17 23.96

16.31 23.31

L39024SG 14.22 22.50

14.55 22.53

14.51 22.51

L39025HG 15.39 23.29

14.57 23.40

15.39 23.38

L39025MG 15.60 23.38

15.38 23.52

15.14 23.46

L39025SG 14.79 22.12

14.74 22.98

14.91 23.11

L39027HG 14.45 21.64

14.32 22.32

14.49 22.42

Z19312D - 0.16ng/reaction 23.90 31.11

76

23.84 31.23

Z19312D - 0.80ng/reaction 21.25 28.84

21.21 28.68

Z19312D - 4.00ng/reaction 18.65 26.37

18.61 26.70

Z19312D - 20.00ng/reaction 15.84 23.85

15.91 23.95

Z19312D - 100.00ng/reaction 12.86 21.68

12.96 21.76

77








L39044HG 14.54 23.48

15.57 23.53

16.27 23.60

L39044MG 16.62 23.70

16.09 23.97

16.81 24.34

L39044SG 17.43 26.18

17.41 25.72

17.56 25.97

L39046HG 16.94 25.26

16.01 25.38

16.88 25.35

L39046MG 15.44 23.92

15.69 23.99

15.68 23.91

L39046SG 15.76 23.47

15.19 23.67

15.39 23.58

L39056HG 14.72 22.89

14.57 22.75

14.74 22.63

L39056MG 15.63 23.37

15.23 23.57

78

15.63 23.58

L39056SG 15.45 23.68

16.22 23.77

15.95 23.47

L39058HG 16.26 24.30

16.16 24.43

16.56 24.31

L39058MG 15.22 23.63

15.43 23.81

15.69 23.75

L39058SG 14.37 22.94

14.44 22.98

14.81 22.99

L39206HG 14.38 23.00

14.07 22.93

14.76 22.94

L39206MG 16.36 24.97

16.73 25.04

16.68 25.08

L39206SG 13.98 22.71

14.27 22.83

14.32 22.61

L39211HG* 13.80 20.34

14.60 21.23

13.93 20.90

L39211MG 16.53 24.39

16.43 24.03

16.42 23.99

L39211SG 14.68 22.88

14.40 22.80

14.33 22.85

79

L39212HG 14.82 22.64

14.48 22.57

14.35 22.57

L39212MG 14.03 23.35

15.33 23.42

15.21 23.33

L39212SG 15.14 23.28

14.96 23.47

14.90 23.12

L39214HG 15.23 23.48

15.25 23.37

15.67 23.42

L39214MG 16.46 25.10

17.43 24.98

17.31 24.94

L39214SG 15.19 22.73

15.05 22.58

14.78 22.61

L39220HG 14.92 22.76

14.54 22.83

14.68 22.65

L39220MG 15.09 23.14

14.82 22.58

15.02 23.23

L39220SG 14.65 23.23

14.27 23.27

14.54 23.28

L39223HG 13.96 23.10

14.22 23.13

14.20 23.06

Z19312D - 0.16ng/reaction 22.43 29.19

80

22.42 29.30

Z19312D - 0.80ng/reaction 20.33 28.39

20.11 28.50

Z19312D - 4.00ng/reaction 17.97 26.05

19.06 26.36

Z19312D - 20.00ng/reaction 15.17 23.79

15.53 23.79

Z19312D - 100.00ng/reaction 12.81 21.78

13.04 21.80 * Ct values for this sample fell outside the standard range; this sample was diluted 10X

and re-run on Plate 6.

81








L39223MG 15.37 23.61

15.19 23.74

15.34 23.66

L39223SG 14.55 22.71

14.40 22.74

14.62 22.89

L39224HG 15.09 23.36

14.63 23.26

14.95 23.27

L39224MG 15.17 23.61

14.98 23.67

15.09 23.71

L39224SG 13.63 22.65

13.49 22.64

13.45 22.71

L39231HG 14.97 23.13

14.59 23.10

14.79 23.05

L39231MG 15.80 23.94

15.81 23.92

15.80 23.96

L39231SG 16.75 25.04

16.43 25.05

82

16.48 25.05

L39254HG 15.03 22.95

15.63 22.04

15.37 22.71

L39254MG 14.63 23.27

15.43 23.72

15.58 23.51

L39254SG 13.86 22.46

13.95 22.42

14.21 22.37

L39258HG 13.65 23.06

14.82 22.95

14.98 22.94

L39258MG 14.90 23.58

15.45 23.54

15.17 23.48

L39258SG 13.98 22.90

13.91 22.95

14.13 22.96

L39260HG 14.65 22.95

14.84 22.96

14.88 22.83

L39260MG 16.14 23.94

16.25 22.83

16.34 24.02

L39260SG 14.42 22.27

14.47 22.27

14.28 22.26

L39262HG 15.36 23.06

15.67 23.04

15.60 23.13

83

L39262MG 15.77 24.32

16.38 23.94

16.08 24.15

L39262SG* 25.20 36.66

25.25 35.68

25.29 36.57

L39266HG 14.25 22.50

14.27 22.41

14.05 22.53

L39266MG 13.94 23.92

15.99 23.83

15.72 23.98

L39266SG 16.25 22.40

16.01 23.68

16.08 23.83

L39267HG 15.65 23.19

15.52 23.26

15.08 23.16

L39267MG 16.16 22.22

16.13 23.86

16.41 23.77

L39267SG 13.72 22.17

13.55 22.30

13.86 22.26

L39271HG 14.19 22.84

14.26 22.90

14.48 22.63

L39271MG 14.89 22.36

14.82 23.44

14.97 23.40

Z19312D - 0.16ng/reaction 22.63 30.58

84

22.54 30.68

Z19312D - 0.80ng/reaction 20.17 28.47

19.97 28.31

Z19312D - 4.00ng/reaction 18.21 26.13

18.70 27.66

Z19312D - 20.00ng/reaction 15.70 23.79

15.91 23.86

Z19312D - 100.00ng/reaction 12.66 21.77

13.29 21.65 * Ct values for this sample fell outside the standard range; this sample re-run on Plate 6

using a lower dilution (more concentrated sample).

85








L39271SG 14.99 22.59

13.95 22.47

13.92 22.53

L39278HG 18.79 26.92

18.31 26.78

18.79 26.70

L39278MG 16.38 23.80

16.32 24.01

16.40 24.09

L39278SG 14.88 23.02

14.90 22.95

14.90 23.04

L39283HG 15.68 23.09

15.70 23.36

15.75 23.49

L39283MG 16.94 24.65

16.93 24.59

16.96 24.47

L39283SG 14.34 22.74

14.35 22.70

14.42 22.67

L39291HG 14.92 22.96

14.91 23.08

86

14.94 22.93

L39291MG 14.98 23.06

15.23 23.12

15.03 23.22

L39291SG 14.39 22.91

14.38 22.92

14.38 22.89

L39294HG 14.39 22.92

15.07 22.96

15.05 22.57

L39294MG 15.29 23.29

14.41 23.39

14.91 23.48

L39294SG 15.47 23.60

15.55 23.56

15.57 23.58

L39307HG 14.92 22.88

15.04 23.06

15.14 22.99

L39307MG 16.25 23.48

15.93 24.17

15.25 22.99

L39307SG 13.85 22.06

13.99 21.92

13.97 21.81

L39310HG 17.44 24.08

16.50 24.98

16.98 25.06

L39310MG 17.84 25.24

17.75 25.29

17.70 25.23

87

L39310SG 15.38 23.18

15.21 23.26

15.33 23.26

L39313HG 16.06 23.84

15.97 24.00

15.70 24.01

L39313MG 14.81 22.94

15.98 23.77

14.93 23.38

L39313SG 15.98 24.07

15.85 24.04

15.86 24.06

L39314HG 16.43 24.09

16.06 23.95

16.03 23.92

L39314MG 15.94 20.95

15.47 19.28

15.24 21.50

L39314SG 15.51 23.58

15.56 23.79

15.56 23.59

L39316HG 16.75 24.42

16.60 24.47

16.61 24.52

L39316MG 18.25 25.53

17.77 26.09

17.19 26.04

L39316SG 16.34 24.21

16.35 24.33

16.45 24.28

Z19312D - 0.16ng/reaction 23.16 30.59

88

23.15 30.54

Z19312D - 0.80ng/reaction 20.57 28.44

20.58 28.37

Z19312D - 4.00ng/reaction 18.16 26.04

17.96 26.13

Z19312D - 20.00ng/reaction 14.92 23.68

15.42 23.91

Z19312D - 100.00ng/reaction 12.94 21.80

13.08 21.78

89








L39027MG 16.94 24.30

16.54 24.19

16.76 24.64

L39027SG 14.26 22.65

14.28 22.56

14.19 22.60

L39325HG 15.18 23.52

15.66 22.11

15.67 23.23

L39325MG 15.78 23.22

14.88 21.01

16.00 22.92

L39325SG 14.57 22.42

14.43 22.31

14.54 22.34

L39326HG 15.29 23.67

15.63 23.47

15.67 22.97

L39326MG 16.25 24.38

16.42 24.31

16.43 24.11

L39326SG 14.81 22.23

14.33 22.70

90

14.33 22.39

Z19312D - 0.16ng/reaction 24.43 30.91

24.41 30.96

Z19312D - 0.80ng/reaction 21.61 28.69

21.56 28.93

Z19312D - 4.00ng/reaction 18.73 26.25

18.60 26.39

Z19312D - 20.00ng/reaction 15.83 23.67

13.62 23.80

Z19312D - 100.00ng/reaction 12.92 21.65

12.55 21.80

91




were run in triplicate while five standard dilutions (Z19312D) were run in duplicate. This

plate included grizzly bear samples as well as two polar bear samples (L39211HG [heart]

and L39262SG [skin]).


G275 16.29 24.52

16.51 24.53

16.27 24.50

G278 15.74 24.15

16.08 24.13

16.34 24.13

G126 16.21 24.39

16.30 24.29

16.44 24.25

G119A 15.95 24.33

15.98 24.26

15.93 24.33

G016 15.83 24.16

15.93 24.43

15.83 24.09

G120 16.47 24.52

16.14 24.56

16.00 24.26

ABNW4678 16.87 25.09

16.67 25.02

16.69 24.85

AB5299X 15.74 23.24

14.84 23.18

92

14.74 23.11

G288 15.78 24.06

16.09 23.96

15.92 23.97

G287 15.87 23.94

15.63 24.01

15.74 24.04

G280 15.71 24.19

15.83 24.20

15.88 24.20

G270 15.81 24.06

15.95 24.12

15.95 24.11

G260 15.68 24.07

15.86 24.03

16.12 24.03

G152 15.74 23.86

15.89 23.97

15.87 24.00

G151 15.28 23.87

15.54 23.94

15.55 23.95

G150 15.57 24.26

15.61 24.19

15.71 24.16

G129 15.90 24.21

15.93 24.22

15.98 24.28

L39211HG* 18.72 24.96

18.23 25.63

18.29 25.77

93

L39262SG* 14.35 21.17

14.12 22.17

14.29 22.56

Z19312D - 0.16ng/reaction 24.43 31.52

24.45 31.08

Z19312D - 0.80ng/reaction 21.74 28.92

21.55 28.44

Z19312D - 4.00ng/reaction 18.82 26.55

18.78 26.36

Z19312D - 20.00ng/reaction 16.13 23.92

16.21 23.91

Z19312D - 100.00ng/reaction 13.38 21.88

13.20 21.66

* Samples were run a second time after producing Ct values that fell outside the standard

range on the first attempt.

94

Appendix 18. Melt curves for seven dilutions ranging from 0.0064 to 10ng per reaction in

duplicate (14 reactions) showing a single peak, confirming specificity of telomere

(telc/telg) primers.

95

96

Appendix 19. Melt curves for seven dilutions ranging from 0.0064 to 10ng per reaction in

duplicate (14 reactions) generally showing a single peak, confirming specificity of

reference (RPLP0-F1/RPLP0-R1) primers.

97

Appendix 20. Characteristics of standard curves six telomere (telc/g) and reference

(RPLP0 [F1/R1]) qPCR plates. For each plate and primer, standard curves were

generated through a log-linear regression of five standard dilutions (0.16ng, 0.80ng,

4.00ng, 20.00ng, and 100.00ng per reaction) as predictors of mean threshold cycle

number for fluorescence detection (Ct).

Plate Slope Intercept r2 Efficiency

telc/g RPLP0 telc/g RPLP0 telc/g RPLP0 telc/g RPLP0

1 -3.90 -3.99 20.85 28.47 1.00 1.00 0.80 0.78

2 -3.42 -2.78 19.94 27.58 0.99 0.98 0.96 1.29

3 -3.36 -3.21 20.00 28.22 0.99 0.99 0.98 1.05

4 -3.67 -3.17 20.20 28.04 1.00 1.00 0.87 1.07

5 -4.33 -3.37 21.03 28.33 0.99 1.00 0.70 0.98

6 -3.97 -3.41 21.26 28.48 1.00 1.00 0.78 0.97

3.6.5 Model selection for telomere length


most parsimonious model (ΔAIC) for models of heart T/S in 40 polar bears. Backwards

model selection began with age, sex, population, and the interaction between age and sex

as predictors and ended with a null (intercept-only) model. The most parsimonious model

is indicated in bold.

Model df AIC ΔAIC

Age + sex + population + age*sex 13 37.81 4.97

Age + population + age*sex 12 36.01 3.17

Age + population 8 34.67 1.83

Population 6 32.84 0.00

Null 2 47.19 14.35

98


most parsimonious model (ΔAIC) for models of muscle T/S in 39 polar bears. Backwards




Model df AIC ΔAIC


Age + sex + population 9 58.68 30.87

Sex + population 7 58.05 30.25

Sex 3 62.11 34.31

Null 2 63.56 35.76


most parsimonious model (ΔAIC) for models of skin T/S in 40 polar bears. Backwards




Model df AIC ΔAIC


Age + sex + population 9 31.12 2.31

Age + population 8 29.23 0.43

Population 6 38.02 9.21

Null 2 48.96 20.15

99

Chapter 4

Inuit methods of identifying polar bear 4

characteristics: potential for Inuit inclusion in

polar bear surveys

4.1 Summary

Due to their close proximity to and frequent interactions with polar bears, Inuit hunters

are aware of changes in polar bear population ecology and characteristics. This valuable

information could contribute to any polar bear research and/or monitoring program.

Understanding how Inuit gather ecological information on polar bears and how individual

experiences shape this knowledge can also overcome any barriers to Inuit inclusion in

bear monitoring and management. Based on interviews in four Nunavut communities, I

report Inuit hunting experiences and methods of identifying polar bear sex, age, and body

size, as well as health. Across communities, Inuit share techniques in identifying and

distinguishing bear characteristics that overlap with scientific methods, suggesting Inuit

could provide immediate and inexpensive information toward polar bear research

programs. Hunting preferences are shaped by individual experiences with polar bears

(e.g., through hunting or bear encounters), as well as familiarity with polar bear research

and management. Identifying and incorporating community perspectives in management

could encourage local support for programs that impact Inuit knowledge formation and

persistence.

4.2 Polar bear conservation and harvest management in

Nunavut

The need for contemporary data on polar bear population trends parallels a growing need

for management actions, which undoubtedly impacts northern communities

economically, socially, and ecologically. Inuit legally harvest polar bears (Indian and

100

Northern Affairs Canada [INAC] 1993) for traditional and personal uses, including meat

for consumption, hides for clothing, bedding, and/or auctions, and bones for carving

(Foote and Wenzel 2009). Guided by Inuit using non-motorized (Inuit-based) methods

(INAC 1993), trophy hunters also harvest polar bears. This activity reinvests economic

benefits into a subsistence economy for Inuit through employment, providing wages for

guides, assistants, outfitters, dog owners, and cooks (Foote and Wenzel 2009, Tyrrell

2009, Wenzel 2009). Due to frequent interactions with polar bears and the importance of

polar bears to them, Inuit continue to gather data on ecological effects of habitat change

(Dowsley 2009a) and human activities (Keith et al. 2005) on polar bears, as well as sex,

age, and body size of bears encountered (Wong et al. 2011). This activity is independent

from scientific monitoring and management. This knowledge comprises Inuit

qaujimajatuqangit (IQ), which is defined as a guiding principle for how Inuit

conceptualize human-wildlife relationships and how this affects their interactions with

and perceptions of animals (Wenzel 2004). In this manner, Inuit could offer a nuanced,

historical and contemporary understanding of polar bear population activity to

complement ongoing scientific surveys in conservation and management.

Inuit traditional ecological knowledge (TEK)—ecological observations that are

acquired through experience and passed on from one generation to the next (Berkes et al.

2000)—is a component of IQ that is already considered in wildlife co-management and

conservation decision-making at territorial (INAC 1993) and national levels (e.g.,

Government of Canada 2002). In Canada, polar bears are managed according to 13

populations using the best available local and scientific knowledge (Peacock et al. 2011,

Vongraven and Peacock 2011). In Nunavut, territorial (Nunavut Wildlife Management

Board) and regional wildlife boards and community Hunters and Trappers Organizations

(HTO) establish harvest quotas (Tyrrell and Clark 2014) for each population, sanctioned

by land claim agreements (INAC 1993), and allocate these quotas to HTOs within

communities harvesting the same population (Dowsley 2009a, Peacock et al. 2011).

These quotas are male-biased to protect females and cubs. HTOs subsequently distribute

tags to individual hunters, usually through a lottery. HTOs also gather and represent local

101

community interests to higher levels of government through community consultations

and public meetings (Dowsley 2009b, Dowsley 2010).

Scientific community-based monitoring programs and data collection ultimately

inform management decisions affecting communities (e.g., allocation of harvest quotas).

Inuit hunters frequently receive employment as guides and research assistants in polar

bear surveys (e.g., Wong et al. 2011, Van Coeverden de Groot et al. 2013), which allow

them to apply and reinforce their experience and traditional skills in research contexts.

Harvest monitoring programs, where hunters actively collect biological samples and

morphometric data from harvested bears, also allow population data (e.g., minimum

abundance, sex and age distribution, health correlates, etc.) to be collected in the years

between population surveys. Independent from research participation, Inuit TEK and

experience have the potential to reveal critical population trends (e.g, Dowsley 2009a,

Kotierk 2012, Kotierk 2010) before scientific surveys are conducted.

Unfortunately, uncertainty and the dearth of data on range-wide polar bear

responses to climate change has contributed to political tension and conflict among

stakeholders, decision-makers, scientists and northern communities (Derocher et al.

2004, Tyrrell 2006, Clark et al. 2008, Tyrrell and Clark 2014). Sustainable harvest rates

rely largely on scientifically collected population data (e.g., sex, age, and body condition;

e.g., Bromaghin et al. 2015) associated with aerial mark-recapture methods (e.g., tattoos,

radio-collars, and ear tags) that are not supported by all communities (Tyrell 2006).

Though less-invasive alternatives to gathering the same data have recently been

developed (e.g., Van Coeverden de Groot et al. 2013, Stapleton et al. 2014), scientific

surveys remain expensive (Dowsley 2009a), time-intensive, and often logistically

challenging (Stapleton et al. 2014) to conduct. Not surprisingly, scientific surveys occur

infrequently and research intensity, time scales, and techniques vary among populations

(Vongraven and Peacock 2011).

Beyond the lack of information on most polar bear populations (Peacock et al.

2011, Vongraven and Peacock 2011), criticisms against both TEK and scientific types of

102

information that inform decision-making have also created challenges in and barriers to

co-management. Other nations have criticized Canada for considering TEK in decision-

making (Tyrrell and Clark 2014), perhaps due to the context-specific nature of TEK that

is actively shaped by the knowledge holder and/or gatherer (Houde 2007) and differs

from objective, conventional natural sciences. Communities across the north also criticize

decisions based on scientific practices (Tyrrell 2009), which might be due, in part, to past

misconceptions of research and management practices by local communities and failure

to address northern interests by research and management practitioners leading to

mistrust (Moller et al. 2004, Clark et al. 2008). TEK comprises only a small component

of IQ that, while containing information on the biophysical environment that could be

integrated into conventional management and policy with relative ease, lacks the breadth

of cultural, ethical and ontological approaches to managing and interacting with wildlife

that IQ encompasses as a whole (Wenzel 2004). Incorporating these elements of IQ into

any research program could overcome some of these barriers.

At local scales, supporting the role played by Inuit in polar bear monitoring

programs can increase understanding of TEK and/or IQ and scientific information by

Inuit and scientific communities alike, while addressing gaps in population data. In these

contexts, documenting Inuit methods of and motivations for identifying polar bear

characteristics can highlight Inuit methods of characterizing population information at a

level finer than broad trends in abundance and, more importantly, IQ of Inuit

relationships with polar bears. IQ influences decision-making through co-management

yet, through impacts on harvesting opportunities, management decisions could also affect

the persistence of IQ. An understanding of how management regulations direct and

influence the process of Inuit knowledge formation can provide insights into receptivity

and levels of local support for those management decisions. For Inuit, documenting Inuit

methods can also safeguard IQ for future generations for Inuit.

Expanding on previous interviews with Gjoa Haven hunters (Wong et al. 2011), I

report on interviews with 23 hunters and 33 elders (48 men and 8 women) that range in

their participation in hunting, research, and management activities. Interviews occur

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across Nunavut in Gjoa Haven, Arctic Bay, Arviat and Kimmirut. Dialogues point to

cultural factors and regulations that shape hunting selection and the context through

which polar bear knowledge is gathered, providing insight into knowledge persistence. I

highlight Inuit hunting experiences and methods for identifying sex, age, and body size of

polar bears, as well as health to determine their potential inclusion and relevance in polar

bear monitoring and research.

4.3 Methods

Interviews built on previous assessments of consistency and accuracy in Inuit estimates

of polar bear characteristics from in situ tracks with Gjoa Haven hunters, which largely

focused on inferences from tracks and provided little information on management

perspectives and hunting preferences (Wong et al. 2011). I initiated interviews for

methods of identifying polar bear characteristics with additional Gjoa Haven hunters and

elders and a single Kugaaruk hunter. I expanded these interviews by including Arctic

Bay, Kimmirut, and Arviat communities who participate in ongoing harvest monitoring

programs in collaboration with the Government of Nunavut. Together these communities

span all three Nunavut regions (Kitikmeot, Qikiqtaaluk, and Kivalliq), covering a broad

range in community perspectives and methods and polar bear ecology (Figure 15).

Face-to-face meetings with HTOs occurred in each community to discuss research

objectives, recruitment, and wages except in Arviat, where these discussions occurred

over telephone. HTOs prescribed and led all recruitment procedures. I recruited interview

participants through a combination of key informant and snowball sampling methods

(Marshall 1996). HTOs and appointed interpreters initially recommended interview

participants and, unless they were absent from the community (e.g., out of town or out

hunting on the land), all recommended participants participated in this work. With the

exception of Kimmirut, where participants were recruited through HTO recommendation

only, I also made radio announcements for interview locations and times (based on HTO

recommendation) to provide the opportunity for all community members to participate if

they wished to do so and, thus, covered a broad range in perspectives (Marshall 1996).

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Initial interview participants recommended additional, experienced community members

until I recruited a maximum of 20 participants from each community (based on budget

constraints) or data became saturated (no new themes emerged).

I identified participants as elders (60 years old or older and recognized for his/her

experience on the land among other community members) and hunters (less than 60 years

old and usually less experienced than elders). I also categorized participants according to

hunting experience: active hunters, non-active hunters (who have hunted but no longer do

so [e.g., elders]), and less-experienced hunters, who have assisted community members

with hunts and would hunt upon receiving a tag. To protect confidentiality and assist

readers in linking themes and quotations to each community, I coded participant names

according to their home community (Gjoa Haven [GH], Arctic Bay [AB], Kimmirut [K]

and Arviat [AR]) and the order of interview; I interviewed one Kugaaruk hunter in Gjoa

Haven (KU).

I conducted semi-structured interviews with open-ended questions following a

guideline (Huntington 2000, Table 7). Follow-up questions were intended to encourage

participants to produce their own understanding and clarify our discussions (Huntington

1998). Interviews began with direct icebreaker questions (e.g., name, age, birthplace)

followed by discussions on methods for identifying polar bear sex, age, and body size.

Additional discussions on identifying health of polar bears occurred in Arctic Bay,

Kimmirut, and Arviat. To determine context and motivation for learning these methods, I

documented participant interactions with polar bears (e.g., through hunting, guiding sport

hunts, encounters while hunting other animals) and preferences for particular bear

characteristics when hunting.

Though I covered most anticipated topics (following the guideline), additional

relevant topics were raised by some participants, such as how to identify aggressive or

dangerous bears (usually reported by Arviat participants), personal encounters with polar

bears, and discussions over hunting and identification techniques unique to some

participants. I did not probe for these unique experiences when participants did not

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mention these topics themselves to ensure participants led discussions according to their

own knowledge. Accordingly, if a participant did not mention a particular observation,

perspective, or theme it did not necessarily mean that they had (or lacked) knowledge or

experience on the subject (e.g., they simply did not mention it), unless they explicitly

indicated so.

I used an audio recorder to allow for subsequent transcribing. I recorded all

nonverbal cues, verbal styles, and relevant information that were informally shared in a

journal along with personal reflections. I analyzed interviews following conventional

content analysis, where categories, themes, and coding names were allowed to emerge

from the data without any preexisting theory (Hsieh and Shannon 2005). I summarized

unique participant perspectives, original quotations, and information that best-described

common themes and categories that arose through discussions.

Communities varied in local harvest regulations, seasons, and constraints, as well

as access to technology (Ford et al. 2006). Participant age, interpretations, recollections,

and sensitivity to topics were also shown to influence individual knowledge and

responses (Huntington 2000, Gagnon and Berteaux 2009). Together these contexts

shaped participant responses and interpretations. Hence, data validation by re-visiting,

reporting back to and engaging with HTOs constituted a critical form of peer review

(Huntington 2004) to ensure participants were accurately represented. Follow-up

meetings with HTOs occurred to clarify my interpretations and discuss preliminary

results, while allowing representative community members to incorporate additional

information that they felt was important and relevant. This additional effort revealed

community-wide hunting perspectives and concerns.

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Figure 14. A map displaying Gjoa Haven (1), Kugaaruk (2), Arctic Bay (3), Kimmirut

(4), and Arviat (5) communities where participants were interviewed for this study. Only

one participant from Kugaaruk was interviewed; this interview took place in Gjoa Haven.

Communities span Kitikmeot, Qikiqtaaluk, and Kivalliq regions in Nunavut, Canada.

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Table 7. Interview guideline.

Topic Questions

Directed introductory questions What is your name?

How old are you?

Where were you born?

How long have you lived in this

community?

Hunting experience

Have you ever hunted a polar bear before?

How many?

Why do you hunt?

How did you learn how to hunt?

How many bears have you hunted by

yourself? With other hunters?

Do you still hunt?

Where do you go to hunt bears?

Hunting preferences

When you hunt bears, are you picky/

choosey? Why?

Do you prefer to hunt males or females?

Why?

Do you prefer to hunt old or young bears?

Why?

Do you prefer big or small bears? Why?

Identifying bears Can you tell differences between bears?

How?

Can you tell if a bear is a male or female?

How?

Can you tell ages of bears? How?

Can you tell sizes of bears? How

Can you determine sex/ age/ size of a bear

from footprints? How?

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Can you tell if a bear is healthy? How?

Are bears close/ nearby your community?

Have you noticed any changes in polar

bears? What are the changes?

Experience with polar bear research

How are polar bears monitored?

Do you know why polar bears are

monitored?

What do you know about scientific

methods?

Have you ever participated on a polar bear

survey?

Have you ever collected scientific samples?

Do you know what the samples are used

for?

What do you think we need to know in

monitoring polar bear populations?

In monitoring bears, do you think polar

bear sex/ age/ size is important? Why?

What is the best way to survey polar bears?

4.4 Results

From May 2011 to April 2014 over five visits (and a follow-up visit in February 2015), I

interviewed 23 hunters and 33 elders (48 men and 8 women) individually (Table 8).

Interviews ranged from six to 63 minutes in duration and took place on the land (for GH

hunters and KU) or at participant homes, hotels, and HTO offices. Interpreters translated

34 interviews. Participants ranged from 27 to 82 years old and comprised 33 active, 14

non-active, and 9 less-experienced hunters, including at least 21 participants who had

previously guided sport hunts. Five participants from Gjoa Haven had previously

participated in noninvasive polar bear surveys and sampling (Wong et al. 2011, Van

Coeverden de Groot et al. 2013). Arctic Bay participants included an individual who was

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experienced in identifying bear characteristics through her experience in hide preparation

and sales across Nunavut (AB14). One Arctic Bay participant was a previous wildlife

officer who was experienced with polar bear surveys and sampling (AB15). Arviat

participants included two local bear patrols (AR1, who had also previously participated

on polar bear surveys, and AR2), regional wildlife (AR3) and HTO (AR20) board

members, and previous wildlife (AR15) and assistant wildlife (AR8) officers. Due to

frequent daily encounters with bears in the fall, most Arviat residents were able to

identify or at least comment on how to identify polar bear characteristics.

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Table 8. Number of interview participants from Gjoa Haven, Arctic Bay, Kimmirut, and

Arviat corresponding to participant type, hunting experience, and having mentioned

experience guiding sport hunts during interviews. Participants were categorized as elders

and hunters according to hunting experience: active hunters, non-active hunters, and less-

experienced hunters. A total of 48 men and 8 women were interviewed.

Community

Gjoa Haven* Arctic Bay Kimmirut Arviat

Participant type

Hunters 3 5 5 10

Elders 7 10 6 9

Hunting experience

Active 5 9 8 10

Non-active 5 4 1 4

Less-

experienced

0 2 2 5

Previously

guided sport

hunts

5

5

3

8

* Includes a single participant from Kugaaruk.

4.4.1 Hunter preference for bear characteristics

Across all communities, active hunters and elders were more selective than less

experienced hunters for bear characteristics. Whether a hunter was selective or not during

a hunt partially depended on logistical constraints, such as the number of bears (or tracks)

that are encountered during pursuit and time available for harvest (48hr in most

communities), while considering the amount of fuel and supplies taken to the field.

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We go by machines now…if he has enough gas…he’ll see a track. If it’s small,

he’ll look for a bigger one…but if he doesn’t have enough gas, thinking that he

won’t come back…he’ll get the first tracks. (Interpreter translating for AB12)

If I don’t get my bear in 48 hours, and I lose my tag and—and I’m out of the

hunt…the guy behind me will get a chance… sometimes you don’t really

concentrate, trying to see all the—whether it’s a male, female, how old, and you

[are] really concentrating on getting that bear and after you get your bear you

finally see what kind of bear you shot and sometimes you can tell. (AR1)

When asked if participants prefer to hunt males or females, participants indicated choice

of sex is driven by management practices protecting females and cubs, favouring large

males (Appendix 24). Many participants believed this practice sustains populations

and/or encourages population growth.

There’s a by-law for hunters and trappers so they have to go for the males. But if

there’s like no male they go out for the female…they’re [thinking] for the polar

bears…they don’t want the polar bears to [diminish]. (Interpreter for G5)

We [would] prefer more males ‘cause…there’s that law…you can’t take females so

much ‘cause they give birth and produce more polar bears…so that’s how it is.

(AB2)

When they’re hunting…they usually say don’t kill [females] with their cubs or only

when they’re male… ‘cause if they caught the female, there will ran out of bears.

(AR10)

Some participants preferred to hunt females and cubs before these practices were

implemented, while others would hunt any type of bear that they encountered.

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Before there was a by-law they could catch females—even [if] they got cubs, and

when after there was a by-law now they have to catch only males. The big ones.

(Interpreter translating for G3)

When they see a bear they don’t just shoot it…figuring that there’ll be a bigger one

coming up and there are other bears too that have cubs…They don’t go for bears

with cubs ‘cause it’s the law…or the policies—guidelines that they have—have to

follow. But back then when they were kids their parents used to go for any bear.

(Interpreter translating for K1)

Hunting preference also depended on whether bears were hunted for food, clothing,

and/or the sale of hides. Today, most participants prefer large, old males with thick, white

(clean) fur due to the high market value of their hides. Current 2:1 male-biased harvests

(following Memoranda of Understanding) have also reinforced these preferences.

When I used to go with my stepfather, he preferred the—for money-wise…the big

male…but for meat, for meat consumption…more fat, and softer meat, female…for

consumption, it’s important…and for money, they used to sell [hides] to the

Hudson Bay back then…the bigger the [male]…we used to get more money with

the bigger hide… nowadays money is more important, which seems than—the meat

is important too but we don’t starve like when we used to. Long time ago. (G8)

When they see a bear, knowing that there might be a bigger one around…they don’t

shoot the one right away and, plus the bigger the skins are they tend to cost

more…they don’t go for females since they have a cub…and their cubs are too

small so they don’t go for those…he tends to go for good fur…some bears have—

seems to have no fur on some areas—neck area…mainly male bears. Maybe from

fighting or something. (Interpreter translating for K2)

If by chance, if he had a choice, he’d go for the bigger one, because they’re more

expensive…and also how clean they are. Like if [the] bum part is really dirty then

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it’s harder to sell them because they—people want to buy clean, white [fur]…But

there’s also a [point] where if there’s not many choices in the bear, if there’s few

bears…they wouldn’t try to go for the skinniest one—the unhealthy one. And also

his third option would be is, if…they had to kill in defense. Then it wouldn’t matter

if it was female or not. (Interpreter translating for AR4)

In contrast, some participants still preferred small, young females for consumption.

I prefer younger…they’re a lot [more] tender…with female they tend to get tender

very faster…’cause I’m always cooking…[old] males, they’re a little harder ‘cause

probably they’re constantly walking and hunting…but females they’re mostly

feeding or just survive or something like that. (AB14)

Some participants preferred middle-sized bears.

He would try and get one that’s not too much of a cub…not too old—if he had a

choice, he wouldn’t go for the older bear ‘cause it’s leading the other bears…he

would try and get the one in the middle. (Interpreter translating for AR6)

Health was also important to participants who hunted polar bears for their hides and/or

consumption.

If it’s easy to clean that means it’s a healthy animal…whereas unhealthy one it’s

hard to scrape off the fat as much. (Interpreter translating for AR6)

Hunters across the north preferred different characteristics of polar bears that they

hunted, depending on their use. With the short time available for hunting due to tag

requirements and small harvest quotas, Gjoa Haven, Arctic Bay, and Arviat participants

were no longer selective for a broad range in bear characteristics. In contrast, Kimmirut

participants remained selective when hunting and some hunters were able to hunt more

than one bear per season. Unlike most communities, Kimmirut hunters rarely pursued

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bears and usually hunted them when they were encountered while harvesting other

animals; tags were distributed following each hunt and lottery distributions only occurred

when two to three tags remained to avoid overharvest.

4.4.2 Methods of identifying polar bear characteristics

Because of individual experience, preferences for bear characteristics, and harvest

regulations, it was important for Inuit hunters to identify and distinguish polar bear

characteristics when hunting. Participants identified bear sex, age, body size, and health

by observing the bear directly (e.g., body shape/size, fur, behavior) and/or its tracks (in

situ footprints). In Arviat, being able to identify polar bear characteristics was also

important to avoid potentially aggressive (dangerous) bears. Bears often frequented the

community in groups. Some community members compared individuals within groups to

distinguish characteristics.

[If] there were two bears, male and female, and you can tell the difference, like size

at the same time and you can look at the neck…longer necks and shorter necks.

(AR1)

4.4.2.1 Distinguishing males and females

Some participants indicated sex could be identified from tracks alone (Appendix 24).

Larger tracks were usually associated with males (versus females). Most participants

reported male footprints are generally angular and wide, whereas female footprints are

round and narrow.

The female footprints are mostly, almost round…females is shorter, male is longer

…when they’re males even they’re older or younger they’re long and big.


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When you find the track, female…they’re more round…male tracks look [almost]

like triangle…more square, more triangle. (Interpreter translating for AB3)

An older male bear, their footprints are wider…whereas a female bear, the paw

print would be more roundish. (Interpreter translating for AR4)

Some participants used gait or footprint orientation to distinguish males from females.

Males tend to walk with a longer stride and their footprints turned inward. Some

participants also observed patterns along tracks for long fur of males.

If the snow is soft at the time the polar bear walked through there, [they] would

have fur drag marks, a big male…because the big males seem to have longer fur, on

the outside of the feet and the bottom of the feet…if there’s any nails broken that’s

a big male broken in fight...Or in [making a seal hole]. (G8)

Some participants indicated female movements are more direct than males.

When they see the prints, if they’re kind of straight footprints…they know it’s a

female…male, when you’re tracking their tracks, they don’t go straight they kinda

maneuver around. (Interpreter translating for K4)

Participants in other regions indicated the opposite.

Where he was taught, the mother bear usually is being followed by the cubs…so it

wanders back and forth, looking for seal…they know it’s a female leading, because

it’s, you know, turning. Whereas a male bear would walk straight, going by the

footprints. If the footprints are going straight…that means it’s like a male bear,

traveling by itself. (Interpreter translating for AR4)

Participants also mentioned sex was more difficult to determine in younger (smaller) bear

tracks than adults.

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The female bears’ prints are shorter than the male bears…he can tell that kind of

difference but if it’s a cub, not full-grown, he doesn’t quite know if it’s a male or

female too. (Interpreter translating for K2)

If it’s a smaller bear I can’t really tell [if] it’s a female or male…if they’re really

big, I know that that’s [a] footprint of a big male. (K9)

When observing bears directly, some participants indicated it is difficult to identify

sex from a far distance.

From a distance sometimes it’s hard when it’s not in the right angle…if it’s

completely sideways and you [can’t] see the neck. (AR1)

In the far distance when you see bears travelling they all look the same, but as they

get closer it’s easier to determine whether it’s female or not. By the fur, the back of

the neck…and the long neck. (AR4)

Participants also mentioned it is difficult to identify sex in older (larger) bears.

If it’s a male…same size as a female, if it’s fat you can’t really tell if it’s a male or

a female…but if it’s skinny, same size as female but you know it’s a male. (AB12)

If it’s an older bear, he wouldn’t know how to determine because the fur is

yellowing as it’s aging…so, the older the bear, then it would be more kind of hard

to determine whether it’s female or not. (Interpreter translating for AR4)

Participants across all communities associated larger body sizes with males. Participants

also used head and body shape to determine sex. Females tend to be more round, with

shorter “snouts”, and smaller heads compared to males.

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[Females] looks like they’re shorter and chubbier…and the males, they’re a bit

bigger and more slender kind of…the female, they might have what looks like two

forehead on top…and shorter face…and the male, they have the longer face...can

also observe the hind legs…[females] their tail looks like lower, and the males will

have a higher—their position—tail a bit higher. (AR5)

Arctic Bay participants generally indicated longer or narrower necks in females versus

males.

With the female, they’re more round…and they have a little longer neck…with the

males they got [a] thicker neck and they’re larger…they have a bigger head…with

the shape of their bum area. (AB14)

Arviat participants indicated the opposite.

You can tell by lookin’ at their ears…the distance. A females’ are gonna be more

closer…and shorter necks. And the male bears, their ears are gonna be more far

apart. And they got longer neck…you can tell by their legs, where they got all that

long hair. (AR1)

Seems like [females] got more short neck…from head to the body, seems like

they’re shorter. But a male, it seems like they’re always have their neck stretched

out. (Interpreter translating for AR14)

Participants described females as having whiter, “cleaner” fur, with dark coloration

around the crotch area, compared to males.

If it’s going—running away from him, and the bum area, if it’s not dirty, he knows

it’s a male…the female ones, when they’re heading away from him, the crotch area

is yellow. (Interpreter translating for K6)

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He can tell by the bum part whether it’s a female because they’re more—they tend

to be more yellowish. (Interpreter translating for AR4)

Participants also used behavior to determine sex.

By the movement you could tell they’re female…‘cause they’re like, cleaner. Very

gentler…whereas the male is [a] very aggressive kind and kind of walks

aggressively too. (AB15)

And a male…they never around with another polar bear…they don’t stick around

with a polar bear, and they got their movement—it’s more hyper…they always

aggressive like anxious and look around, look all over, but the female ones, they’re

a lot easier to tell. (AR14)

4.4.2.2 Identifying age and body size

Participants indicated that it was not important, historically, for Inuit to identify ages of

bears. Instead, body sizes were and continue to be of interest.

By Inuit knowledge they didn’t care about the age…when renewable resources

started asking for samples, then the government started finding out how old the

bear is. (Interpreter translating for AB4)

They know, yearly, like last year [cubling]…and estimating how height…what the

height is…they guess how old the bear might be…they don’t put actual age.


Not by age but by size…only by size they look. (Interpreter translating for AR3)

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Participants from Gjoa Haven, Arctic Bay, and Kimmirut mentioned inferences on body

size can be made by placing their kamiks (traditional boots) together along tracks

(Appendix 25).

When they’re male, put your feet together and you could tell they’re big bears, [in]

the footprint. And when they’re female they’re small, smaller than [that].


He wear caribou kamiks…just by the footprints, you put your feet near it…they’re

really fluffy, the kamiks…if it’s smaller than that they’re small. (Interpreter

translating for AB1)

By Inuit ways, they put their feet together to determine how big the bear might

have been…to his knowledge as he’s growing up that’s the only way the hunters

determined how big the bear might be…using their feet together. (Interpreter

translating for K1)

While few participants used tracks alone to determine age, participants associated larger

tracks with larger body sizes and older bears. Some participants mentioned bears reach

large body sizes quickly.

They grow really fast…they age really fast…like dogs have 7 years, for us, a year.

(Interpreter translating for AB4)

The height, if it’s last year’s [cubling] it’s that big …not many years, the bear cub

tends to grow as big as the mother…so, looking at the cub and the mother they

estimate the age of the bear. (Interpreter translating for K2)

Most participants used age categories versus chronological age (in years) to distinguish

bears.

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In Inuktitut there’s—we have names for yearling…second year, third year, and

those that are the same size as the mother…and then there’s a next to adult male,

young male, and big adult male…there’s names on every stage. (AB15)

The younger ones, you can[’t] really say exactly how old…you can see a

yearling…a cub that’s like full grown…you can guess like there’s like 2 or 3, 4

year old…a full year, like 2 years, 3 years, and when they reach their—where they

stop growing. And so I think they go from 3 to 4 when they [finally] stops growing.

(AR1)

Several participants mentioned that large, old bears—Tulajuittaq—that stay in open

water and never come inland.

There’s stories of polar bears that never go on land. There’s a term in Inuktitut,

they’re called Tulajuittuq, which means ‘they never go on land’…they always stay

in the moving ice...tula is to go, like a boat to go ashore…juit is never, and ‘doing

it’…so tula—land—not—do…they’re the biggest bear you’ll ever see.” (AB15)

There’s biggest and biggest bears and that doesn’t come to the town or, it doesn’t

go inland…he said that there are only few, few, less and less humongous

bears…[sport hunters] usually want to get the biggest bear that he was talking about

these bear that usually [not] hunting inland. (Interpreter translating for AR12)

Two participants indicated bears appear to be smaller, with less body fat, as they reach

older ages.

The big males…are older when they really can’t run anymore…they’re just

walking, even if their fur is nice…when they’re older, their feet…they’re bad…and

they’re a little skinnier than the younger ones. (Interpreter translating for AB10)

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When they get too old, I guess they’re not so good at hunting seals…so they get

really skinny. And they appear smaller…they have a better time hunting and are

successful hunting when they’re younger. And stronger I guess. (K9)

Arctic Bay and Arviat participants also used fur color to make inferences on ages of

bears; younger bears are associated with white (versus yellow) fur.

When they’re older, they’re more yellower…when they’re younger, their fur is

more beautiful and more white. (Interpreter translating for AB5)

He would use wolf for example. He knows with the wolf that the fur starts to get

more yellowish…so the same would probably go for bears, a healthy, younger bear

would have more white…the hide, would be more whiteish. Whereas an older

bear—older bear would start yellowing more. (Interpreter translating for AR4)

There’s an [Inuktitut word] meaning between a cub and a full-grown. There’s a

middle, category that we say…you can tell by the color of the fur whether they’re

reaching full adult or whether they’re still in their middle…stage. You can tell by

the color of the fur like how white it is, how, the fiber [of] the fur itself. (Interpreter

translating for AR6)

Participants in all communities also examined behavior; younger bears tend to run away

faster when being pursued.

The old one…they cannot run. They only walk…they’re very easy to catch…they

not gonna run from you, they’re just gonna walk very slow. (AB6)

Participants also indicated younger bears are more active and aggressive toward humans.

The big adult male, they’re kind of—they got confidence, when they’re

walking…slowly. They know that then they kind of just…move around. Slowly.

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Young one—young ones are very curious. They move around and…they look

around, they go into camps…they’re the one[s] that follow the people

more…‘cause they’re young, they don’t know, they don’t have experience.

Whereas the big males, they know not to bother the camps, so they don’t. They

kinda cool. (AB15)

Younger bears, you know, still might have a chance to breed or whatever [and] still

has to grow, and, kind of like adolescents, like they’re more mischievous or more

active. But older adults, they’re more relaxed, they don’t—they’re not as active.

(AR8)

Old polar bears, they’re not aggressive…‘cause they understand…they know when

we have weapon as they approach they can tell if we have a rifle or not…the

younger ones, they don’t seem, to have, knowledge if we have weapon or

not…they just approach…so we feel more comfortable with the older ones. (AR16)

At least one participant from each of Arctic Bay, Kimmirut, and Arviat communities

examined teeth from harvested bears to estimate age.

He thought that’s why the bear was old, some teeth were broken and chipped off.


4.4.2.3 Identifying health of individual bears

When asked about health of individual bears, all participants indicated body fat and/or

size is a direct indicator of health.

If it’s skinny, it might not be getting enough to eat, or it—it might be sick…but I’ve

never really seen a sick bear. Like I just seen a skinny bear or, who’s had hard luck

of like, catching prey…all I know is like, they appear very unhealthy when they’re

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skinny…I guess when they’re not eating then—when they’re too hungry like they

appear, unhealthy. (K9)

When they’re unhealthy they’re skinny and tiny and when they’re healthy they’re

big…they’re chubby and big fat on their tummy…when they’re getting old, and

they’re—when they’re not eating enough—not enough they’re start to, skinnier.

Skinnier and skinnier. (Interpreter translating for AR13)

Three Arctic Bay participants inferred body fat by observing footprint shape (Appendix

26).

Polar bear, when they’re fat…their tracks are round…but the skinny ones’ just like

my foot. (AB6)

One participant observed gait from tracks.

When they’re skinny their tracks are closer to each other…and they tend to take

longer steps, like further steps…the nice and healthy ones, their—their tracks are

more apart…and their steps are closer. (Interpreter translating for K6)

Relevant to this, when observing bears directly, Arctic Bay, Kimmirut, and Arviat

participants indicated unhealthy bears move slower or in a more staggered and

unpredictable manner compared to healthy bears.

There was one time, he saw one bear that seemed sick so they didn’t go catch

it…the way, it was walking…hardly move, hardly walking…and when it stops it

stays there for a while…won’t move, he said. (Interpreter translating for AB3)

One time he saw a polar bear that seems like was drunk ‘cause it’s so hungry…it

was staggering…and he didn’t want to catch that one. (Interpreter translating for

K7)

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A healthy bear would walk in a more, straight fashion or, orderly fashion than an

unhealthy bear, kind of like a drunk person, not walking straight, walking around.

(AR8)

Some participants inferred health from fur color. White (versus yellow) fur was

associated with healthier bears.

You can tell by looking at it because with the healthy bear, the fur is shinier and

more, you know, clean looking…whereas unhealthy bear, it’s dirty…the fur’s not

shiny as much...[like humans] before we reach the adult we have good skin…so we

can tell by looking at our skin. (Interpreter translating for AR6)

Most participants indicated hunting ability or ability to acquire food affected health.

Well they’re just like humans…some of them are better…hunters than [the]

other[s]…some of them don’t know how to hunt…but they can kill somebody or,

kill each other…if they don’t know how to hunt seals. (AB6)

They’re like humans. Some humans tend to catch more animals and some hardly

catch anything and he believes bears are like that too. In order to be healthy some

bears who catch regularly, but some bears may not be catching regularly like the

healthy ones. (Interpreter translating for K2)

I saw one, big male, and you could just tell the ribs…the head’s even seems like it

was a huge head…the body was like—like just really skinny and you can see the

bones…I bet that bear didn’t even make it through the early fall. ‘Cause it wasn’t

even scared…I think he was not a very lucky bear to get a free meal from another

kill somewhere along the shore…sometime they’re just gonna get starve and, and

never regain their energy… they’re gonna miss, miss, miss, miss and—and they’re

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gonna be forced out from other bears and, so I think that’s they just start[ed] going

downhill. (AR1)

In the polar bear, like in a family…sometimes there is one bear…it’s always

hungry…they don’t share with it …they help each other, they feed each other, but

there’s always one bear that is always…thrown outside of the circle…so that one

ends up hungry all the time. He has to fend for himself, not with the group.

(Interpreter translating for AR3)

Some participants indicated health corresponds to changes in local prey populations.

When he was a teenager there were a lot of seals around. Young seals, the ones that

were born same year but they were together and there were lots of them...[then] the

bears started…being more populated around—around Kimmirut…nowadays

there’s hardly any seals…when he was a teenager he—they were catching

abundance of seal. So back then they were quite healthy. Seems like majority of the

bears that he saw were fat, and healthy…but nowadays there’s hardly any seals, he

knows too that they don’t only eat seals but like, vegetation around the land they

eat those but nowadays, with hardly any seals, some tend to be—look unhealthy.


It’s hard for the bear to catch seals a lot, that’s when it starts losing it’s weight…it

helps them to get ready for the full winter…the seal meat helps them prepare, that

hey can help hibernate longer. So they try and eat as much seal…if there’s hardly

any seals around, like this [spring] time of the year, then the bear’s gonna be

hungry for longer [‘cause] they eat mainly off seal. (Interpreter translating for AR3)

Participants indicated bears that are more aggressive toward humans are less successful in

hunting, and are, thus, less healthy.

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When you will see a healthy bear, and when you see a track when you hunting

them, they go…scared away…they kind of run, right away…but a sick bear,

doesn’t care…you know, they lost that will…[to] get away…so they kind of just,

slowly, kind of walk away but not—not in a hurry…as if they’re trying to show us,

‘look I’m sick already…so don’t bother me’ ...kind of thing. But a healthy bear will

go, scattering away…very fast. Their fur is white too. The sick bear is yellow fur.

(AB15)

The less they eat, they’re gonna be more skinnier and more desperate…and not

afraid of humans when they’re hungry. (AR5)

Participants also described male-to-male and inter-sexual combat affecting body

condition.

Not really sickness that affects the polar bear from being skinny, it’s when they

fight males, they break muscles…or bones. That really stops them from hunting

‘cause they’re in pain…especially during mating season. (Interpreter translating for

AB4)

When they’re pretty old, you can tell, and by mating…season. They fight

sometimes to the death…or hurt themselves really bad…you can tell that it’s

hurting…their bones get broken. Their muscles are torn and all that…so it becomes

unhealthy…during that time. (Interpreter translating for AB12)

The female can fight the bigger ones…they’re really strong…those females they

really love their cubs…and when that big male started to get close to the cub. Then

that female start to—started to run after that big one, it’s trying to fight it—maybe

sometimes, they kill that female…I’ve seen that, couple of times...down at northern

Manitoba. (AR11)

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Participants provided insight into potential causes of recent changes and observations

related to polar bear (population) health. Many of these observations were made through

frequent opportunities to observe and interact with polar bears; these immediate

observations might not be made available through scientific methods alone.

4.5 Discussion

Participant methods and the ability to discern polar bear characteristics continue to play

an important role in hunting. Traditional skills in identifying characteristics associate

with personal preferences and experiences, which vary among communities and

community members. Hunters generally prefer larger males for trophy hunts and hides,

and females and cubs for food. Identifying sex is also important because of differences in

hunting challenges and hide preparation, as well as meat quality between males and

females. Although identifying age was not important to Inuit in the past, hunters today

associate fur quality and body size with age classes. Discussions over health always

involved implications for human use; many community members associate polar bear

health with food consumption, ease of skinning and hide preparation, and coloration and

quality of fur. Arviat participants—who experience frequent interactions with bears—

always identify polar bear characteristics that are associated with aggression, which have

direct implications for human safety. Personal experiences also shape the acquisition of

hunting skills, as is evident through participants frequently discussing hunting methods in

the context of their own concerns and priorities. This focuses on preference for personal

versus trophy hunting, or tendency to actively pursue versus avoid bears. These

observations have implications for the understanding and inclusion of IQ in polar bear

monitoring and management.

4.5.1 The role of Inuit methods of identifying polar bear

characteristics in monitoring programs

Community-based monitoring programs are attractive because they can supplement

scientific population data and, through participation, allow Inuit to inform management

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decisions that affect them. Inuit methods of distinguishing individual polar bears could be

particularly applicable in surveys for population abundance, sex and age structure, and

health condition, especially in years between comprehensive scientific surveys when

these data are not available. These methods could also complement scientific surveys

through Inuit participation, for example, in identifying individual bears to avoiding re-

sampling the same individuals. Inuit could also provide rapid preliminary sex, age, and

health information on individual bears without requiring physical capture, sampling or

untimely laboratory processing to collect these data. These data could be evaluated for

consistency for inferences on accuracy (Wong et al. 2011) prior to inclusion in

quantitative surveys.

While participants across communities generally agree in methods of identifying

sex, some inconsistencies exist, namely, whether males or females associate with longer

necks or snouts, or rounder footprints. These inconsistencies are also unique observations

that not all participants discussed. The lack of agreement could be due to new

observations that remain to be validated by other community members through extensive

practice (Alessa et al. 2015), or, similarly, inaccurate observations of inexperienced

individuals. It is also possible that differences in polar bear morphology and behaviour

occur across different regions (e.g., footprint shape) though this is more difficult to

confirm empirically. Such will require extensive scientific sampling and/or regional

comparisons of local reports of these unique observations. Inconsistencies or lack of

agreement among participant reports should be taken into consideration if these

observations are incorporated into any monitoring program. Group discussions where

participants and elders across communities are able to share their observations might

overcome or clarify any discrepancies.

The inclusion of Inuit hunters in any polar bear monitoring program should

consider the limitations of participant hunting experience and methods of identifying

characteristics. Some participants reported difficulty in identifying sex from far distances

and in some age classes of bears (old or young bears, depending on the hunter). Inuit

diagnoses of age categories (as a recently acquired technique) and body size might be

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more reliable or consistent than chronological estimates of age in polar bear surveys, as

participants indicated that historically chronological age was not important to them. For

Inuit, it may also be more meaningful to refer to categories of observations within their

traditional contexts rather than ecologically meaningful characteristics that scientists and

managers use, such as desirability of hide or tenderness and tastiness of meat versus sex

and/or age categories. The few instances where participants report examining teeth from

harvested bears also suggest community members may be learning from or are aware of

scientific methods (of aging polar bears using teeth; Christensen-Dalsgaard et al. 2010).

Hence, scientific methods may also shape IQ and TEK. Inuit participation in research

could provide unique opportunities for Inuit to become aware of—and perhaps build

on—what knowledge is relevant in scientific and decision-making. Research participation

could also allow both Inuit and scientists to see how observations that are important to

Inuit correspond to scientific and management relevant categories and vice versa. Clearly

defined terminology for categories according to the contexts of their application will be

necessary.

4.5.2 Comparisons between Inuit methods of identifying

characteristics and science

Identifying overlaps between TEK and science will not only facilitate dialogue between

Inuit and scientific researchers but also support the role played by Inuit in science-driven

research and management. Though Inuit focus on identifying characteristics that are most

relevant to them, community members from different communities and regions share

identification techniques that overlap with scientific methods. For example, participants

distinguish males from females by identifying larger head and body sizes, and presence

of foreleg guard hairs (Derocher et al. 2005). Hunters use age categories versus

chronological age to age bears just as used in mark-recapture surveys and population

viability analysis to estimate population structure (e.g., Taylor et al. 2006). Several

participants indicated younger males are more active, and activity is related to health

condition. Higher body condition associates with prime-aged (five to 20 year old) bears

due to their ability to survive nutritional stresses, such as their ability to hunt and take

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seals from subordinate bears (Regehr et al. 2007). Some participants reported higher

growth rates in younger bears, as empirical observations have reported (Derocher et al.

2005). Participants also indicated that, in their search for food, younger bears are more

likely than older bears to enter communities. This corresponds with the larger proportion

of young bears killed in defense of life and property across Nunavut (Dyck 2006). Bears

are also more likely to enter communities when food availability is low (Rogers 2011),

especially younger males due to naiveté or lack of risk-aversive behaviour. Participants

also linked health to fat and body size, and fatness indicates body condition in monitoring

programs (Stirling et al. 2010). Taken together, these observations suggest hunter-

knowledge can complement science in any polar bear monitoring and/or research

program.

Spending time with Inuit in search for polar bears (Wong et al. 2011) allows for

knowledge-gathering and ground-truthing, cultivating a deeper understanding of Inuit

interactions with polar bears, and experiencing how IQ is gathered and applied—

specifically, how IQ operates as a guiding principle for Inuit interactions with animals.

Unfortunately, most community members lack scientific experience and many

community members do not trust in science (Moller et al. 2004). Basic science is often

viewed as being inseparable from management because science largely informs

management decisions (Bocking 2007). Constraints on timing, funding, and logistics

limit most researchers from spending enough time in the north to interact closely with

what is being researched, on a level comparable to that of surrounding communities.

Such might explain the local criticisms against monitoring programs that are inadequate

in capturing local ecological phenomena (Moller et al. 2004). In areas where scientific

survey data are lacking and/or out-dated, there is also ongoing pressure for decision-

makers to adjust harvest quotas according to immediate (local) observations. Quotas

based on inaccurate scientific data can potentially lead to overharvesting, which can

result in detrimental and potentially irreversible population effects (e.g., Taylor et al.

2006). Instances where quotas are too small after incorporating defense-kills may also

lead to more frequent human-bear interactions (Stirling and Parkinson 2006, Peacock et

al. 2011, Vongraven and Peacock, 2011). Persistent long-term engagement of Inuit in

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scientific monitoring can facilitate a comprehensive understanding, at the community

level, of how science and IQ can synergistically inform management decisions; such

might assuage local misconceptions of both research practices (Pearce et al. 2009) and

IQ. Documenting IQ on population characteristics, beyond broad statements of “more” or

“less” bears, not only allows for a better understanding of the formation of IQ and polar

bear ecology but also provides Inuit with a chance to share their own ecological methods

and observations independently from science.

4.5.3 The role and persistence of Inuit knowledge in polar bear

management

Participant discussions indicate that harvest regulations continue to impact motivations

for gathering and transmitting knowledge of polar bear characteristics. The ability to

distinguish males from females is especially relevant to male-biased harvest regulations,

while body sizes remain important in protecting younger bears. Economic incentives and

demands for hides and sport hunts continue to drive the hunting of large males, which has

also been reported in other communities (Dowsley 2009b).

When he was young hunters were catching any bear they saw…back then when he

was growing up…he noticed the hunters were hunting any bear, even the cub, or

the mother…back then they used to not know whether if it’s a female or

male…they caught it whether it was female or male back then, but nowadays they

can tell the difference between the females and the males...nowadays they tend to

try and get the bigger bears. (K4)

Canada—home to two-thirds of the world’s bears (Peacock et al. 2011) and 70% of the

world’s legal harvest (Tyrrell and Clark 2014)—is the only country that allows

international trade of polar bears through aboriginal subsistence hunting. One might

expect the economic benefits of selling a tag to sport hunters outweighs the benefits from

personal hunting (Dowsley 2009b, Dowsley 2010). However, Arviat community

members indicate there is little incentive for sport hunting after expensive supplies (e.g.,

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oil and gas) and time-intensive labor (e.g., hide preparation and outfitting) are taken into

account. Arctic Bay community members also report frequent disputes during public

community meetings over the numbers of tags allocated to sport hunters. In Clyde River,

Nunavut, no more than 20% of hunting tags are devoted to sport hunts (Dowsley 2009b).

These reports together suggest a strong cultural value still persists in polar bear hunting

for personal (traditional) purposes.

With smaller quotas and hunting opportunities, younger hunters acquire less

experience and are unable to distinguish polar bear characteristics at the same level of

detail as elders and older hunters. Elders express concern about younger hunters’ lack of

in-depth knowledge of the ecological and ethical relevance of their hunting practices.

Elders and more experienced hunters frequently stress that IQ is experiential; knowledge

is gathered through active participation and engagement with animals on the land.

Hunting opportunities have been lost in some areas (e.g., communities overharvesting in

M’Clintock Channel which led to a moratorium [Taylor et al. 2006] and recent

reinstatement of a small quota), leading to abandonment of traditional practices. This

could result in overreliance on technology over IQ and youth with poor hunting practices

and ethics (e.g., Gomez-Baggethun and Reyes-Garcia 2013). Contemporary changes in

local wildlife authority and social structure of harvest management also affect the degree

IQ is integrated into increasingly Westernized and modernized northern communities

(Padilla and Kofinas 2014). Historically, IQ was used as an educational tool to promote

sustainable harvests, including ethics regarding relationships with animals and how

people should behave in society and their environmental surroundings (Natcher et al.

2005, Houde 2007, Berkes, 2012). This differs from following the prohibiting wildlife

management regulations today (Moller et al. 2004), such as harvesting only as much as

you need to avoid overharvest versus according to a quota. Community-based population

surveys and bear-safety programs hold promise to provide unique and frequent

opportunities for community members to interact with bears in non-harvest contexts. The

inclusion of youth as observers and/or assistants in research also encourages inter-

generational knowledge transfer while supporting researchers in outreach activities.

Because management decisions actively shape the formation of Inuit knowledge and

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persistence, policy-relevant projects that are guided by community interests and/or

concerns will enhance the preservation of knowledge.

4.5.4 Barriers to Inuit inclusion in polar bear research

Community members use the same observations and cues (e.g., fur coloration, body

shape, tracks) to make inferences on multiple characteristics of polar bears. The

integration of these data in a scientific framework through a systematic, objective manner

is challenging. Notably, IQ links intimately with the context through which it is formed

and, thus, is subject to misinterpretation when isolated (Houde 2007, Berkes 2012). As

opposed to conventional scientific practices where phenomena are treated as controlled,

isolated subjects of study, Inuit view animals as constantly interacting with humans and

their environmental surroundings and incorporate their observations as part of a holistic

experience (Huntington 2004, Berkes et al. 2007). This is evident through instances

where participants describe polar bear characteristics through comparisons with human

behavior. Community members –and scientific researchers alike—are also more likely to

note unusual patterns in local animal distributions, behaviour, disease or breeding failures

(Moller et al. 2004) based on their individually unique experiences (Huntington 2004).

Knowledge-holders are also selective in the type of information they share and interpret

as their own form of management (Parlee et al. 2014) according to their own political

interests, cultural values and status within their communities (Berkes et al. 2000, Padilla

and Kofinas 2014). When key knowledge-holders and/or local decision-makers (e.g.,

wildlife board representatives) do not view themselves as representing community voices

it is a challenge to establish representative community perspectives (Parlee et al. 2014).

These complexities make locally endorsed or cohesive policies that take into account the

broad range in community and participant views over large regions particularly difficult

to devise (Parlee et al. 2014).

Understanding how management goals affect Inuit and the animals that they

interact with will allow conservation decision-makers to consider the socio-ecological

impacts and receptivity of management decisions before implementing them. For local

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communities, understanding common conservation goals that underlie scientific research

and monitoring could perhaps reveal cultural incentives for hunters to apply existing

traditional skills in a contemporary conservation context. Inuit inclusion is critical for

conservation management across the north, as the fate of the polar bear will span social,

economic, and cultural aspects of Inuit communities.

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4.6 Appendix

4.6.1 Participant responses to interview questions

Appendix 24. Number of participant responses by community corresponding to

observations used to identify sex of polar bears. General comments indicate where

participants mentioned the observation but did discuss how that observation was used.

Observation

Community


Footprint

General comments 1 2 3 3

Round in females, narrow in

males

4 1 0 3

Narrow in females, round in

males

0 0 2 1

Larger in males than females 7 7 6 7

Gait


Smaller stride in females

versus males

0 0 0 2

Male tracks more turned in

than females

0 2 1 3

Inferences made on behavior 0 1 1 0

Head


Shorter snout in females 0 1 1 1

Longer snout in females 0 0 1 1

Larger in males 0 2 1 2

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Body

Shorter in females 2 3 0 4

Longer in females 0 2 0 1

Longer in males 0 0 0 6

Larger in males 3 11 6 12

Comments on length 1 0 0 0

Comments on rump 0 2 3 2

Comments on back 0 1 0 0

Comments on legs 0 0 0 2

Comments on neck 0 0 0 3 * Includes the single Kugaaruk hunter that was interviewed outside of Gjoa Haven (KU).

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observations used to identify age and body size of polar bears; most participants

associated age with body size. General comments indicate where participants mentioned

the observation but did not discuss how that observation was used.

Observation

Community


Footprint

General comments on shape 1 3 0 2

Longer in older bears 0 1 0 1

Rounder in older bears 1 0 0 0

General comments on size 5 4 3 2

Cannot determine from

shape alone

1 1 1 0

Cannot determine from size

alone

0 1 1 0

Comments on claws 0 2 0 1

Gait


Comments on activity and

behavior

0 8 4 6

Younger bears more active 0 2 3 3

Younger bears more

aggressive toward humans

0 0 0 4

Body

Size 0 2 10 8

Use of kamiks 4 2 2 0

Fur color 0 4 0 4

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Use of age classes 1 1 2 4

Comments on Tulajuittaq

(large bears that never come

inland)

0 4 1 3

* Includes the single Kugaaruk hunter that was interviewed outside of Gjoa Haven (KU).

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observations used to identify health in polar bears. General comments indicate where

participants mentioned the observation but did not discuss how that observation was

used.

Observation

Community


Footprint shape


Behavior


Unhealthy bears more likely

to interact with humans

0 0 1 4

Unhealthy bears seem

“drunk”

0 0 1 0

General comments on

movement

0 7 4 3

Unhealthy bears move more

slowly

0 0 0 3

Body

Fatness 2 8 8 15

General comments on fur

color

0 3 2 4

Effects on health

Fighting with other bears 0 3 0 0

Hunting ability 0 4 7 7 * Includes the single Kugaaruk hunter that was interviewed outside of Gjoa Haven (KU).

Questions on health were generally not discussed during interviews with Gjoa Haven

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participants and were added to subsequent interviews with Arctic Bay, Kimmirut, and

Arviat participants.

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Chapter 5

Inuit perspectives of polar bear research: lessons 5

for community-based collaborations

5.1 Summary

Research partnerships with northern communities hold promise for capacity and

resilience against environmental changes. Given their historical relationship with and,

thus, ongoing concern for polar bears, Inuit communities are keen to participate in

monitoring programs. In spite of this, northern communities continue to show some

resistance to polar bear research and collaborations. Here, I summarize and report

interviews with four Nunavut communities on Inuit experiences with polar bears and

research perspectives. Research interactions reveal ongoing cultural, socio-ecological,

and ethical barriers to polar bear research projects. Research licenses and standardized

ethics procedures do not always guarantee collaborations. Adaptable research methods,

mutual understanding, and open dialogue are essential in forming strong research

partnerships with northern communities.

5.2 Background

Community-based collaborations between governmental or non-governmental

researchers, decision-makers and communities can build local community support for

adaptive policies (Berkes et al. 2007, Ford et al. 2010). In Canada, rapid environmental

changes are affecting arctic ecosystems and these compel northern communities to

participate in research (Gearhead and Shirley 2007, Pearce et al. 2009, Ford et al. 2010,

Armitage et al. 2011). Unfortunately, some research projects inadequately involve

community members and/or fail to address community interests and concerns

(Provencher et al. 2013). Ongoing barriers to establishing meaningful collaborations

include a historical lack of trust (Kendrick 2000), “fly in, fly out” research practices

(Gearhead and Shirley 2007) and colonial histories that have not served the interests of

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northern communities (Tester and Irniq 2008). Subjects that have high political interest

are especially challenging for forming and maintaining strong bonds between researchers

and northern communities. Disputes between Inuit and scientific communities over the

responses of polar bears to climatic change exemplify this concern (Dyck et al. 2007,

Dyck et al. 2008, Clark et al. 2008, Dowsley et al. 2008, Stirling et al. 2008, Vongraven

and Peacock 2011). A lack of data on population dynamics for some subpopulations

(Obbard et al. 2010, Peacock et al. 2011), varying degrees of local support for monitoring

methods (Dowsley 2009, Tyrell 2009), and harvest management decisions that seemingly

victimize northern communities (Clark et al. 2013) might further polarize views. It is

important to ameliorate the lack of local support for monitoring programs because

management decisions that incorporate the best available scientific and community-based

information continue to hold promise for the effective conservation of polar bears

(Peacock et al. 2011, Dowsley et al. 2013, Tyrell and Clark 2014). It is critical that all

researchers form strong relationships with Inuit communities to ensure support for

management decisions founded on scientific- and community-based information.

It is necessary to engage communities throughout all levels of research—from

research proposals to disseminating results—to support community ownership of

research outputs (Buytaert et al. 2014), integrate local priorities in decision-making, and

sustain long-term collaborations (Pearce et al. 2009, Grimwood et al. 2012, Brunet et al.

2014a). Accordingly, researchers have encouraged a shift from “participatory” to more

active, “partnership” roles played by northern communities in collaborative research

(Gearhead and Shirley 2007, Brunet et al. 2014a, Tondu et al. 2014). Community

members consult as well as actively shape research throughout all stages of the process.

In Nunavut, community consultations and participation are mandatory (e.g., through

permits; Indian and Northern Affairs Canada [INAC] 1993). For research involving

traditional ecological knowledge (TEK) and Inuit qaujimajatuqangit (IQ)—historical

observations, experiences, and values in relation to environmental processes that are

passed on from one generation to the next (Berkes 2000, Wenzel 2004)—territorial,

institutional, and local levels usually require approved ethics protocols. Northern

community members usually review ethical procedures and require evidence of local

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consultations a priori (INAC 1993, Inuit Tapiriit Kanatami [ITK] and Nunavut Research

Institute [NRI] 2007, CIHR et al. 2010). From a practical standpoint, local experience

and knowledge benefits fieldwork safety and travel in remote and unpredictable

environmental conditions. But, to encourage support for research outcomes, it is essential

to go beyond the minimum institutional (both government and academic) requirements

for community participation in any research program.

Efforts to develop strong partnerships with Inuit communities are underway in

ecotourism development (e.g., Dowsley 2009), climate change mitigation and adaptation

(e.g., Ford et al. 2010, Pearce et al. 2010), and the management of natural resources (e.g.,

Grimwood and Doubleday 2013) including wildlife (e.g., Freeman and Wenzel 2006,

Kowalchuk and Kuhn 2012). The inclusion of Inuit collaborators in scientific monitoring

programs can gain support for wide-ranging management applications, going far beyond

those offered by scientific methods alone (e.g., Garnett et al. 2009, Buytaert et al. 2014,

Huntington et al. 2014, Moller et al. 2004, Phillipson et al. 2014). This can involve the

encouragement of public understanding (Reed and McIlveen 2006), inter-generational

transfer of knowledge (Garnett et al. 2009), and innovative ways to gather new

information (Phillipson et al. 2012). However, how to integrate IQ and science in a

complementary manner that does not compromise the integrity of either source of

knowledge remains an ongoing challenge to resolve. Though IQ includes traditional

TEK—a component of IQ that comprises measurable knowledge of ecological

phenomena (Berkes et al. 2000, Berkes et al. 2007) that is relatively easy to incorporate

into research and co-management systems (Wenzel 2000)—IQ includes guiding

principles for Inuit actions (including thoughts) and how these processes can affect

biophysical phenomena (Wenzel 2004, Dowsley and Wenzel 2008). Documenting IQ is,

thus, more challenging than documenting TEK because it is an experiential system based

on internalized norms, which are not amenable to observation (Wenzel 2004). IQ holders

see themselves as part of the inter-related phenomena under study (Berkes et al. 2007,

Houde 2007). In contrast, scientific methods emphasize cause-and-effect relationships

and objective, quantitative procedures (Moller et al. 2004) that separate researcher and/or

observer perspectives from their conclusions (Huntington et al. 2004). TEK literature

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also continues to separate indigenous and scientific knowledge in a paradoxical way;

scientific and indigenous knowledge have been used to validate one another (Agrawal

1995). Still, separating these lenses of viewing reality may undermine overlaps between

both types of knowledge and this should be recognized (Agrawal 1995). Both science and

IQ emphasize repeatability, analyses, and prediction gleaned through empirical

observations, albeit in differing ways (Huntington 2000).

The inclusion of IQ in monitoring programs allows knowledge-holders to

continue to use their skills and benefit from employment (Pearce et al. 2009) while

documenting and safeguarding knowledge for future generations. Few studies highlight

the key elements and procedures necessary to establish research relationships with

northern communities within specific and political research contexts (but see Pearce et al.

2009, Huntington et al. 2011, Grimwood et al. 2012, and Tondu et al. 2014). It is

possible to cultivate collaborative support for northern research by drawing from

examples on how to develop meaningful relationships with non-academic (e.g.,

indigenous and public) communities and stakeholders (e.g., Rowe and Frewer 2000,

Mercer et al. 2008, Phillipson et al. 2012) in non-Arctic contexts. Documenting IQ can

also engage and build relationships with northern local communities while allowing

researchers to identify unanticipated community perspectives, contexts, and other types

of knowledge that communities can share, including unique ways of community

participation.

For polar bear researchers, building relationships with Inuit can promote an

understanding and appreciation of nonconventional methods of knowledge formation. It

can also reveal persisting political and cultural barriers that may stagnate collaborative

efforts on the part of communities and researchers alike. Driven by the common goal of

better understanding polar bear ecology and the desire for community members to voice

their concerns, I report and summarize Inuit experiences with research. While quotations

include IQ and TEK of polar bears, I focus on Inuit views of polar bear research and

management in scientific contexts. I report on interviews with 23 hunters and 33 elders

(48 men and 8 women) in four Nunavut communities that range in their experience with

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polar bear research. I highlight ongoing challenges with polar bear research and

emphasize research practices that can improve support for research and monitoring

efforts, ensure better collaborations with Inuit communities and, ultimately, garner more

complementary biological and environmental data.

5.3 Methods

Over eight years of northern polar bear research in Nunavut provided me with the context

and experience to conduct this research. Collaborations with the Gjoa Haven Hunters and

Trappers Organization (HTO) began in 2008 during an independent project integrating

Inuit traditional ecological knowledge TEK of polar bears in a noninvasive survey (Wong

et al. 2011, Van Coeverden de Groot et al. 2013). This fieldwork allowed me to witness

firsthand the different relationships, experiences, and levels of enthusiasm and

engagement that Inuit hunters and elders have with polar bears and polar bear field work.

Camping on the land was often associated with unpredictable, physically and mentally

challenging situations. This provided unique opportunities to develop interpersonal and

adaptable research skills. It also provided context for subsequent interviews.

Interviews followed methods detailed in Chapter 4, but expanded on Inuit

relationships with polar bears and recommendations for polar bear research and

monitoring, which became the focus of this chapter. Briefly, HTOs prescribed and led all

recruitment procedures (radio announcements, flyers, and/or recommendations by other

community members), which varied in effectiveness among communities. HTOs also

recruited interpreters except in Arviat, where the Hamlet recommended an interpreter. I

recruited interview participants through a combination of key informant and snowball

sampling methods (Marshall 1996). In Arviat, most community members were familiar

with polar bear management regulations and research methods, and interview data

became saturated; no new themes emerged with additional interviews (Hsieh and

Shannon 2005). As in Chapter 4, participants were identified as “hunters” and “elders”

according to experience (active hunters, non-active hunters, and less-experienced

hunters) and names were coded to protect confidentiality.

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Semi-structured interviews included discussions on polar bear hunting, population

dynamics, monitoring, and management. As most initial participants steered interviews

toward their own views of polar bear population ecology research, subsequent interviews

included an opportunity for participants to describe what they felt was the “best way to

research and survey polar bears”. Generalized questions ensured conversations were not

encouraged in a leading way and follow-up questions that were posed as a response

encouraged participants to produce their own understanding and thoughts and clarify

information that was being discussed (Huntington 1998).

Interviews were analyzed as in chapter 4. I identified unique perspectives and

reported the quotations and participant information that I felt best described common

themes and categories. In 2015, I made a second trip to Arctic Bay, Arviat, and Kimmirut

communities to discuss initial results, perspectives at a broader community level, and

desirable research applications.

Outside of interviews, I spent time exchanging cultural views and stories,

familiarizing myself around town, and participating in community activities (when

invited) with community members and students. These interactions were exceptionally

important in cultivating trust, transparency, and comfort in sharing research perspectives

and understanding community priorities. Spending more personal time prior to data

collection through multiple visitations might have further strengthened participant

understanding and engagement (Pearce et al. 2009, Huntington et al. 2011, Grimwood et

al. 2012, Tondu et al. 2014).

5.4 Results

From May 2011 to April 2014 over four visits and one visit in February 2015, I

conducted individual interviews with 23 hunters and 33 elders (48 men and 8 women)

comprising 33 active, 14 non-active, and 9 less-experienced hunters. In February 2015, I

interviewed one additional active hunter. Interviews ranged from six to 63 minutes in

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duration on the land (for Gjoa Haven hunters and KU1) and at participant homes, hotels,

and HTO offices. Appointed interpreters translated 27 interviews. One Arctic Bay hunter

translated another participant’s interview prior to being interviewed. One Arviat hunter

translated six interviews following her interview, as the local interpreter was unavailable

due to illness. While questions initially focused on experiences with and perspectives on

polar bear population dynamics, monitoring and research practices, participants raised

concerns that pointed to cultural, ecological, and ethical considerations in research that

they felt needed to be shared with researchers.

5.4.1 Cultural factors affecting participant responses to research

questions

Several cultural considerations could have influenced participant responses and

involvement in TEK research, which extend beyond polar bear knowledge. The

interpreter in Arviat cautioned that modest participants responded with short answers and

it was frowned upon to “boast” about experience and/or knowledge. This ethic might be

so respected that participants provided vague responses or did not answer questions

directly. Arctic Bay and Kimmirut participants also touched upon some of these themes:

…[Polar bears] should not be bothered...don’t make fun of them or you know,

traditionally we were told ‘no don’t talk about animals in a negative way’…and

never say that you’re a great hunter too. Because if you say ‘oh I can get a bear’

the bear will teach you a lesson…so they told us ‘no don’t brag about polar bears,

that you’re able to hunt them’…even questions about hunting bears is kind of

very touchy too, for elders especially. I could tell that they don’t want to

answer…because they’re afraid…because it’s not something that Inuit talk about,

just bragging about it, [you know] it’s…vital…important subject, animals. Any

animal. Not to talk about them, not to bother them…leave them be, you know.

(AB15)

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The interpreter in Arviat also advised that Inuit were taught to “do as elders say”. Thus,

some interview topics were never questioned or doubted among community members.

Some knowledge and experience was deemed a “matter of fact”. Participants also

emphasized the importance of oral tradition.

…Those elders here…in Nunavut there’re [a] lot of uh, they know everything like

they have a lot of knowledge about life, or look after their family and so, they

know everything…the elders…like from young to…middle age. Taught them

how to be alive…but they don’t write it down because they have their knowledge

in their head…rules…in their head because we didn’t have any—or Inuit didn’t

have any paper or pencil so [they] have [it] in their head…so that’s…the Inuit

culture…we carry on…I carry, and now I told to my young family, my family, so

they started to know…so they’ll be know Inuit knowledge…like we don’t educate

by writing down...by looking at [it], by listening, and by doing it, we learn. (AR9)

The interpreter in Arviat indicated chores at camp were often distributed among family

members. Thus, while some individuals did not have practical experience, they were

familiar with technical skills through observation. Relevant to this, all participants

indicated they learned how to hunt by observing and/or camping with other (older) family

members.

By the age of 10 he started going with his dad to go hunting…he wasn’t really

taught how to hunt…he was watching his dad…but now he realized that he was

being taught how to hunt…but he didn’t know that he was being taught…just by

watching his father hunting…just looking at him, seeing him and he learned how

to hunt. (Interpreter translating for AB1)

Thus, Inuit share knowledge through experience as a “way of life”. Researchers should

become aware of and open to unanticipated responses and potentially sensitive topics.

Communities also stressed the importance of gathering knowledge through experience.

Spending time outside of communities (on the land) with community members can

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expand dialogue and encourage accurate interpretations of interview discussions while

establishing inter-personal relationships.

5.4.2 Inuit observations of polar bear ecology

All participants reported having more bear encounters in recent years than in the past.

Some participants indicated that the bears they have encountered were healthy.

…Last year he said that there’s more bears that are more fat…they rarely see

unhealthy bears…the only time they would see one is when it’s pretty old…it

won’t hunt—hunt as much…and it’s skinny. (Interpreter translating for AB9)

Others indicated the opposite.

Since they’re getting hungry, the polar bears…they seems to be declining in

fatness. So they’re skinnier one…lack of uh, food… the year before one that he

caught seems skinnier than the one that he caught last year…due to lack of food.

(K7)

Some participants attributed interactions with bears to cyclical changes in polar bear

distribution.

Back then there used to hardly be any bears…1920s, the father-in-law said they

used to go miles and miles by dog team, or by walking to go hunt polar

bears…but after 1980s, to now there’s a lot of bears…1920s, his father-in-law

was saying that there were a lot of bears back then…few years later they were all

gone…and now they’re all back…I think it goes like that, back and forth. (AB12)

Our elders, they say, they migrate, into other area…for years, and then they come

back…that’s what we’re experiencing now…back in early 80s, and mid 90s, there

were hardly any bears…there’s too many polar bears now. (AR16)

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Some participants linked these changes to food availability.

They go where there’s more food, you know…they always look around, they

can—they walk around everywhere for—look for food…so, if there’s more seals

down there they’ll be right there. (AB6)

And nowadays we tend to see bears close by Kimmirut…he doesn’t really know

why but he thinks it’s uh because they go—they follow their food…the more

hunters catch around the community…or just outside the community, the more

[bears tend to come] where the hunters hunt. (Interpreter translating for K1)

Despite climate change effects, many participants indicated bears were able to learn from

and/or adapt to changing environments.

He said he don’t really know about if [melting ice] affect the polar bears but he

said the um polar bears could stay in the water…they could go on the land. And

like, before they go on the ice they eat um, grass or from the land and they stay on

the ice…before they go on the ice and lay—laid down or rest or something they

eat grass so they don’t have to get hungry right away. (Interpreter translating for

GH3)

…Bears can catch seals even—even if the—if the ice is really thin…they’re great

hunters those bears…they’re really smart…they know how to survive…even if it

was just in the water floating, seal go by him and just grab it and eat it. (KU1)

All participants felt bears were more aggressive toward humans now than in the past.

Bears are really knowledgeable…they know now they won’t be caught…they’re

like humans…way of thinking that nobody’s gonna take them [to eat]…and that’s

why they’re smart as—they’re more aggressive and there’s [potentially] more of

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them now…the polar bears know that they won’t be shot at…now, but back then

they used to be afraid…knowing that they’ll be shot. (Interpreter translating for

AB5)

Arviat participants were particularly concerned with declining health in bears attracted to

and feeding at local dumps.

In the early 70s, ’65 to 70s, there has been increased in seeing bears around. And

yes we see more if it, they’re not healthy…because they eat a lot at the

dumps…before the 70s, it was much cleaner, you know, the tundra was much

cleaner, the town was cleaner but these days we have dumps…in most

communities. And that’s what they go for, so most—most bears, when they’re

hun-hungry enough they’ll go looking for food at the dump…and it’s getting

more and more frequent because of the dumps that they go looking for food.

(AR4)

Arviat residents have faced heightened safety concerns (Stirling and Parkinson 2006,

Kotierk 2010, Peacock et al. 2011) and being able to identify and respond to aggressive

bears has been and remains an ongoing priority. This was evidenced through participants

sharing knowledge of aggressive bears even when the topic was not addressed directly.

…A group of three or more? The lead bear, if he doesn’t attack right away, the

rest won’t…and if you’re approached that close? You don’t move…you don’t

make quick movement[s], you don’t move, you just sit still, because you’re

watching the lead bear…you don’t provoke it…you don’t even make any noise.

Like even coughing. (Interpreter translating for AR6)

…An elder always go through the radio… worried about young people, ‘Don’t

walk away so far’ or something like that. There’s always somebody encourage or

like, announce it on the radio… ‘Keep an eye, keep—keep look[ing] around,

when—when it’s dark’…there’s always somebody saying something about the

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polar bears, what to do and what not to do. (AR14)

Interestingly, participants across all communities indicated females and younger bears

were more likely to enter communities versus males and adults, respectively.

…The big adult male, they’re kind of—they got confidence, when they’re

walking…they kind of just kind of move around. Slowly. Young one—young

ones are very curious. They move around and [you know], they look around, they

go into c-camps, and you know, they’re the one[s] that follow the people

more…‘cause they’re young, they don’t know, they don’t have experience.

Whereas the big males, they know not to bother the camps, so they don’t. They

kinda cool. (AB15)

...They’re gonna bring their cubs right to the dump… they’re gonna show their

cubs where they can find their—their free meal? And the cubs grew, and, even

though they’re not with their moms anymore they—they’re gonna remember and

they’re gonna come back to the site, or to different places and they’re gonna find

whatever scent they…smell? (AR1)

Documenting observations of polar bear ecology offered elders and hunters a chance to

voice their personal observations and perspectives, regardless of agreement with

scientific views. Community members can offer a more nuanced understanding of

population dynamics than science alone. Polar bears are not isolated objects of study;

they also react to human interventions.

5.4.3 Management perspectives and recommendations for polar

bear research

Even though hunting regulations were implemented recently, participants stressed that,

historically, polar bears were harvested responsibly, sustainably and respectfully. When

learning how to hunt, young hunters are taught ethical responsibilities in addition to basic

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hunting techniques.

We always get enough food for the year we don’t try to finish all the bears we just

get enough. [When we get] what we need…we say stop or [even] any

animal…when we go out we check the tracks for fresh tracks, if we see them

sometimes when there’s bears with cub—young cubs we just don’t bother them

we just go after one single bear…when we have enough food for the family we’ll

always stop…we been controlling our animals…ever since long time ago…so we

could control it for our—the bears… ‘cause we don’t grow food…up here, that’s

one of our main diet…even without tags. (KU1)

…Bears are not just a game…and they’re not for pets. (K5)

…The older people, they know…how to handle them and [because] our parents

used to tell us not, to kill too many animal because what you need, just kill what

you need. No more than [that]. So that’s what’s, our rule is…Inuit. (AR9)

Some participants felt scientific and management practices (e.g., quotas and male-biased

harvests) have increased bear abundance.

But ever since I started growing up in Kugaaruk there’s way more bears than

when I used to be a small or young…today there’s a lot more bears now ‘cause

the hunters don’t kill the mom with uh females with little cubs anymore. (KU1)

The government specifically tells each community [how] many bears to

hunt…and not enough tags are coming into the community and that’s why the

population is growing. (AB9)

Some participants expressed concern over male-biased harvests and felt males were

important in maintaining populations.

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…There’s a by-law now and like they have to go for only males and he asked that

person how come like if you catch all the males and there’s no more males…how

they gonna make cubs…he said he don’t believe that there’s only one male and

there’s lots of females they gonna make lots of cubs ‘cause they always make

cubs only once a year…same time. (Interpreter translating for GH3)

Participants were aware of mark-recapture methods (ear tags, tattoos, collars, and

tranquilization) used to monitor polar bears. Most participants have collected scientific

samples or were aware of harvest-based sampling.

…They gave us an example of how they counted polar bears and they used uh,

beans. They had a whole bunch of beans and then white beans of some sort and

then they—they opened that and then they colored…so many beans and then they

thrown them back in there, they shook it and then they grabbed a handful…and

then there’s a couple of beans, that they grabbed and then—and then the rest are

not colored so they determine the population in each area that way sort of…so,

yeah that’s exactly how they do it. With the tattoo…so instead of just coloring the

bean, they tattoo the bears. (GH2)

Participants were also concerned with loud aerial surveys that negatively affect bears,

which are sensitive to noise and depend on sound to hunt.

…Polar bears are hunters. They need their ears to hunt seals. ‘Cause they’re under

the sea…I mean the ice. They need the ears for sure and they are ask when they’re

working, in an environment that’s really loud, they’re asked to use ear

protections…so they won’t damage their ears. Helicopters tend to damage

ears…and the polar bears are more skinny ‘cause they’re not successful in their

hunt…skidoos more safer than the helicopter. (AB12)

Participants also felt tranquilization continues to affect polar bear meat for consumption.

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You can tell, if the bear is healthy, or not…if you catch a—one with the

tattoo…on the lip…even cooking it you can tell that it’s unhealthy

sometimes…the water—they’re boiling in…it’s a little whiteish. (AB11)

Due to ongoing concerns, participants provided broad and specific

recommendations for monitoring and research methods. Some participants preferred

noninvasive versus invasive studies, reminding researchers to treat bears with respect.

He said it’s better if you don’t put them to sleep and looking at the footprints

instead to study. (Interpreter translating for GH7)

I think the way we’re doing now it’s—I think it’s better to count bears and…

‘cause we’re on the ground…we don’t put them to sleep or anything we just see

them and let them leave…we can always tell whether there’s more bears or less

bears as—as a—‘cause we keep going out rather than hunting bear only we—we

go out on the sea ice all the time. (KU1)

Participants recommended all surveys take into account bear movements, seasons, and

ice conditions, as surveys using transects and random sampling regimes (Buckland et al.

2001) incur a sampling bias (e.g., individuals in difficult-to-access areas).

Sometimes there are surveys being done on polar bears but they don’t catch all of

them, or they don’t see all of them…it’s kind of impossible. He has been on the

helicopter too when they’re surveying…it’s—you can’t [nitpick] any bear,

like…sometimes they’ll miss…when they’re following the tracks by helicopter, if

they’re zigzagging or going everywhere, uh, they tend to get air sick…following

the tracks. (Interpreter translating for K6)

Community members also emphasized the importance of spending time making

observations in the field and including local knowledge could help interpret scientific

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findings. Participants continued to support and in some cases prefer harvest-based sample

collection.

For his opinion, he’d rather have a polar bear killed…get the meat sample and the

fat sample and send that down…to be analyzed, why the polar bears are getting

sick…[he] doesn’t want anyone coming up here, so they won’t be scared off…so

they can be healthy. (Interpreter translating for AB1)

He prefer not to have them surveyed…he prefer uh when the hunter catches

on…uh the fat, the meat, the penis, the heart and all that be sent down instead of

them coming up here…and survey and research them…they use helicopters to

tranquilize the bears …and the tranquilizer, medication I think, is still in the body

and he doesn’t want that. (Interpreter translating for AB12)

Unfortunately, many community members were not aware of why researchers are

interested in polar bear samples or how samples could be used to monitor polar bears.

Few times we did on our sporting hunting uh with the polar bear and there was a

scientist came along to, to survey and…test out the polar bears and stuff like

that…I didn’t really learn it…they were on their own doing stuff. (AB2)

They don’t report back…if they’re given samples…and they don’t tell them why

they’re collecting, [what] they want those samples for…the only way that you can

get those is ‘cause the hunters are giving those to the GN (Government of

Nunavut)… he feels it would be nice if the GN or whoever they sent the samples

to are—if they can get feedback on those…they must know as to—if you receive

the samples, where it might have come in from…and they would know accurately

a—if they’re given feedback of how old, and…was that bear healthy or unhealthy.


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Interestingly, the differentiation between academic versus government researchers was

not clear in these discussions, and several participants discussed research in the context of

academic and government research interchangeably. Management and research practices

should consider long-term ethical and ecological impacts on local communities and polar

bear populations, which will differ across the north. Explaining how scientific polar bear

surveys (biological sampling, fieldwork, and data collection) are designed, their

limitations, and the inferences that are made from sampling data to community members

could resolve some criticisms against these surveys. Some academic and government

researchers already make these efforts, suggesting other factors that limit access to or

understanding of scientific information and materials might be at play. These

implications are not always immediately evident through initial community consultations

or scientific literature. For example, communities across the north differ in levels of

experience and engagement with research that might only be revealed through

establishing relationships with community members to identify levels of communication

and reporting back that are required.

All participants felt including Inuit hunters and TEK can enrich polar bear

research with historic, holistic and contextual insight to improve projects and achieve

common research goals. Participants were especially supportive of efforts that allow

elders to share their stories, experiences, and perspectives.

…All the hunters are usually out, along these leads…they always have a story to

tell, if they see a bear…how many bears they saw, they’re reliable

information…so that information were used to determine—let’s [say] caribous

were caught in this area, how many. Like the same with the polar bear, ask the

hunters if they saw anything, if they found a bear here…other hunter does found a

polar bear here, we can determine if it’s the same bear if they’re close

together…so we could tell by what day the hunter saw that, what day the other

hunter saw that…they could tell ‘yeah that’s a different bear’…so that way we

could tell, and the seasons too, are different. Like right now, they’re in the

den…summertime we know most of them are around the coast. (AB15)

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Community members were able to provide specific recommendations in research design

and encouraged the inclusion of hunters and elders, suggesting communities could

inform—and recognize value in—collaborative research.

5.5 Discussion

5.5.1 Lessons learned from community-based interactions

In this study, few community research priorities were discussed during initial HTO

meetings. Community-wide concerns only became evident after subsequent interactions

with community members and multiple visitations, where time was spent to allow

community members to understand research objectives and resulting outputs. Participant

recruitment was especially challenging in Arctic Bay due to previous misrepresentation

by (and, thus, lack of trust in) non-local visitors and was only successful after

broadcasting a live radio show, where respected community members were able to phone

in and ask questions about research objectives and also show support for this work.

Similarly, local support and encouragement by other community members facilitated

participant recruitment in all communities.

Through their own enthusiasm in and understanding of research objectives,

interpreters were especially important in affecting the willingness of community

members to participate in this work when approached. Interpreters also provided a

contextual background for interviews through their own participant observations and

experiences, such as identifying reputable community members and instances where

participants might have held back responses. While research experience varied among the

interpreters, each interpreter influenced the research process in some way. The Arctic

Bay interpreter had no previous experience with research participation, yet introduced

this research to participants without the researcher’s intervention and also shared her

support for TEK work outside of interviews. Interpreters in Gjoa Haven and Kimmirut

were more reserved—displaying little evidence of their own research perspectives—and

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interactions were largely research-oriented, creating a more “formal” atmosphere for

interviews. The Arviat interpreter was a recognized translator and asked to review the

interview guideline prior to interviews so that she could anticipate how participants

would respond to some questions and guide participants toward research themes of

interest. AR10, who translated six interviews in Arviat, had no previous experience with

translations and in some cases responded to interview questions directly without the

participant’s response (as her own responses), suggesting her focus was on the “true”

answer to particular questions versus unique participant perspectives. In this manner,

research participants not only shape the research and knowledge-gathering process but

also influence how community-based research is perceived and received by the

community. Research practices that are culturally acceptable and effectively meet

community priorities differ from community to community and following ethical

guidelines and permitting processes does not necessarily guarantee local support (INAC

1993, ITK and NRI 2007, CIHR et al. 2010). These standardized and institutionalized

processes do not account for community-specific preferences, past experiences with

research, and capacity for research engagement. Spending as much time with community

members as early as is feasible in the research process can allow researchers and

communities to overcome any cultural barriers and establish the capacity to mutually

understand and appreciate scientific- and community-based applications. Unfortunately,

funding agencies do not always provide room in budgets for initial community

interactions, relationship-building opportunities and meetings for research validation and

completion. Training for researchers to establish these capacities is also lacking. Despite

these limitations, efforts made by researchers to understand and engage with communities

are critical and morally necessary because researchers and Inuit are impacted by research

in different ways. Research directly impacts Inuit livelihoods and their relationships with

their surroundings.

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5.5.2 Overlaps between polar bear TEK with science and other

TEK studies

Though polar bear TEK has been documented in Arviat (Arviat Hunters and Trappers

2011, Kotierk 2012), Gjoa Haven (Keith 2005), and Kimmirut (Kotierk 2010), no studies

of TEK in Arctic Bay have been published and individual views and perspectives are not

necessarily generalizable across communities and Inuit as a whole. Building on polar

bear TEK literature, this study serves to voice detailed Inuit perspectives from different

Nunavut communities and regions. Participants were able to share—and in some cases

reiterate—their own views within a research (versus management) context, make specific

recommendations on monitoring practices, and highlight themes that they felt were

important. This work also allowed community participants to ask questions about current

polar bear research and scientific methods and how data could be used to inform

management, from a research perspective.

Several ecological and scientific views expressed by community members align

with previous TEK studies. Participants in this work shared views that are consistent with

reports from Pond Inlet, Qikiqtarjuaq, and Clyde River (Dowsley 2007, Dowsley and

Wenzel 2008) and Pangnirtung and Iqaluit (Kotierk 2010). Across the north, Inuit still

report recent increases in polar bear abundance and the ability of polar bears to adapt to

rapidly changing environments (Keith 2005, Tyrell 2006, Dowsley 2007, Arviat Hunters

and Trappers 2011, Kotierk 2012, Kotierk 2010). Consistent with previous TEK,

community members warn polar bears are dangerous animals (Keith 2005, Kotierk 2010,

Kotierk 2012) and some Inuit are weary of consuming polar bears that have been eating

garbage (Arviat Hunters and Trappers 2011). In the past, community members have also

reported dissatisfaction with scientific methods (Tyrell 2006) and the level of influence

that Inuit have in management (Kotierk 2010). Together these reports suggest Inuit share

concerns that are ongoing and wide-ranging across the north, and persist despite efforts to

integrate them through research collaborations and co-management (Peacock et al. 2011).

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Across communities in this study, participants reported increasing bear encounters

are an adaptive response to dietary changes, which has been scientifically reported in

Western Hudson Bay, where bears are seeking alternative food sources around

settlements (Stirling and Parkinson 2006, Government of Nunavut 2012, Gormezano and

Rockwell 2013b). Though dietary changes have been attributed to sea ice changes

limiting access to primary prey (ringed and harp seal; Thiemann et al. 2008b), evidence

for bears foraging on land-based foods (Dyck and Romberg 2007, Gormezano and

Rockwell 2013a, Rockwell and Gormezano 2009)—reported as typical behaviour by

most participants here—might also suggest an opportunistic feeding strategy (Thiemann

et al. 2008b), where bears pursue readily available food sources even in the presence of

preferred ones (Gormezano and Rockwell, 2013b). Bears foraging for land-based foods

have been reported empirically prior to recent concerns over climate change (Gormezano

and Rockwell 2013a). Observations of bears consuming garbage are not uncommon

(Gormezano and Rockwell 2013b) and bears are likely more aggressive at sites where

resources are defendable and predictable (Elfström et al. 2014), such as garbage dumps

and Inuit hunting caches, which might explain aggressive behaviour of bears near

communities. Participants also felt bears are no longer afraid of humans because of

habituation to scientific surveys and human activities, consistent with other community

reports (Keith 2005, Kotierk 2010) and scientific observations (Dyck 2006, Stirling and

Parkinson 2006, Andersen and Aars 2008). Habituation to human activities is not

unexpected, especially when food is rewarded (Keith 2005).

Participants further reported young males are more likely to enter communities,

showing some evidence for a sexual dimorphic life history, where males maximize

growth by exploiting high-quality food areas (remote areas avoiding humans) and

females prioritize offspring and avoid males (Elfström et al. 2014). Participants also

reported behavioural adaptations, where mothers teach young how to acquire food near

communities; this behavioural transmission from mother to offspring has been reported in

other bear species (Kaczensky et al. 2006, Madison 2008, Elfström et al. 2014). Thus,

polar bear characteristics reported by community members could reveal early changes in

population health and ecology; large solitary males near communities might indicate lack

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of accessible, high-quality habitats (Elfström et al. 2014).

5.5.3 Challenges and considerations for polar bear monitoring and

research methods

Across the surveyed communities, several participants criticized invasive mark-recapture

methods for their negative effects on polar bears. Loud vehicles (e.g., snowmobiles)

displacing polar bears from hunting areas have been reported scientifically (Andersen and

Aars 2008), which could lead to decreases in body condition and reproduction. Although

scientific studies have shown little evidence for mark-recapture and radio collaring

effects on indicators of body condition, reproduction, and survival in polar bears (Messier

2000, Thiemann et al. 2013, Rode et al. 2014), the impacts of handling on long-term

behaviour and human-bear interactions have not been reported. The inclusion of local

communities in monitoring research can shed light on effects of research practices that

might not be immediately recognizable through scientific methods. This has been

recognized and efforts to include local participation are already in place (Peacock et al.

2011, Vongraven and Peacock 2011). Participants in my work also reported declining

health and body condition, and abnormal behaviour attributable to radio collaring, as well

as increased aggression of bears that have been previously handled toward humans, thus

endangering local communities. Still, some community members believe mark-recapture

could provide important data on population dynamics to inform appropriate harvest

regulations, as long as surveys take into account temporal and spatial considerations for

representative sampling. Mark-recapture surveys in some regions occur in the spring

during den emergence and mating season to maximize probability of capture (Vongraven

and Peacock 2011, Rode et al. 2014) and interpretations of population viability analyses

have been discussed within the context of sampling biases due to bear movements and

reactions to helicopters (Taylor et al. 2006).

Each polar bear subpopulation is examined and studied every 10 to 15 years

(Peacock et al. 2011, Vongraven and Peacock 2011) and communities affected by this

work are usually involved from the initial planning stages (e.g., consultation meetings),

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through the research as participants, to reporting back to communities as a three to four

year process. In some cases, local community perspectives and TEK have been

documented to complement scientific studies (e.g., communities harvesting Baffin Bay

[Dowsley 2007], Davis Strait [Kotierk 2010], and Western Hudson Bay [Kotierk 2012]

populations). However, unless a community harvests from several populations, a

substantial time can pass until polar bear-related research occurs in the same community

again. This suggests that some of the research concerns that community members

reported to me might reflect research practices that are out of date, perhaps due to lack of

awareness or understanding of updated research methods in other areas (e.g., new less-

invasive aerial [Stapleton et al. 2014, Stapleton et al. 2016], genetic-based [Van

Coeverden de Groot et al. 2013] and biopsy-dart [Pagano et al. 2014] sampling methods

that have been developed as a response to community concerns) and accessibility to

contemporary scientific data in other regions (whether through scientific literature or

reports). Regional representatives of Inuit designated organizations, for example, regional

wildlife boards, must exchange relevant and updated information with their counterparts

from other regions, which must then be distilled to each community HTO. As there are

three regions spanning Nunavut—Kitikmeot, Kivalliq, and Qikiqtaaluk comprising five,

seven, and 13 communities, respectively—frequent exchange across this scale is certainly

challenging. However, through research participation and engagement with researchers,

community members could become aware of ongoing research in other regions.

Instances where participants do not support any scientific research practice are, in

some cases, associated with a misunderstanding of research goals, suggesting there is

room for improvement in communicating research objectives and expected outcomes

among management, research, and local communities. Despite concerns at the participant

level over insufficient reporting, some (academic and government) researchers do hold

consultation meetings on a frequent basis when conducting polar bear research, include

local communities in the field where possible, and report back to HTOs through written

translated reports, orally translated presentations, and discussions with translators present.

In all communities, scientific information (prepared by the Government of Nunavut) is

available through booklets distinguishing males and females (to encourage male-biased

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harvests) and posters explaining scientific surveys. HTOs are aware and acknowledge

these efforts, despite lack of awareness at the level of community members. This

indicates that even though efforts are in place to distil research processes and data to

relevant community organizations, community members—especially elders and

individuals that are not active in research and/or management participation—may not

necessarily receive or have access to this information; in other words, research is not

being delivered or communicated back in a way that communities desire and need.

Research reports should highlight themes that are relevant to community-specific

interests and priorities (e.g., implications for harvests and human-bear interactions) and

how these results can be used in monitoring and management and—most importantly—

benefitting Inuit. Because Inuit knowledge is often passed on through word of mouth

versus written reports, effort is needed to establish capacity for the diversity of

community members (e.g., youth, older elders) to learn about scientific information as it

relates to the community. This could be made possible by making research findings

accessible through presentations at the school, local organizations, community hall, radio

announcements, posters, videos, and websites that include contact information,

depending on the community. These efforts will require active HTO involvement and are

in most cases considered as falling beyond the scope of a typical scientist’s job

description. Aside from their own research priorities, academics and scientists working in

the north require skills in communications across cultural settings, consulting, program

management and supervision, hiring, mentorship, and financing, to name a few. These

efforts should be routine and are necessary to engage communities and keep community

members up to date with research projects and the broader contexts that they are a part of.

While these commitments could be challenging for “southern” researchers to meet—

especially with expensive northern travel and limited time available to spend up north—

this level of engagement for any research in the north is necessary from an ethical,

practical, and moral standpoint.

In some communities, mass turnover of community (HTO) staff might make it

difficult for community members to stay current with research processes. HTOs often

receive several (research and non-research related) reports at a time and other community

165

priorities might take precedence over reading them. HTOs are not only involved in

research activities, they review proposals, technical reviews, economic development

plans, land plan use activities, harvesting issues, etc. These form a plethora of demanding

issues that at times cannot be accommodated. HTO boards are established on the basis of

knowledge experience, and the administrative duties and bureaucracy demanded of them

often lie beyond their capacity. Combined with the limited financial and timing capacity

of most researchers to remain up north to engage communities, these ongoing issues

suggest that polar bear research, and research in the north in general, might require

community-based research institutions and/or coordinators, where designated, active

liaisons bridge gaps in communication and engage communities in research projects.

Some of the barriers to communication might be due to poor interpretation by researchers

and community members, or the lack of technical understanding of ideas and scientific

information that is inadequately translated into local dialects (Inuktitut) and back to

English. Thus, interpreters (for both research conduct and preparation of reports) with a

comprehensive understanding of research contexts, data gathering and analysis, and

applications are necessary for this process. These issues touch on another endemic issue

that is education and beyond the scope of this discussion. Aside from these exigencies,

researchers are still responsible for the research process and adapting their research views

according to Inuit culture, context, language, and protocols that their research is a part of.

5.5.4 Concluding remarks for northern community-based research

Discussions on research relationships with and practices conducted by academic and

government organizations are not easily distinguishable, suggesting some community

members might generalize their research experiences to “outsiders” as a whole. Past

views and experiences still shape current community perspectives, and views against

academic and/or government research persist, especially when past research practices

have ignored or failed to incorporate community concerns. Communities differ in their

levels of research engagement and willingness to participate yet more time and effort can

ensure an understanding of research objectives, especially in communities that have

negative views toward all types of research due to past experiences with unethical

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conduct (e.g., inadequate consultations, disagreement with research practices, lack of

reporting back, and misrepresentation). Considerable time is needed to mend past

relations and experiences. For Inuit, local knowledge and perceptions are shaped by

social views that are fundamental to physical survival (Bennett et al. 2016). For

researchers, knowledge perceptions are usually research- and/or academic-focused and

not necessarily relevant to livelihood. Ethical research practices from the outset are

critical in setting the stage for all types of forthcoming research activities. Opportunities

to participate in research and decision-making processes need to be made transparent by

the researcher (Chilvers 2008), especially with respect to how outputs will be used to

direct policy (Rowe and Frewer 2000). Clarifying community and research roles and,

more importantly, research limitations and their impacts on communities can avoid

misconceptions.

Although all participants follow management regulations, each individual varies

in his or her level of familiarity with and support for current management and research

practices. Researchers should contact other researchers who have worked in the same

communities as well as local Hamlet, Arctic college, and relevant community

organizations to determine what forms of engagement do and do not work. Two-way

lines of communication between researchers and community members should be

maintained and accommodating for community members throughout all stages of

research (e.g., telephone or fax may be preferred over email). It will likely be necessary

to report back and check in on multiple occasions. This will require persistence on the

part of researchers and communities are likely to engage if research objectives speak to

community priorities. Lack of community engagement might suggest that research

outputs have failed to incorporate community needs. Research questions and efforts to

determine how communities could benefit from their participation might need to be re-

visited. As with any personal interaction, relationships should be maintained and nurtured

even after data gathering is complete.

Strong and transparent relationships between polar bear researchers and Inuit

communities are necessary to overcome persisting misconceptions in research and

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communities. For community members, most types of research have been viewed as

inseparable from government agendas through funding and consulting programs

(Bocking 2007) and past histories and power relations have politicized views of scientific

research as a whole (Reed and McIlveen 2006). Upon arrival into any community, a

researcher should take on the role of a learner, shifting from research driven by expertise

and certainty to one with humility and willingness to adapt to changes (Grimwood et al.

2012, Brunet et al. 2014b). As community participation in research projects will

undoubtedly impact research results and community members through potential to inform

management, forming collaborations in research design can guide research toward

community priorities so that these priorities are effectively included in subsequent

decision-making. In the past, academics have been criticized for prescribing expected

research plans and outcomes in a rigid way, leading to condescending views of unfamiliar

knowledge practices and unwelcoming interactions with community members

(Grimwood et al. 2012). Notwithstanding, community members also recognize the need

to strengthen communication and relationships to achieve a mutual understanding in open

collaborations. Ethical research conduct will pave the way for positive conceptions of

forthcoming research programs. In these contexts, the ability to build meaningful

relationships is not only critical for successful research involving TEK, but for sustaining

community involvement in research activities and support for research-based policies.

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Chapter 6

Synthesis of chapters and concluding discussion 6

6.1 Summary of chapters

In chapter 2, TRF assays were successfully developed to quantify telomere lengths in 21 wild

grizzly bears (seven females and 14 males). While effects of age and sex on telomere length

were significant and indicators of acute and oxidative stress were not significant, these findings

were based on small sample sizes and will require further investigation in larger groups.

However, TRF assays using fresh samples collected from wild animals are feasible in frequently

monitored grizzly bears associated with life-history data, which could potentially allow for

longitudinal studies to quantify telomere rates of change. These studies could incorporate

survival and capture characteristics in telomere models.

In chapter 3, qPCR assays using 40 salvaged polar bear heart, muscle, and skin tissues

collected by Inuit hunters were able to detect differences in telomere length among age groups,

sex, and populations. While differences in age and sex were only significant in muscle,

significant differences across five polar bear populations were detected using all tissues. Assays

of additional skin samples across age and sex groups could confirm age and sex differences for

applications in noninvasive surveys. At minimum, this work suggests differences in telomere

length across populations could reflect genetic and ecological stressors affecting biological

senescence.

In chapter 4, interviews with four Inuit communities across Nunavut revealed shared

methods of identifying polar bear sex, age, body size, and health and hunting selectivity relates

directly to personal experience and preferences. The ability to distinguish individual polar bears

is important not only for food, fur quality, and hide preparation, but also safety against

potentially aggressive bears. Inuit methods of identifying polar bear characteristics show some

overlap with conventional scientific methods, suggesting Inuit could provide frequent,

complementary information on polar bear populations.

169

In chapter 5, interviews indicate that guidelines and ethics procedures for community-

based collaborative research in the north do not always guarantee meaningful collaborations.

Though efforts to report scientific information back to communities are in place, Inuit still

continue to meet polar bear research with some resistance. Strong relationships with Inuit

communities are necessary to establish and maintain community capacity in monitoring, as well

as encourage relevance for research outputs and, thus, support for resulting management

decisions.

6.2 Telomeres as an indicator of biological senescence

While TRF assays could potentially detect age- and sex-specific differences in telomere length in

wild grizzly bears, qPCR was more practical for detecting these patterns in wild polar bears.

Quantitative PCR was also able to show differences in telomere length among populations.

Differences in telomere length could reflect differences in ecology (Thiemann et al. 2008a) and

biology (Derocher and Stirling 1998), as well as responses to local genetic (Cronin et al. 2009,

Zeyl et al. 2009, Peacock et al. 2015) and environmental stressors (Stirling and Parkinson 2006,

Peacock et al. 2011). Rapid changes in sea ice conditions (Regher et al. 2007), prey availability

and composition (Thiemann et al. 2008a), hunting pressures, and interactions with humans

(Dowsley 2009) could elicit stress responses that lead to physiological damage and thus, aging

phenotypes (Cadenas and Davies 2000, Monaghan et al. 2008, Macbeth et al. 2010, Beaulieu

and Constantini 2014). In this manner, it is likely that telomere lengths will serve as a more

appropriate marker of biological senescence, versus chronological aging. Understanding how

environmental and physiological stressors mediate population characteristics (e.g., age and sex

structure, body condition) is necessary for appropriate management actions. Prolonged exposure

to physiological, oxidative stress responses could compromise survival and reproductive output

(Macbeth et al. 2010, Beaulieu and Constantini 2014), and hence population abundance.

Because several interacting physiological, ecological and environmental factors could

impact telomere dynamics, they should be considered in any model for telomeric aging. One

such variable is body size, which varies across polar bear populations (Derocher and Stirling

170

1998), and is indicative of body condition and survival (Stirling and Parkinson 2006, Regehr et

al. 2007, Stirling et al. 2010), as well as reproductive output (Derocher and Stirling 1996). Body

size has been shown to shorten telomeres and contribute to aging in wild house sparrows

(Ringsby et al. 2015) and American alligators (Scott et al. 2006). Telomere rates of change

(attrition) could also vary with chronological age (Frenck et al. 1998, Hall et al. 2004, Pauli et al.

2011), with higher rates of shortening in early life due to rapid cell and energy turnover (Sidorov

et al. 2004) and stress during maturation to adulthood (Hall et al. 2004, Salomons et al. 2009).

Chapter 4 showed some support for this, where Inuit indicated that polar bears achieve adult

sizes fairly quickly. Telomere attrition may also vary according to differences in telomerase

activity across tissues (Eisenberg 2010, Monaghan 2010). Though rare, telomerase activity in

somatic tissues could be quantified in cell culture (e.g., Gomes et al. 2011) or directly from

tissues (e.g., Jacobs et al. 2010, Lin et al. 2010). Tissue-specific attrition rates could also be

estimated in vivo by re-sampling the same wild or captive individuals across time, confirming

identity through microsatellite genotyping (Van Coeverden de Groot et al. 2013) or breeding

records, respectively. Such longitudinal studies could also allow for changes in somatic

functioning and individual survival to be observed. Heritability and relatedness may also affect

telomere patterns and attrition; evidence for this has been shown in humans, where longer

telomeres have been observed in the offspring of older fathers (Monaghan 2010, Eisenberg

2010). Heritability and relatedness in wild polar bears could be determined through

microsatellite genotyping (van Coeverden de Groot et al. 2013). Maternity and paternity have

been previously estimated for M’Clintock Channel and Gulf of Boothia polar bears (Saunders

2005) and efforts to improve these estimates through the addition of more loci are ongoing. Both

populations are also currently being re-sampled through mark-recapture (Government of

Nunavut 2015).

By examining wild polar bear populations, this research contributes to a better

understanding of polar bear senescence in vivo, as very few wild animals live long enough to

suffer senescent declines (Monaghan et al. 2008). This work also suggests qPCR assays for

telomere length could be applied to skin and, thus, similar noninvasive samples (e.g., biopsy

darts and/or hair samples). Prior to noninvasive survey applications, qPCR assays in a larger

sample of known skin samples that capture variation in age and sex within populations,

171

especially females and cubs, will be required to characterize telomere lengths as they relate to

these groups. Noninvasive samples could be genetically sexed, genotyped and cross-referenced

with mark-recapture data to incorporate known age, sex, and additional body condition indices

(Taylor et al. 2006a, Van Coeverden de Groot et al. 2013) to evaluate their effects on telomere

dynamics in these samples. Hair cortisol concentration could also be measured in hair samples

(Beschøft et al. 2011) to include indices of stress. Once developed, telomere assays in

noninvasive samples could be linked to Inuit interpretations of tracks (Wong et al. 2011) to

incorporate information on bear characteristics, morphology, behaviour. For harvested polar

bears, supplementing biological data from harvested samples with Inuit hunter knowledge of

health, body condition, and population changes could reveal factors associated with individual

polar bears and samples that are not detectable using scientific methods. Interviews with

communities could also reveal drivers of hunter selection—for example, management

regulations, personal preferences, or logistical constraints leading to biases in harvests—to

determine how representative samples and thus telomere assays are to polar bear populations and

species as a whole. For survey and monitoring applications, telomere assays will require the

same assay procedures and protocols for quantification to be conducted in the same lab to

minimize inter-assay (multi-year monitoring) variation (Nakagawa et al. 2004, Horn et al. 2010,

Aviv et al. 2011, Dunshea et al. 2011, Nussey et al. 2014).

For polar bears, quantifying DNA methylation in known age-related epigenetic markers

could serve as an alternative molecular method to telomeric aging. In mammals, DNA

methylation involves the addition of a methyl group to the 5-carbon of the cytosine ring of a

CpG dinucleotide (cytosine followed by a gunanine base; Calvanese et al. 2009, Jung et al. 2015,

Zampieri et al. 2015). CpG sites are largely focused in promoter regions and repeat sites, where

methylation usually silences gene expression and/or maintains genome integrity (Calvanese et al.

2009, Jung et al. 2015, Zampieri et al. 2015). In response to environmental factors and stochastic

errors in transmitting epigenetic information over time (Zampieri et al. 2015), changes in

methylation of CpG sites with age (hypomethylation and hypermethylation) have been observed

in human blood (Fuke et al. 2004, Bjornsson et al. 2008), muscle (Zykovich et al. 2014), and

skin (Grönniger et al. 2010) and a range of mouse tissues (Wilson et al. 1987). Recently, the

effect of age on percent CpG methylation in several known age-related epigenetic markers was

172

observed in humpback whale biopsy tissues (Polanowski et al. 2014). These assays have not

been conducted in ursids and, as with telomeric aging, will need to take into account potential

confounding factors, such as environmental variation (Polanowski et al. 2014, Jung et al. 2015).

At a broad scale, for any study examining age in wild animals, sampling across age

categories in age-structured populations could be biased due to the inherently low number of

individuals in older age classes (Wilson et al. 2008, Nussey et al. 2008). For telomeric aging,

sampling could also be biased if polar bears are associated with selective disappearance of

particular telomere lengths or telomere attrition rates that are cohort-specific (Monaghan 2010,

Mather et al. 2010, Eisenberg 2010). For example, critically short telomeres may not be observed

because individuals with very short telomeres die off, perhaps due to extrinsic mortality risks.

These biases could potentially limit adequate sampling across all age categories. Biases in

harvests toward large, adult males due to management regulations and hunting preferences also

limit adequate harvest sampling of cubs and females within populations. Across populations,

harvest quotas differ (e.g., from three animals in M’Clintock Channel to 61 in Davis Strait;

Government of Nunavut 2014-2015 Harvest Report), which limit equal distributions of harvest

samples across all populations. For populations with small quotas, larger sample sizes could be

achieved through noninvasive sampling led by Inuit hunters (Van Coeverden de Groot et al.

2013), where cubs and females could be sampled by targeting denning areas in the spring after

emergence.

6.3 Inuit methods of estimating polar bear health as potential

indicators of biological senescence

For Inuit, identifying indicators of biological senescence (health), chronological age and sex in

polar bears is important not only to follow harvest management regulations, but also govern and

interact with a resource according to traditional ethics and values. Inuit observe body size and/or

fat, fur color and quality, and bear movements and behaviour as indicators of polar bear health.

In Arviat, Inuit usually identify health of polar bears that they encounter, as health has direct

implications for aggressiveness and, thus, human safety. Inuit prefer to pursue healthy bears

173

when hunting, especially for food and hides, which are of higher quality in healthy bears.

According to Inuit, polar bear health is impacted by factors that contribute to stress, including

hunting ability. Stress contributes to biological senescence through the accumulation of

damaging reactive oxygen species produced as a by-product of stress responses (Macbeth et al.

2010, Beaulieu and Constantini 2014). However, in instances where food is not available, stress

responses can mobilize energy toward increased foraging effort (Romero 2004). Similarly, Inuit

indicate changes in prey availability impact health; in Chapter 3, telomere lengths among

populations corresponded to levels of prey diversity, with shortest mean length in a population

with low prey diversity (Thiemann et al. 2008a). Inuit also indicate male-to-male combat

impacts health, and unhealthy bears are more aggressive toward humans. It is likely that

aggression is associated with elevated stress hormones (Goyman and Wingfield 2004), which

could contribute to telomere shortening (Epel et al. 2004, Haussmann et al. 2012). Inuit also

report younger bears are more active and aggressive toward humans, suggesting age and stress

could interact to affect biological senescence. Indeed, Inuit are likely aware of methods and

indicators of biological senescence in polar bears and their knowledge could inform—and in

some cases overlaps with—scientific approaches to gathering these data. However, the type of

information that government and academic scientists seek is also affecting Inuit knowledge

formation within the context of how Inuit interact with or understand polar bears. For example,

Inuit identify ages and body sizes of bears to protect cubs during harvests though, historically,

only body sizes were of interest (Chapter 4). Some Inuit examine teeth to age polar bears, which

is likely due to experience with estimating age for harvest monitoring records. When engaging

with Inuit communities, researchers must consider the dynamic nature of Inuit qaujimajatuqangit

that is actively shaped by the social, cultural, and ecological systems within which it is

embedded.

6.4 Conclusions

The interviews in this work suggest Inuit consider several observations at the same time to

distinguish age, sex, and body size and health in polar bears. This approach to examining polar

bear characteristics and biological senescence could certainly be paralleled using scientific

methods, where multiple factors are considered simultaneously to model telomere dynamics. For

174

conservation applications of polar bear research—and all types of research in the north—long-

term relationships with Inuit communities will be necessary not only to acquire biological

samples and document traditional ecological knowledge, but also to ensure relevance and

meaning of scientific outputs for communities. Inuit communities interact with animals as part of

their livelihood and are likely able to suggest and/or inform research methods that are of

conservation relevance. Further, Inuit interpretations of scientific information distilled in a

comprehensive manner could allow for more effective integration of traditional ecological

knowledge and Inuit qaujimajatuqangit in northern co-management. For scientists, a better

understanding of Inuit knowledge formation and the cultural, ecological, and social processes

that Inuit persist in will likely allow for more meaningful and responsible methods of research

collaborations and co-management.

This research demonstrates that the direct participation of Inuit hunters in collecting

samples for scientific research could allow for physiological investigations of ecological and

environmental factors that impact biological senescence in polar bears, which would otherwise

not be possible. Using telomeres as an indicator biological senescence, TRF assays could be used

in frequently monitored animals that provide fresh, high quality samples, while qPCR assays are

useful in noninvasive samples and animals where collecting high quantities and qualities of

genomic material is difficult. For polar bears, scientific interpretations of ecological data could

be enriched through the inclusion of Inuit knowledge of population characteristics and indicators

of biological senescence. Inuit continue to support the inclusion of traditional knowledge in

developing scientific methods to achieve common conservation objectives. Still, efforts are

needed to establish and maintain strong relationships. The inclusion of Inuit in polar bear

research, monitoring, and management will continue to identify linkages between two

independent (scientific and traditional) knowledge types in co-managing potential species at risk.

175

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Conservation and Biological Senescence in Polar Bears ... · experience. I would also like to thank Kathy Shire, Guido Stadler, Amy Lathrop, Kristen Choffe, Lori Frappier, Jennifer