Conservation Genetic Implications of Microsatellite Variation in the Muskox Ovibos moschatus: the Effect of Refugial Isolation and the Arctic Ocean on Genetic Structure
Peter J. van Coeverden de Groot
A thesis submitted to the Department of Bioiogy in conformity with the requirements for the degree of Doctor of Philosophy
Queen's University Kingston, Ontario, Canada May, 2001
copyright O Peter J. van Coeverden de Groot, 2001 National Library Bibliothèque natiode of Canada du Canada Acquisitions and Acquisitions et Bibliographie Services services bibliographiques 395 Wellington Street 395, nie Wellington OttawaON KtAON4 OttawaON KiAW CaMda Canada
The author has granted a non- L'auteur a accordé une licence non exclasive licence allowing the exclusive permettant à la National Lïbrary of Canada to Bibliothèque nationale du Canada de reproduce, loan, distribute or sell reproduite, prêter, distriiuer ou copies of this thesis in microfom, vendre des copies de cette thèse sous paper or electronic formats. la forme de microfiche/nlm, de reproduction sur papier ou sur format électronique.
The author retains ownmhip of the L'auteur conserve la propriété du copyxight in this thesis. Neither the droit d'auteur qui protège cette thèse. thesis nor substantial extracts Erom it Ni la thèse ni des extraits substantiels may be printed or othefwise de ceiie-ci ne doivent être imprimés reproduced without the author's ou autrement reproduits sans son permission. autorisation. To investigate the role Arctic Ocean water gaps play in impeding genetic exchange in muskoxen Ovibos moschatus and to conduct a genetic evaluation of current conservation and management plans for these animals, microsatellite polymorphism was examined
across the range of the species. The low genetic variability in muskoxen meant that additional variable loci had to be cloned. Of 8 perfect and 9 hperfect di-nucleotide loci
studied, pe~ectloci were found to be significantly more heterozygous than imperfect loci
in this species. Thus average heterozygosity calculated from my increased sample of
microsatellite loci was substantially higher than earlier estimates.
Polymorphism at a subset of 14 microsatellite loci in 1 1 different muskox
populations sampled across the Arctic showed that in spite of their larger numbers, Arctic
Island muskoxen are much less variable than mainland conspecifics. In addition
geneaiogical analyses suggest that mainland muskoxen constitute the sister group of two
Arctic Island muskox lineages - the Northem Arctic Island (NAI) and Southem Arctic
Island (SN) lineages. Refugial isolation on Banks Island during the Last Glacial
Maximum of the Wisconsin may explain this pattern.
Regression analyses of interindividual shared allele distance and geographic
distance shows the Arctic Ocean does not consistently impede island muskoxen movement
relative to mainland muskoxen. Multiple regession analysis suggests that Arctic Ocean
watergaps generally expedite muskoxen movement in the more northem NAI muskcxen,
while Generalized Mantel Analysis indicated different waterways can either retard or expedite muskoxen movement. This reflects ice conditions or width of individual watergaps.
An evaluation of cumnt conservation practices found: 1) populations of the three major muskoxen lineages are conserved; 2) the most genetically diverse populations of
Mainland and SAI muskoxen receive some protection; and 3) conservation areas are large enough to conserve the process of natural dispersal in NA1 and mainland muskoxen but perhaps not in SA1 muskoxen. The area of positive autocomlatiun frorn the
autocorrelation of intenndividual genetic distance on geographic distance was used to
estimate dispersa1 indirectly for the latter analysis. This thesis would not have been completed without the support and love of my wife
Margaret - thank you.
Many members of the Boag lab have helped in completing this project particularly
Denise Michaud, Chad Davis, Linsey Mutch and Candace Scott. Steve Lougheed, Jim
Austen and Andrew Check made the late evening work more enjoyable.
The collection of samples was a large undertaking and in this regard Anne Gunn needs the heartiest of thanks for her expeditious charm in securing many samples. 1 would also like to thank S. Akeeagok, P. Aastmp, L. Coady, E. Coleman, M. Forchhammer, J.
Hunter, J. Kuneyuna, T. Lockhardt, R. Mulder, J. Nishi, A. Williams for assistance with sarnple collection in Canada and Greenland. My field trips were funded by gants from the Northem Students Training Program (NTSP) with substantial support from the Polar
Continental Shelf Project (PCSP) and by Peter Boag's NSERC grant. The substantial cos& of lab work was covered by Peter Boag's NSERC grant.
Queen's University funded me through a Queen's Graduate Award and a Queen's
Graduate Fellowship with additional support from Peter Boag's NSERC grant, Resources
Wildlife and Economic Development (RWED) of the Northwest Temtories and
Department of Sustainable Development in Nunavut. My parents Frans and Adrienne v. C. de Groot also helped me pursue this work.
Thanks to Peter Boag who thought these were good ideas, helped me formulate them more precisely, and let me go after them - 1could not have asked for anymore. Also thanks to Tim Birt, Chris Eckert, Dolf Harmsen and Rowland Tinline for being on my cornmittee, Table of Contents
Abstract
Achwledgements iii
Table of Contents
List of Figures viii
List of Tables
Chapter 1 GENERAL INTRODUCTION AND LITERATURE REVIEW Two Conservation Concems for Wild Ungulates The muskox - a Unique Opportunity Genetic Variability and Sarnples Muskox Hierarchical Genetic Structure From Populations to Individuals The Effect of Waterways on Genetic Exchange in Muskoxen A Genetic Evaluation of Muskoxen Conservation and Management Molecular Evolution and Genetic Distance Thesis Organisation Chapter 2
MICROSATELLITE VARIABILITY IN TEE MUSKOX OVIBOS MOSCHATUS ABSTRACT INTRODUCTION Variable Muskox Microsatellite Loci Objectives METHODS Optimizing Microsateilite Primers for Ovibos moschatus Estimating Microsatellite Polyrnorphism in Muskoxen RESULTS AND DISCUSSION Factors Affecting Variability at Microsatellite Loci in Ovibos moscha~ General Implications ACKNOWLEDGEMENTS FiGWLEGENDS Chapter 3
MICROSATELLITE VARIATION IN THE MUSKOX OWBOS MOSCtlATUS: EVIDENCE OF ISOLATION IN A LATE WISCONSIN ICE FREE GLACIAL REFUGE
ABSTRACT INTRODUCTION Late Wisconsin Ice - Free Refuges in Arctic North America Genetic differentiation in muskoxen Expectations fiom Models of Recent Muskox Diversification METHODS Sampling and DNA Extraction Microsatellite Typing Microsatellite Variability at the Sample Location Level Genealogical Relationships among Sample Locations Analysis of Muskox Lineages RESULTS Sample Location Microsatellite Diversity DISCUSSION Genetic Structure in Muskox Recent Muskox Diversification Evidence for the Diversibing Role of North American Arctic Refuges ACKNOWLEDGEMENTS FIGURE LEGENDS Chapter 4. THE ROLE OF THE ARCTIC OCEAN IN GENETIC EXCHANGE AMONG ISLAND MUSKOXEN OVIBOS MOSCHATUS: EVIDENCE FROM MICROSATELLITES
ABSTRACT INTRODUCTION Genetic Exchange and Geographic Distance Different Genetic and Geographic Distance Relationships for Different Landscapes MEXHODS Samples And Their Geography Microsatellite Loci Analyses RESULTS Simple Linear Regression Multiple Regression Generalized Mantel Analysis Accounting for Genealogical Structure in Arctic Island Muskoxen DISCUSSION Summary of Findings 94 Interindividual Genetic Distance and Varying Geographic Scale 95 Two concems: Geographic Distance and Genetic polyrnorphism 96 The Varied role of The Arctic Ocean 97 Conclusions and Implications 100 ACKNOWLEDGEMENTS 102 FIGURE LEGENDS 103
Chapter 5 USING GENETICS TO EVALUATE CONSERVATION PRACTICES FOR MUSKOXEN OVIBOS MOSCHATUS: EVIDENCE FROM MICROSATELLlTES ABSTRACT INTRODUCTION Muskox Conservation: A Unique Large Ungulate Opportunity Cumnt Conservation and Management of Endernic Muskoxen Defining the Critena for Evaluation of Conservation and Management of Muskoxen A Genetic Evaluation of Current Conservation and Management METHODS Sarnples and their Geography Molecular Methods Analyses RESULTS Comparative Variability across AI1 Muskox Relative Contribution to Diversity Spatial Autocorrelation DISCUSSION The Recent History of Muskoxen Departures from QuasiStationarity - a Measure of Short Tem Equilibrium Genetic Evaluation of Current Conservation and Management of Muskoxen ACKNOWLEDGEMENTS FIGURE LEGENDS Chapter 6 GENERAL DISCUSSION AND SIJMMARY A Test of the Banks Island Refuge A Better Test for Arctic Ocean Watergaps The Relative Contribution of Males and Femdes to Dispersal Estimates Greatest Perceived Threats to Muskoxen Populations s-ary Literature Cited
Appendices
Appendix 1: 14 Locus genotypes for 172 muskoxen. Appendix 2: Two pairwise distance matrices. Appendix 3: Individuai Assignment probabilities for 172 muskoxen Appendix 4: Assignment Matrix of 172 rnuskoxen to three major rnuskox lineages. Appendix 5: Likelihood distances between three muskox lineages.
Vita List of Figures
Figure 2-1. Map showing location of 16 of the 18 samples used in this study.
Figure 2-2. Distribution of repeat unit size for perfect repeats.
Figure 3- 1. Geographic limits of muskoxen.
Figure 3-2. Alternative muskoxen genealogies.
Figure 3-3 Consensus trees of 10 000 resampled replicates for Dm and Ds.
Figurr 3-4. Evolutionary relationships among the three muskox lineages.
Figure 4-1. Geographic limits and genealogical relationship within the muskox.
Figure 4-2. Al1 directions correlograms of rm for inter-individual DsA.
Figure 5-1. Distribution rnap of muskoxen in Canada and Greenland.
Figure 5-2. Protected and Hunting areas for muskoxen
Figure 5-3. Evolutionary relationships in extant muskoxen based on 14 microsatellites.
Figure 5-4. Contribution to allelic nchness r(g) of each sample to respective lineages.
Figure 5-5. Correlognuns of spatial autocorrelation of intenndividual genetic distance for each Iineage.
Figure 5-6. The estimated numbers of muskoxen in 19 17.
Figure 5-7. The contribution of Thelon Bone sarnples to dlelic richness in MAINLAND muskoxen,
Figure 5-8. Correlograms of MAINLAND muskoxen showing the effect of including the Thelon bone samples. List of Tables
Table 2-1. Table of muskoxen microsatellite loci optimized.
Table 2-2. Table of microsatellite loci cloned from other ungulates optimized for muskoxen.
Table 2-3a. Allele frequencies at 30 microsatellite loci across 18 muskoxen. 35
Table 2-3b. Allele lengths in base pairs of the 30 loci used in this study. 37
Table 2-4, Cornparison of heterozygosity in different classes of di-nucleotide microsatellite loci. 39
Table 3-1. Variability at 14 microsatellite loci in 169 muskoxen from 1 1 sample locations. 73
TabIe 3-2. Results of pairwise genic (allele frequency) differentiation tests across the three lineages for each locus. 74
Table 3-3. Summary of microsatellite variability in the three rnuskox lineages.
TabIe 4- 1a. The different levels of variation across 14 variable dinucleotide microsatellite in muskoxen.
Table 4-1b. Samples sizes and sample locations. 108
Table 4-2a Results of simple linear regression of DsAon geographic distance for pairs of individuals from the Arctic Islands and the mainland.
Table 4-2b. Results of simple linear regression of DsA on geographic distance for two putative Arctic Island and mainland Muskoxen.
Table 4-3a Multiple Regression of DSAon geographic distance and the presence or absence of water between Arctic Island and Greenland muskoxen.
Table 4-3b. Multiple Regression of DsA on geographic distance and the presence or absence of water in the two putative Arctic island muskox lineages - NA1 and SAI. Table 5-1. The properties of hunting areas for muskoxen in the Northwest Temtories and Nunavut Canada
Table 5-2a. The different levels of microsatellite variation across 14 variable dinucIeotide microsatellite loci in muskoxen.
Table 5-2b. Variability at 14 microsatellite loci in 158 muskoxen from 11 sample locations across their range.
Table 5-3a The contribution of each sample of muskoxen to the allelic nchness in their respective lineages for 14 microsateliite Ioci.
Table 5-3b. Contribution analysis showing the high relative contribution of bone sarnples from the ~helon~a&e Sanctuary (TH) to allelic richness of the MAINLAND Iineage.
Table 5-4. Results of spatial autocorrelation analysis for each lineage of muskoxen across 100 and 200 km scales.
Table 5-5. Evaluation of the current conservation of endemic muskoxen with respect to major subdivisions and estimated areas of positive autocorrelaiion in three different lineages (MAINLAND, Southem Arctic Island (SAI) and Northem Arctic Island (NAI)). Chupter I
GENERAL INTRODUCTION AND LITERATURE REVTEW
Two Conservation Concemfor Wild Ungulates
Long term consequences offragmentation
The rapid rate of habitat loss throughout much of the range of wild ungulates results in fragmented isolates of formerly widespread species. In planning conservation action to ensure the persistence of remnant populations, managers ideally should have empirical estimates of the long term consequences of fragmentation on ungulate ecology and evolutionary potentiai. In the absence of such data we have to rely on simulations or theory to assess the potential impact of reduced size and increa~disolation of populations resulting in erosion of genetic variation, elevated inbreeding, increased interpopulation divergence and reduced gene flow (Templeton 1990; Gilpin 199 1;
Young et ai. 1996). Empirical estimates of the long-term consequences of fragmentation are difficult to obtain, requinng a natural expenment on two sets of conspecific populations: one that has been fragmented for significant periods of time while the other is assumed to have no history of long term fragmentation.
Lack of information from undisrurbed populations of ungulates
Another result of rapid habitat change is that conservation plans for large unguiates are iikely to be reactionary - mitigating the effect of fragmentation and population size reduction - as a opposed to being pre-emptive. Conservation plans that incorporate knowledge of the properties of the undisturbed taxon stand the best chance of ensuring the long-term persistence of the species in the face of future anthropogenic habitat alteration.
The Muskox - a Unique Oppomity
The current distribution of Ovibos moschatus - a large Arctic ungulate in the sheep (Caprinae) subfamily - suggests that Arctic Island muskoxen populations are naturally Fragmented relative to animals on Mainland Canada. Muskoxen are found on many of the Arctic Islands, some separated from one another by > 60 km (Figure 2-1).
The impact of these waterways on movement of muskoxen throughout their Arctic range is unknown. However, should Arctic Ocean gaps between Arctic Island muskox populations impede genetic exchange relative to Mainland animals, this system has the potential to serve as a natural mode1 of the long term consequences of population fragmentation in ungulates.
Along with the general relevance to conservation of ungulates, the widespread distribution of muskoxen across the Canadian Arctic and Greenland provides a unique opportunity to evaluate current conservation plans for the muskoxen themselves. Three important aspects of undisturbed muskox populations cm be evaluated in a short period of time using modem molecular methods: 1) the identification of any major genetic divisions, 2) the amount and distribution of genetic divenity within those divisions, and
3) a description of ongoing microevolutionary processes such as gene flow that may be cntical to future local adaptation. A management plan that incorporates these three types of data for muskoxen populations will go a long way to ensunng long term persistence of this taxon in the face of anthropogenic range contractions.
The purpose of this thesis was determine how the Arctic Ocean affects genetic exchange in island muskoxen relative to conspecifcs on mainland Canada, and then to determine if current conservation and management practices make sense from a conservation genetic perspective. To do this 1 had to solve two major problems of doing population genetic work in muskoxen: low genetic variability in the taon and an extensive and rernote distribution making collection of sample material problematic.
The result is a story built around the variation of microsatellite marken for 172 muskoxen spread across 5 million km2 of remote northem terrain.
Genetic Variabiliry and Samples
Law genetic variabiliry in rnuskoxen
Previous studies of muskoxen suggested that this species displayed generally
low amounts of genetic variation and a complete Iack of genetic structure despite the existence of historically described subspecies (Tener 1965; Groves 1997). The low muskox genetic variation at allozyrne loci and rnitochondrial (mtDNA) meant that one of
the major objectives of my thesis was the development of microsatellite DNA markers
for the species. Microsatellites are repeated sequences of DNA interspersed throughout
the genome with high rates of mutation (Weber and Wong 1993; Tautz and Schlotterer
1994). Preliminary studies with even these rapidly evolving molecular markers in muskoxen were not encouraging, with low levels of polyrnorphism king detected at microsatellite loci optimized using PCR (polyrnerase chain reaction) pnmers from other taxa (Engel et al. 1996; Groves and Crawford unpl. data 1998). Thus 1began by developing new microsatellite loci that would have a better chance of king variable in muskoxen.
To do this 1 followed three general niles when constructing a muskoxen-specific rnicrosatellite genornic library and selecting clones for primer optimization (Chapter 2).
First, dinucleotide loci - symbolized as (CA),, where ,refers to the numbers of repeat units - are thought to have higher mutation rates than trinucleotide (CAC), and tetranucleotide (CACA), repeat loci (Jin et al. 1996; Estoup and Coumet 1999). Second, of the three types of di-nucleotide repeat motifs recognised @e@ect with an unchanging array of di-nucleotide repeats, impetfect with a few mutated bases in an otherwise
perfectly repeating array, and intempted with unique sequences interspersed in a
repeating array), peflect loci appear most variable (summarized in Estoup and Coumet
( 1999)). However, the relative rate of evolution of irnpeflect and perfect microsatellite
loci has not been quantified. Third, microsatellites that include longer repeat motifs
appear more prone to mutation (summarized in Estoup and Cournet (1999) but see Amos
(1999)). Thus in Chapter 2 of my thesis, 1 detail the optimization of perfect and
imperfect Iloc of different repeat lengths from muskoxen.
Measures of genetic va riability
In this study, 1use two measures of genetic variability: the more cornmon
unbiased estimate of expected heterozygosity H, (Nei and Roychoudhury 1974) and a
fixed mode1 genetic diveaity estimator referred to as the Probability of Identity (PD) (Paetkau et al. 1998). The former is usefd for comparative purposes, while the latter is attractive for individual based studies as PD can be used as a guide to the number of loci needed for a specifc study like mine.
Anticipating an individual-based analysis, 1required enough microsatellite loci such that each of the estimated 130 000 wild Canadian and Greenland muskoxen would have a unique genotype (Anne Gunn. pers. corn. 2001). Whereas H, does not give any guidance as to the number of loci required under this criterion, the set of loci 1required had to have a Pa,greater than 1.O E-6.
After conducting a survey of 30 different microsatellite loci in Chapter 2,1 chose
14 for the body of the thesis (Chapter 3,4,5). These 14 loci are on average equally heterozygous as the 8 perfect loci 1cloned from muskoxen (H,= 0.5 1810.034 vs. H, =
0.5 1W.045 respectively, f SE). However, those 8 pefect loci used alone would have had a PD = 1.08E-05, which translates into a maximum resolution less than the current estimate of muskoxen numbers. The addition of 6 extra loci resulted in a PD of 5.0 E-9 which means the probability of each muskox 1 surveyed having a unique genotype is
increased considerably.
Sample collection
The collection of samples involved extensive field work. 1 visited Ellesmere
Island National Park, Eureka (Ellesmere Island), Axe1 Heiberg Island, Truelove Inlet
(Devon Island), Cornwallis Island, Bathurst Island, Fort Ross (Somerset Island) and the
Thelon Game Sanctuary (See Figwe 2-1). Samples were collected in the field by
colleagues in Greenland from Hold-With-Hope, Jarneson Land, Ymer and Zackenberg.
Fresh tissue was provided by Canadian Hunter and Trapper Councils fiom the communities of Baker Lake, Cambridge Bay, Gjoa Haven, Grise Fiord, Holman,
Kugluktuk, Lutsel Ke, Resolute and Sachs Harbour (see Figure 2-1). Through these efforts 1arnassed a collection of over 350 muskox tissue samples. With the objective of having 20 animals per "population", I extracted DNA from my tissue database and attempted initial PCR amplifications with 4 microsatellite loci. Many of the samples did not readily ampli@ microsatellite DNA using PCR because of degradation of the DNA in the field. As a result I ended up with 172 samples which were eventually scored for 14 microsatellite loci.
Muskox Hiera rchical Genetic Structure
The presence of hierarchical genetic structure will confound estimates of gene flow made for populations that actually exist on different hierarchical levels from one
another. In Chapter 3 1 set about to characterize the genetic structure of muskoxen so as
to factor it into my examination of Arctic water gaps (Chapter 4). The highly variable
nature of muskox population sizes across their Arctic range suggested that a Fixed
Mode1 framework of population structure would be more easily be applied than the more
traditional Random Mode1 framework(Fems 1977; Miller et al. 1977; Miller 1988;
Miller 1989; Forchhammer and Boertmann 1993; see also Chapter 5). In Fixed models
sampling of only the current generation is important and populations are not considered
to be replicates of one another (Weir 199 1). In particular I used the recently formulated
likelihood distance (Dm ) - a fixed mode1 analogue to more traditional evolutionary
distance estimators - to estimate the genedogical relationship among muskox populations (Paetkau et al. 1997). This distance is useful for small samples of microsatellite data where population history in not known.
After describing the large scale phylogeographic patterns in muskoxen, it becarne clear that muskoxen are divided into distinct Mainland and Arctic Island lineages
(Chapter 3, Figure 3-3). The division of muskox into at least two evolutionary lineages had to be taken into account to properly estimate the effect of the Arctic Ocean on
Ovibos genetic exchange (Chapter 4). nie two important effects of muskox metapopulation dynamics
Apart from hierarchical structure, muskox population fluctuations could also confound interpretation of genetic divergence data. Simulations suggest that if populations are mortal and originate from a single source, populations diverge from each other more rapidly under dynamic metapopulation venus more stable random mode1
conditions (Slatkin 1977; Wade and McCauley 1988; Whitlock and McCauley 1990).
Also asymmetric gene flow arnong subpopulations accentuates the effect of variation in
population size, further increasing population divergence in a metapopulation (Whitlock
1992a; Whitlock 1992b). The second concem is that a metapopulation dynamic of
repeated population extinction and recolonisation can substantially reduce the genetic
variability of a species, resulting in low effective population size (N,)(Gilpin 1991).
Thus low genetic variation which might be interpreted as evidence of a histoncal
bottleneck, may actually be the result of a metapopulation with a currently high census
size which has a history of frequent local extinctions (Luikart and Comuet 1998; Luikart
et al. 1998). These two concems mean that the low genetic variation in all Ovibos and
the increased genetic divergence per km in the northem Arctic (Island) part of their range - expected if the Arctic ocean impeded muskox genetic exchange between islands - may be diEcult to interpret unambiguously. In this thesis 1argue these processes canot explain major hierarchical divisions in muskoxen (Chapter 3). but may contribute to the depressed genetic variation in the species and are likely important in departures from short term demographic equilibrium in muskoxen (Chapter 5)
From Populations to Individuals
Having assessed the higher level hierarchicai structure of muskoxen, the next step was to examine if the Arctic Ocean impeded genetic exchange relative to Mainland muskoxen. After choosing the appropriate analyticai framework, stability analyses indicated Iittle support for any population groupings other than the three major lineages
(Chapter 3). Coupled with small sample sizes, this meant 1 could execute other analyses at the individual level (Chapter 4.5). Here 1 follow an increasingly popular trend in population genetics, a move from more traditional measurement of genetic exchange arnong populations to more recent models of genetic divergence arnong individuals
(Paetkau et al. 1995; Wasser and Strobeck 1998).
1explored the effect of the Arctic Ocean as a dispersa1 barrier by regressing inter-individual genetic divergence on inter-individual geographic divergence within each of the three muskox lineages (Chapter 4). 1 then evaluated currently designated conservation areas using spatial autocorrelation analyses of interindividual genetic distance (Chapter 5). The Effect of Watemays on Genetic Erchange in Muskoxen
In Chapter 4,1 address one of the original questions of this study - does the
Arctic Ocean impede muskoxen movement among the Arctic Islands relative to the mainland? The large range of muskoxen and the limited sample sizes restricted my investigation to a series of regression analyses. I conducted simple linear and multiple regression as well as Generalized Mante1 Analyses (GMA) with the Shared Allele
Distance DSAto test for the effect of water gaps on gene flow. Since the latter andysis is not common, 1 review it here briefly. If Y equals the inter-individual shared allele distance matrix and X equals the inter-individual geographic distance matrix (in km) then the Mante1 statistic is defined as f0110~:Zux= xij(&,Yij) where zij= summation over al1 ij pain other than i = j (Mantel 1967). Since Zn< is
sensitive to sample size, and the samples sizes are not the same in each lineage, a
cornparison of this statistic for a number of distance classes across lineages is difficult.
However a cornparison across lineages of the relationship between the normalised
Mantel statistic rux and geographic distance can still be informative (Smouse et al.
1986). Not only does nomalization remove the effect of unequai sample sizes, it means
GMA is essentially a regression analysis over different scales (Smouse et al. 1986). For
meaningful cornparisons across lineages, we caiculated the normalized Mantel statistic
(rdfor distance classes in multiples of -100 km across al1 muskox combined and for
each lineage. The significance of each rm is evaluated by randomization tests. The rm
values and their significance are presented in 1 dimensional correlograms (Sokal 1986). 1chose to use GMA analysis because by panitioning the data into distance size classes the effect of animals separated by small distances can be removed from the analysis of more distantly separated pairs of muskoxen. This is a particular concern in my study where the difficulties of sampling mean that coverage is not uniform, but tends to be clumped in certain areas, e.g. near communities. A second attraction of GMA is that the unavoidably inaccurate assignment of geographic coordinates to some muskoxen may lead to inaccurate rw in the 1-100 and possibly the 10 1-200 km classes, but normally these do not affect rm estimates for subsequent classes (see Chapter 4). In traditional regression approaches the effects of having several nearby muskoxen with inaccurate location data are dificult to discount without the introduction of weighting schemes (Legendre and Fortin 1989).
A Geneiic Evaluation of Muskuxen Conservation and Management
In Chapter 5 1complete the second major objective of my thesis by evaluating
conservation and management plans using data denved from variation at microsatellite
loci. This was done by erecting three criteria against which current actions could be
evaluated. 1 asked three questions: 1) Are the major genetic divisions in this species
conserved (Chapter 3) in current conservation areas? 2) Are the most variable
populations in each of these major divisions conserved? 3) Are the opportunities for
ongoing gene flow arnong muskoxen populations conserved? The preservation of a
maximum amount of genetic divenity coupled with the oppominity to maintain these levels through normal patterns of genetic exchange are assumed to be desirable endpoints for the long-term conservation and management of al1 large mammal species.
In quantifjing which of my geographic areas contribute the most to muskox genetic diversity, 1used the contribution analysis of Petit et al. (1998). Here the contribution of variability within a population and differences between populations is calculated (Petit et al. 1998). If al1 populations sampled contribute equally to variability, then al1 areas are of equal value in the evaluation of conservation plans.
As a final part of the genetic evaluation of current muskox management. 1 estimated a correlate of dispersal distance for each lineage of muskoxen. To do this 1 conducted spatial autocorrelation of pairwise intenndividual genetic distances (Smouse and Peakall 1999). Since interindividual spatial autocorrelation analyses are relatively new 1 will describe them briefly here.
Genetic spatial autocorrelation of individuals can detect and quantify genetic structure where population based (h) methods have failed (Eppenon et al. 1999).
Autocorrelation analyses also allow one to estimate the average dispersai distance for a species - currently unquantified in muskoxen (Eppenon et ai. 1999; Hardy and
Vekemans 1999). In continuous populations, the genetic unit above the level of the individual is the neighbourhood area (4xd ), where $ is the variance in axial dispenal distance (Sokal and Wartenberg 1983). To estimate dispenal distances from the autocorrelation between genotypes, current methods require the assumption of short term equilibrium (quasi-stationarity) in the study taxon as well as evidence of isolation by distance in autocorrelation con-elograrns (Epperson et al. 1999; Hardy and Vekemans
1999). 1show in Chapter 5 that these two conditions are not met in my study. As a result, 1calculate a correlate of muskox dispersal - the area of positive autocorrelation - as a first estimate of dispersal distance in muskoxen. This is the distance at which the autocorrelation coefficient becomes zero and is correlated with the true dispersal distance (Epperson 1993a).
At the individual level there are currently five genetic statistics which can be autocomlated over geographic distance classes: Morans 1which is calculated allele by allele for each locus; Joint Count statistics calculated genotype by genotype for each
locus; Wright's coefficient of relationship pij (Hardy and Vekemans 1999); the coefficient of kinship r, (Montalva et al. 1997); and a multivariate inter-individual
genetic distance suggested by Smouse and Peakall(1999). The calculations for the first
two parametea are computationally intensive. For example, Morans 1is calculated for
each allele at a locus and an individual is scored either as 1.0.5, or O depending on
whether the genotype is homozygous, heterozygous or if the allele is absent (Peakall and
Beattie 1995; McCue et al. 1996; Miller 1998; Streiff et al. 1998; Mahy et al. 1999;
Philipp et al. 1999). Similarly. when using joint counts, standard normal deviates (SND)
for joint counts of like and unlike genotypes are scored for al1 distance classes and then
averaged across loci (Shapcott 1995; Leonardi et al. 1996; Van Staaden et al. 1996;
Reusch et al. 1999). By contrast, when cdculating the 1st three parametea a single
estimator is autocorrelated over distance classes. To remain consistent with the use of
genetic distances in my previous analyses, 1chose to use the autocorrelation of the
genetic distance of Smouse and Peakall(1999) to evaluate muskox conservation plans. Molecular Evolution and Genetic Distance
Throughout this study, 1assume that the particular model of molecular evolution at microsatellite loci is not important. Given my fixed model frarnework coupled with the recency of muskox colonisation of their Arctic range (see Chapter 3), my population analyses (Chapter 3) follow Paetkau et al. (1997) and calculate pairwise estimates of evolutionary divergence using the likelihood ratio distance Du and Nei's (1972) standard genetic distance Dsarnong 11 muskox population sarnples. Paetkau et al. (1997)
evaluated 6 measures of genetic distance for microsatellites by comparing the regressions
of genetic divergence from microsatellite data on geographic distance in brown bean
(Ursus arctos). Three of the distances, Nei's (1 972) Ds.Nei' s Minimum DM(Nei 1973),
and Nei et al.'s Improved Distance DA(1983) perform particularly well at recovenng
phylogeographic relationships under the assumption of the Infinite Allele model (IAM)
in which new mutant alleles are always different from existing ones (Kimura and Crow
1964; Nei 1972; Nei 1973 ;Nei et al. 1983 ). Two other measures, Shnver et a1.k hW
(1995) and Goldstein et da's Dm (1995). were originally formulated under a stepwise
mutation rnodel (SMM)for microsatellite evolution (Ohta and Kimura 1973). The final
measure Dm,in which the relative likelihood of complete multilocus genotypes is
cornpared for each population, makes no assumptions about molecular evolution at
microsatellite loci. Of these six measures, Dm and Dswere linearly related to
geographic distance. with R' values of 0.877 and 0.870 respectively (Paetkau et al.
1997). DLRis specifically formulated under fixed model assumptions, and is calculated from a pairwise assignment rnatrix based on the likelihood of individual genotypes
(Paetkau et al. 1995; Paetkau et d. 1997).
The choice of interindividual genetic distance estimaton is currently Iimited, and the two 1used make no assumptions about molecular evolution. In Chapter 4.1 used the
Shared Allele distance DsA. This distance has been used in studies of interindividual divergence (Bowcock et al. 1994; Goldstein et al. 1999), is conceptudly easy to understand (see Chapter 4 for formulation), and for low variability species provides an accurate estimate of relative divergence. In Chapter 5,I use the Euclidean distance of
Smouse and Peakall(1999) as this distance is an improvement on DSAfor more variable loci. It has the disadvantage of not having ken widely used.
Thesis Organisation
This thesis begins with the description of two propenies of muskox biology rhat may be relevant to the conservation of large ungulates and a discussion of various approaches to genetic analysis of a widespread species (Chapter 1). In Chapter 2 1 describe the optirnization of variable loci cloned from muskoxen. The meat of the thesis consists of three centrai sections: 1) an analysis of hierarchical structure in muskoxen
using estimates of genetic distance between pain of muskox populations (Chapter 3); 2)
an investigation of the Arctic Ocean as a barrier to muskox genetic exchange arnong
Arctic Islands using regression analysis (Chapter 4); and 3) the evaluation of current
conservation and management practices using genetic data (Chapter 5). The final section of the thesis (Chapter 6) explores avenues for extending this study, as well as discussing loorning threats to muskoxen. Chapten 2-5 are in manuscnpt form. Chapter 2
MICROSATEIUTE VARIABILITY IN THE MUSKOX OVIBOS MOSCHATUS
PETER J. VAN COEVERDEN DE GROOT'.'AND PETER BOAG' 1. Department of Biology, Queen's University, Kingston, Ontario, K7L 3N6 Canada 2. Corresponding author, email peteriiB bioloav.aueensu.co
To optimize variable microsatellite loci in the muskox Ovibos moschatus, we characterized the effect of type of microsatellite loci - perfect or imperfect - and repeat number on microsatellite polymorphism in muskoxen. We show that type of locus had a significant effect on estimates of heterozygosity in Ovibos. Perfect loci are significantly more heterozygous than impeqect loci. In contrast the number of repeat units does not significantly effect their heterozygosity in muskoxen. We also showed that perfect loci optirnized from muskoxen are significantly more variable than an assortment of di- nucleotide loci cloned from other ungulate taxa. Finally, we provide an estimate of microsatellite variation in Ovibos of H, = 0.29 1ïM.OO9 1 (SE) which includes 30 pedect and impet$ect loci from muskoxen and other ungulate taxa. Although still low, this is substantially higher than earlier H, estimates for the species INTRODUCTION
Along with limited allozyme and mtDNA variation, recent studies suggest the muskox Ovibos muschatus is charactenzed by the lowest recorded level of microsatellite polymorphism for a large ungulate (Fleischrnann 1986; Engel et al. 1996; Groves 1997;
Holm et al. 1999). In a survey of 697 base pairs of the putatively fast evolving mitochondrial D-loop from muskoxen across their 5 million km' range, only 10 nucleotide sites were polyrnorphic (Groves 1997). The lack of variation in this species is evident when 1.4% of variable D-loop sites in muskoxen is compared to that of the cow
Bos sp. where 7.0% of D-loop nucleotide sites are variable (Loftus et al. 1994). A comparative survey of 16 ungulates species across 20 Bovine, Capnnae and Ovine microsatellite loci indicated the low mtDNA polymorphism in muskoxen is complemented by a relative lack of microsatellite variation (Engel et al. 1996). The average heterozygosity of the 16 ungulate surveyed was H, = 0.362 i 0.040 (BE), whereas the 8 muskoxen surveyed had the lowest microsatellite variability of H, = 0.059
(Engel et al. 1996). Law muskox microsatellite polymorphism is aiso indicated in a more recent survey of 6 di-nucleotide loci optimized from muskoxen, where an even lower H, = 0.0 18 was recorded in a survey of 34 animals from western Greenland (Holm et al. 1999). Variable Muskox Microsatellite Loci
Although microsatellite polymorphism in muskoxen thus appean low, there are at lest two reasons why published values might underestimate microsatellite polymorphism in this species. One reason is that the estimates of microsatellite polymorphism did not include loci rnost likely to be variable in Ovibos. The microsatellite loci used in the comparative study of 16 ungulates were al1 cloned from sheep or cattle (Engel et al. 1996). Since recent data suggest microsatellite loci are likely to be more polyrnorphic in the taxon from which they were cloned when compared to their variability in other species, there is a good chance Ovibos microsatellite H, will be underestimated if only microsatellites from sheep and cattle are used (Estoup and
Cournet (1999) but see Pepin et ai. (1995)). These data suggest the fiat step in optimizing the most variable loci in muskoxen is to clone a DNA library for Ovibos.
To select clones for optirnizing variable muskox microsatellite pnmers from this
library, two general findings should be incorporated: 1) longer di-nucleotide repeats
appear more prone to mutations than shorter ones (summarized in Estoup and Cournet
(1999), but see Amos (1999)) and 2) the substantial differences in variability among
types of di-nucleotide loci. There are three basic types of di-nucleotide repeat motifs:
pegect where the motif consists of an unchanging array of di-nucleotide repeats,
imperfiecl where a mutated base is included in what is othenvise a perfectly repeating and
interrupted where the repeat amy is interspersed with stretches of unique sequence
(summarized in Estoup and Cournet (1999)). Whereas perfect have a higher mutation rate than imperjiect repeats the mutation rates of perfect and imperfect repeat loci have not been compared*
To investigate the effect of repeat type and repeat length on microsatellite variability in muskox we sequenced a large number of clones that hybridize to dinucleotide probes, calculated the distribution of repeat number in clones with perfect repeat motifs and optimized perfect and impe$iect loci that are near or longer than the median repeat length of clones with perfect repeat motifs.
The second major reason that estimates of Ovibos microsatellite polyrnorphism may
be so low is the limited geographic coverage and potential relatedness of the animals
used in these two surveys. The animals used in the Engel et al. (1996) study were from
Alaskan muskoxen kept at an experimental fmwhich were originally derived from 37
animals introduced from Eastern Greenland in 1930. Similarly the animals in the Holm
et al. (1999) snidy were from a herd on western Greenland where 27 animals were
introduced from Eastern Greenland in the 1960s. Therefore, the animals surveyed to
date are al1 from a tiny part of the 5 million km2range, may have experienced
bottlenecks during translocation and are derived from the least diverse of al1 wild
muskoxen populations (Chapter 3). A biologically meaningful estimate of microsatellite
polymorphism in naniral Ovibos moschatus populations requires samples from across
their range. Objectives
To investigate the role the Arctic Ocean plays in genetic exchange of muskoxen
(Chapter 41, we needed a set of variable microsatellite loci. Based on the two reports of low polymorphism in Ovibos (Engel et al. 1996; Holm et al. 1999), Our first objective was to optimize polymorphic microsatellites using the steps above. We optimized 8 perfect and 9 imperfect di-nucleotide rnicrosatellite loci from Ovibos and with three published muskox loci (Holm et al. 1999) determined the contribution of locus type - perfect or imperfect - and number of repeat units to the inherent variability of di- nucleotide Ovibos microsatellite loci. An increasingly common practice is to test large numben of heterospecific primers in one's study species instead of rnaking one's own
(Petit et al. 1997; Forbes and Hogg 1999; Marshall et al. 1999). To evaluate the success of such an approach in providing microsatellite primers as polymorphic as the ones we made, we surveyed variability at 9 microsatellite loci that had been cloned from Bos spp.,
Ovis spp. and Rungifer tarondus (Buchanan and Crawford 1992; Bishop et al. 1994;
HuIrne et al. 1994; Moore et al. 1994; Wilson et al. 1997).
With a total of 30 perfect and imperfect loci cloned from muskoxen and other ungulates, our second objective was to calculate a more reaiistic estimate of rnicrosatellite variability in the muskox Ovibos moschatus. Unlike previous studies, the
muskox sarnples used in al1 Our calculations covered the naturd range of muskoxen in
Canada and Greenland (see Figure 2-1). METHODS
Optirniring Microsatellite Primers for Ovibos moschatus
Lib ra ry construction
The cloning of Ovibos moschatus di-nucleotide microsatellites followed the procedure outlined in Michaud et al. (1997). Bnefiy, 10 pg of whole genornic DNA collected from 5 muskoxen in a single herd on Banks Island was simultaneously digested with Alu 1, Hae III, and Rsa 1 restriction enzymes. DNA fragments 350-450base pairs
(bp) long were selected using standard procedures (see Michaud et al. (1997)). The selected DNA fragments were blunt ended and cloned into SmaI digested PUC 18 vectors. These inserts were electrotransformed into a large number of E. coli bacteria, which were then plated ont0 LB and McConkey Amp agar plates. These libraries were probed with endlabelled yP3' poly(dA.dG).poly(dC.dT) and poly(dA.dC).poly(dG.dT) oligonucleotides. Positive clones were subjected to a second screening with the same oligos. Positive clones from the second screening were sequenced and various types of repeat motifs were scored. In addition the number of pefect di-nucleotide of different repeat lengths was calculated.
Designing and optimizing microsatelIite primers
Both perfect and imperfect clones had to have 2 80 more base pairs of unique sequence on both sides of the microsatellite to be considered for primer design. The best primen for a clone were selected for an optimum Tmof 55' C with PRIMER 3 (Whitehead Institute for Biomedical Research, http://www.genome.wi.mit.edu/c~- bin/primer/primer3.~pi).In this study, microsatellite loci were classified as impe@ect if the repeat array included mutated bases, a single inserted base, or a poly-N repeating sequence in what is othenvise a perfect repeating anay (see Table 2-1 and 2-2 for examples).
Al1 muskoxen loci were optirnized in modified touchdown PCR reactions
(Hecker and Roux 1996). The basic cycle consisted of two parts, the first being a 3 min denaturing soak at 94 OC followed by 34 cycles of a touchdown PCR. This consisted of:
30s at 94 OC, 20s at an initial annealing temperature of 65 OC with this temperature dropping by 0.5 OC in each subsequent cycle - in the default cycle the final annealing temperature is 48 OC - and 10 s at 72 OC. The touchdown PCR was followed by a second
PCR of 15 cycles of 30s at 94 OC, 20s at 50 OC, and 10 s at 72 OC. Modifications of this cycle included changing the final annealing temperature in the touchdown portion. In
these PCRs the second part of the amplification consisted of 25 cycles of 30s at 94', 20s
at final annealing temperature in the touchdown portion of the PCR,and 10 s at 72 O (see
Table 2-1). We also used 3 muskox primers designed by Holm et al. ( 1999) with their
published conditions (see Table 2-1).
Primers cloned in other ungulate taxa and optimized in muskoxen
We also amplified 9 microsatellite loci cloned from other ungulate taxa. These
samples included 6 perfect and 3 imperfect di-nucleotide repeat Bovid, Cervid and Ovine
loci (see Table 2-2). The amplfication conditions were those descnbed by the original
authors. To score allele lengths for dl optimized loci one of the pnmers was endlabelled with e3and the endlabelled PCR products were electrophoresed in polyacrylamide gels. Different alleles were scored from the resulting autoradiograph.
Estimating Microsatellite Polymorphism in Murkoxen
We calculated a comrnon estimator of variability, the expected heterozygosity
(Nei and Roychoudhury 1974) in 18 samples of muskoxen. These sarnples were from 16 locations from throughout their range and one sample each from captive herds in
Saskatchewan and Norway (see Figure 2-1). DKA was extracted from fresh tissue provided by different Hunter and Trapper Councils using standard phenol-chloroform methods (Maniatis et al. 1989). In the case of desiccated tissue flakes, DNA was extracted using standard phenol-chloroform extraction procedures, and then further purified by elution from a silica rnatrix using the QIAMP 0 Tissue Kit (QIAGEN,Inc.).
Polymorphism of microsatellites in muskoxen
We investigated the effect of locus type - perfect or imperfect - and the effect of number of repeats in the cloned allele on estimates of H, calculated from Ovibos microsatellites in an analysis of covariance. We also compared H, in 1 1 pegect muskox microsatellites with a sample of 9 microsatellite loci cloned from other ungulates using an independent sample t - test (Archie 1985). For these analyses, heterozygosity estimates for each locus across 18 animals were arcsine square root transformed (Archie
1985; Paetkau et al. 1998). Finally an estimate of genome wide microsatellite H, was estimated with 30 peflect and imperfct loci from muskoxen and other ungulate taxa RESULTS AND DISCUSSION
We sequenced a total of 107 unique positive clones: 38 sequences contained pe$ect repeating motifs with unique flanking sequences on both sides (see Figure 2-2);
16 were imperfect sequences with unique flanking sequence on both sides; 10 consisted of single nucleotide repeats; 14 had inserts with perfect mysof 1 4 repeating units, and in the remainder the complete repeating motif was not included in the insert. The median length of perfect repeats was 20, with the longest being 28 and shortest being 12
(see Figure 2-2). Using the median length as a guide, we optimized 8 loci containing perfect repeats of 2 18 repeat units and 9 imperfect loci from this library (Table 2-1).
Factors Affecting Variability at Microsatellite Loci in Ovibos moschatus
Initially with ail 20 muskox loci the type of locus - perfect or imperfect - and median number of repeat units in the cloned allele were significant effects in a multiple regression on &: P 5 0.0001 and P = 0.0007 respectively. However the significance of the number of repeat units depended on a single locus OM53-12,suggesting this datum was an outlier. With the exclusion of this locus, the type of locus still contributed significantly to H, while the median nurnber of repeat units in the cloned allele was not significant: P 5 0.000 1 and P = 0.1 16 1 respectively. From this initial survey, genetic variability at the perfect loci was: H, = 0.5035 f 0.0450 (k SE) ,the mean number of alleles = 3.8H.5, maximum = 6, and minimum = 2 (Table 2-3a,b & 4). Genetic variability at the imperfect loci wax H, = 0.0672 t 0.0553, the mean number of alleles =
24 1.2 f 0.1 ,maximum = 2 and minimum = 1 (Table 2-3a,b & 4). As expected these H, estimates are significantly different (unequal sarnple size t test, t= 6.908, df =l5, PC
0.00 1).
It must be recalled that only one microsatellite with a repeat number substantially less than the median of 20 (Figure 2-2) was used in our calculations - MX1 with TGi3.
The absence of data from loci with smaller repeat unit numben and the possibility of a more complex relationship - than our simple linear mode1 - operating across the spectrum of repeat number, means our conclusion of no relationship among di- nucleotide repeat number and H, cannot be extended across the full range of di- nucleotide repeat numbers in muskoxen (see Amos (1999); Estoup and Coumet (1999) for a recent discussion of the relationship between repeat number and variability).
The 11 perfect loci cloned from muskoxen were more variable than the 9 loci
cloned from other ungulates (t test unequal samples, t= 2.4 16. df =15, Pc0.05). From
this initial survey, genetic variability at the 9 loci from other ungulates was: H, = 0.2896
+ 0.0323, with a mean number of alLeles = 2.4N.6, maximum = 6, and minimum = 1
(Table 2-3a,b & 4). However loci from a coIlection of other ungulates was more
variable in muskoxen than the imperfect loci cloned from muskoxen (t test equal
sarnples, t= 2.242, df =16, Pcû.05).
An estimate of microsatellite variability in muskoxen
A more realistic estimate of microsatellite variability in Ovibos moschatur is
thus H, = 0.292 f 0.009. This estimate includes microsatellite loci that are more likely to
be variable in muskoxen - 11 pefect muskox loci [we include the 3 loci from Holm et al
1999 in this groupl- and loci less likeIy to be variable in muskoxen. The latter includes
25 9 imperfect muskox loci, locus 52-32 and the 9 loci - perfct and imperfect - cloned from other ungulate taxa (See table 2-1,2-4).
General Implications
Comparing the three factors (type of locus, number of repeats in cloned allele and the taxonomic ongin of a locus) our data suggest that type of locus -whether aperfect or impegect di-nucleotide repeat array - is the major determinant of microsatellite variability in muskoxen. Although Our data are preliminary, they also suggest a collection of microsatellites from other ungulate taxa are likely to be less variable than peflect loci cloned from muskoxen. Pol ymorphism in one species is not an ironclad predictor of polymorphism in another (see locus MCM58 and RT30 in Table 2-2 and
Groves and Crawford unpublished 1998). One reason for this may be the mutation of the
repeat array from perfect to imperfect or intempted in heterospecific ungulates. Pepin
et al. (1995) found perfect di-nucleotide repeats from cattle mutated to interrupted
repeats in goats. Similarly, perfect di-nucleotide repeats from goats mutated to
intermpted repeats in sheep. As expected, once the locus contained an interrupted
repeat array, variability decreased (Pepin et al. 1995). Another reason may be the smaller
number of repeat units in heterospecific amplifications (Estoup and Coumet (1999) but
see below). Only through cloning a muskox library could we ensure the microsatellite
contained a perfect array of median or longer length. Lastly, arnong the three, number of
repeats in the cloned ailele appears the least important predictor of variability in
microsatellites with the median or greater aumber of repeat units. The extrapolation of this to al1 dele repeat numbers cm be questioned, but our data suggest that loci of median or near median repeat length are just as likely to be variable as loci with longer repeat lengths.
Our nsults suggest specific steps to be taken when optimizing microsatellite loci for a species with particular goals in mind. If the goal is parentage assignment, optirnization of variable loci using consepecific or heterospecific microsatellites should proceed on a species by species basis until some cnterion is satisfied. For example. enough loci with sufficient variability are isolated to completely exclude non-parents or at least assure high LOD scores to true parents (Marshall et al. 1999). On the other hand if estimates of genetic distance between populations or individuals are the goal, the minimum number of loci with a Probability of Identity PD as low or less than the census size of the population rnay be the goal (Paetkau et al. 1998). In both cases, a random collection of variable consepecific or heterospecific microsatellite loci may suffice.
However, if maximizing the variability in the sample of loci is essential, pe~ectdi- nucleotide rnicrosatellites cloned from the study taon using our approach will give the best chance of reaching the study goals.
Despite the profusion of rnicrosatellites studies, the many different approaches to selecting and optimizing loci means one can seldom make meaningful genome wide comparisons among published microsatellite variability estimates for different taxa.
Along with the usual variability estimates and descriptions of repeat sequences at polymorphic loci, the repeat sequence of al1 optimized monomorphic loci should be made available. As a final complement to these calculations the origin of the study samples and census size of the study species should also be reported. Finally, as a result of this study we selected 14 variable di-nucleotide loti - 10 peflect loci from muskoxen and 4 perfect loci from other ungulates - to investigate the effect of late Pleistocene refugial isolation (Chapter 3) and Arctic Ocean isolation
(Chapter 4) on gerietic divergence in Ovibos. Of the 17 variable loci in our study, these
14 provided a relatively high estimate of H, = 0.5 179 f 0.0394 for perfect loci .
Although the 8 pe@ect ioci cloned in this snidy had a marginally higher H, of 0.5193 I
0.0496, their combined PD= 1.O8 X 105 was much less powerful than that of the above
14 loci where PD = 5.00 X 10~'. This is due to the distribution of alleles, and with Our preferred set of 14 loci, the likelihood of each the of - 130 000 muskoxen having a unique genotype is increased. Our thanks to Denise Michaud who provided invaluable assistance and guidance in cloning muskox microsatellites. Chad Davis and Linsey Mutch provided assistance with primer optimization. Lars Erkk Holm provided us with sequences of his primers before they were published. We would like to thank Knoed Roed for muskox samples from Norway and for assistance in optimizing cattle and sheep primers. Similarly we thank James Kushny and Curtis Strobeck for assistance in optimizing caribou microsatellites on muskoxen. We thank Anne Gunn and Peter Aastrup for expediting the collection of samples from the Canadian Arctic and Greenland respectively. The moleculas work was funded by grants to PTB from NSERC and the field work was funded by grants to PJvCdG from Polar Continental Shelf Project (PCSP) Canada
FIGURE LEGENDS
Figure 2-1. Map showing location of 16 of the 18 samples used in this study. Not shown are the two samples from captive herds in Saskatchewan and Norway. The Saskatchewan animals originated near Kidjuut Lake (KL) and the Norway animals frorn Eastern Greenland. The animals used to clone the library are from Banks Island, collected near the community of Sachs Harbour (SH). Included are the current distribution limits of two subspecies of muskoxen, the white faced muskox Ovibos moschatus wardi and the barren ground muskox Ovibos moschatus moschatus. Also show are census sizes of Canadian Arctic Island, Greenland and Mainland muskoxen (Gunn and Fournier unpublished data 1998 ). AI = Axe1 Heiberg Island, BI = Bathurst Island, BL = Community of Baker Lake, DI = Devon Island, EI = Ellesmere Island National Park, EU = Eureka, GF = Comrnunity of Grise Fiord, GH = Community of Gjoa Haven, JA = Jameson Land, KU = Community of Kugluktuk, KL = Kidjuut Lake, LK = Community of Lutsel Ke, TH = Thelon Garne Sanctuary, WB = Community of Wellington Bay, ZA = Zackenberg.
Figure 2-2. Distribution of repeat unit size for perfect repeats for a dinucleotide library cloned fiom 5 unrelated male muskoxen from Banks Island. The cloned library was probed with poly(dA.dG).poly(dC.dT) and poly(dA.dC).poly(dG.dT). There were no repeat motifs between the size of 4 and 11 so only those with 1 1 repeat units or more are show and the median number of repeats was 20 for the 38 clones (see text for details). -
GREENLAND
LK NWT & NUNAVUT
[f White faced rnuskox Barrenground muskox
Figure 2-1 Frequency distribution of 38 perfect repeats in a di-nucleotide Library of the muskox Ovibos moschatus
10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 18 t9 30
Repeat size of clones
Figure 2-2
Table 2- 1 conrd,
Locus T Repeat motif Left Primer Right Pd mer # He Cycle
(AG)~(TG)I~ gta att caa atc ctt ggg riat ri agt gaa ttt tcc agt gag aga c (GT)~CT(WBAT(GT)~ tat trit cat cca ctg acc ctt c gca gac ata acc aag aga ctü 8 (CA)2GA(CA)2TA(CA)3CG(CA)i art tca gaa gtc ctc caa gtc att gtt tta atc gct ttc agt t (TG)&A(TG) ioTC(TGI2 atc aag aga aag aaa tct gag g mg gat aaa tca tat ctg cct g (AC)dAT)dAC) 14 tgg aga aria gac aca tgt aaa a cgt aaa tac tct cag tgc ctg t (TG)5TC(TG)8TCACA(TG)4 gin tcc tgt gat ang ccg tan t ggt gaa gaa tct gtt tac cag t TACA(TA)3(CA)IiCGTGCG(CA)i2 cca gag atg gtc cat cgt tta g ggt tac cat ttt cta ttc cari a (GT)16(TATG)2TGTCTGN66(GT)I,gaa ggg aga cnt gat tag ttg t gac agg tat tct aga acc agg ii
- - - p. ------p. ------' = Loci from Holm et al. (1999). * =Technically an ititerricpted microsatellite with two invariant products amplified by these primers, = This wns the only muskox locus thnt did not amplify with a touchdown PCR;in this case the cycle was 3 min at 94'~~34 cycles of 30s nt 94'~,20s at 55'~~and 10 s ai 72'~. Table 2-2,
Table of microsatellite loci cloned from other ungulates optimized for muskoxen in this study. Type refers to nature of the di- nucleotide repeat in the cloned allele where P = pegect repeat motif which contains no mutated bases or interruptions and I = itnperfct repeating motif where the repeating array is interrupted by a single inserted base or a poly-N sequence. or one or more bases have mutated. # Alleles = the tiumber of microsatellite alleles detected in the original publications. H, = average unbiased estimate of heterozygosity in 18 muskox samples (Nei and Roychoudhuty 1974). Spccies = the species from which the microsatellites were originally cloned. The primer sequences and PCR conditions can be found in the original publication.
-- -- - Locus Type Repeat motif # Alleles H, Species
sheep' sheep2 cari bou3 cari bou3 caribou' cari bou3 COW~ COW~ COW~
' = Buchanan and Crawford (1992), = Hulme et al. (1994), ' = Wilson et PI. (1997). = Moore et al. (1994), "BBhop et al. (1994). Table 2-3a,
Allele frequencies nt 30 microsatellite loci across ~he18 muskoxen in this study. The maximum number of alleles for any locus in this study is 6 whereas the maximum number of alleles for a locus in our larger study of muskoxen was 9 (Chapter 3 and see Table 3-2b). This maximum is indicated by the showing an 1 allele in the table. Allele sizes are shown in Table 3-3b.
Locus
Table 2-3b,
Allcle lengths in base pairs of the 30 loci used in the study of Ovibos »ioscli(rrusmicrosatellite polymorphism. The alleles include dl those found in this study and in a funher study of microsatellite polymorphism with a set of 14 of these loci (Chnpier 3). Monomorphisrn at a locus is indicated by a single allele length and the grentest number of alleles per locus was 9 found in BM 1225. Most of these alleles were found in this study, with n maximum of 3 being discovered when anothet 15 1 rnuskoxen were genotyped (Chapter 3). New alleles typed only in the broader study oppear in brackets under the locus name. Table 2-3b contd.
Locus
MAWO MCM58 CSSM 002 CSSM 003 RT-6 (D,E) (8,F) Table 2-4.
Cornparison of heterozygosity in different classes of di-nucleotide microsatellite loci across 18 muskoxen from throughout theit range (Nei and Roychoudhury 1974). Heterozygosity was higher in perfcct di-nucleotide loci relative to imper$ect loci cloned from muskoxen and relative to 9 microsatellite loci cloned from other ungulates. PcrJecf and irnpetfect loci are defined in the tex t. Otlier roigitlutes refers to a group of diverse di-nucleotide loci from caribou, cattle and slieep that amplify in muskoxen (sec text for details). Al1 includes al1 30 loci used in this study. N=the number of microsatellite loci in the class, He = unbiased estimate of expected heterozygosity and includes the standard error (I SE) (Nei and Roychoudhury 1974).
- Class of microsatellite loci
Perfec t Imperfect Other Al1 ungulates Chapter 3
MICROSATELLDE VARIATION IN THE MUSKOX OVIBOS MOSCHATUS: EVIDENCE OF ISOLATION IN A LATE WISCONSIN ICE FREE GLACIAL REFUGE
PETER J. VAN COEVERDEN DE GROOT'~AND PETER BOAG '
1. Depariment of Biology, Queen's Universi& Kingston, Ontario, K7L 3N6 Canada 2. Corresponding author, email peteri@biolom. weensr<.cn
We report polymorphism at 14 variable microsatellite loci in 172 muskoxen Ovibos moschatus from the Canadian Arctic and Greenland. The generally low genetic variation in this species is unequally distributed across its range with our data suggesting 3 lineages of muskoxen. Mainland, Southem Arctic Island (SAI) and Northem Arctic Island (NAI) muskoxen lineages are supported by stability analyses of the likelihood distance Dm and painvise tests of allele frequency homogeneity. Mainland muskoxen display almost double the heterozygosity of the two Arctic Island lineages (H,= 0.535, SE = 0.068 (versus H, = 0.247, SE = 0.028 in the SAI lineage, & = 0.294, SE = 0.049 in the NA1 lineage). These data are consistent with the isolation of Arctic Island muskoxen in an ice-free glacial refuge during the Last Glacial Maximum (LGM) of the Wisconsin Glaciation. The divergence of the two island forms occurred after the withdrawal of the Innuitian Ice Sheet sorne 10 000 yem before present. These findings suppoa recent work ascribing a divenifjhg role to the Ice free refuge on Banks Island that persisted through the last 700 000 yean of the ~leistocene. INTRODUCTION
Pleistocene refugia are thought to have played a major role in generating biodiversity in many geographic areas (Haffer 1969; Holder et al. 1999). Repeated cycles of habitat expansion and contraction, occumng every 100 000 years with each glacial-interglacial cycle (GIC),may have served as a biodiveaity pump (Pielou 199 1).
The nature of refugia and their surroundings differ depending on latitude. In Neotropical
Central and South American Iowlands, mesic refuges existed in largely xerk environments durhg glacial maxima while at the sarne time in northem latitudes ice-free tundra refuges are thought to have persisted in a sea of glacial ice. Convincing evidence for the diversiQing role of this process cornes from: a) vicariant biogeography as evidenced by congruent genealogicai patterns among similarly distributed unrelated taxa
(Lynch 1988), and b) estimates of times of divergence that are concordant with the existence of refugia (Morrone and Crisci, 1995).
The muskox Ovibos rnoschatus is a large Arctic ungulate naturally distributed through the Canadian Arctic and Greenland whose current geographic diveaity may nfiect Wisconsin refugia. Two putative subspecies have been recognized. the barren ground muskox, Ovibos moschatus moschatus, and the white faced muskox Ovibos rnoschattis wardi based on subtle physical differences and distribution (summarized in
RowelI(1990)). Although the width of the contact zone between these two groups is unknown, mainland O. nt mosclzatus are not generally found on the Arctic islands nor are 0. nz. wardi found on the mainland (see Figure 3-1). The limited morphological differentiation between the two subspecies has led some to conclude they may have diverged from each other recently, during the Wisconsin glaciation (Harrington 1961).
Proving specific refugial links for present day taxa has been controversial (Endler
1982), with dificulties depending on latitude and topography. For example, evidence of refugial origin for lowland Neotropicai South Amencan biodiversity has been complicated by: a) lack of independent estimates of refuge location; b) confounding distribution patterns of many organisms - originally used to delimit refugia - over very large areas; and c) possible post divergence dispenal and hybridization (Endler 1982).
Also refugia in these areas are thought to have changed position with each successive glaciation. On the other hand tests of a general mode1 of Pleistocene refuge origin for montane Neotropicd taxa appear easier as the montane refuges did not move dunng the
Pleistocene; orogenesis was largely completed in Central Amenca by the Pliocene.
Recent work suggests these montane refuges played a significant role in generating smail
mmalbiodiversity in this region (Van Coeverden de Groot 1995). Links to a specific
glacial-interglacial cycle (GIC), however, may be problematic as expectations for the
diversifying role of a specific GIC cm be difficult to distinguish from the roles of
different but chronologically close GIC's. Discriminating among successive cycles
requires accurate estimates of evolutionary divergence times among the study taxa
(Monone and Crisci 1995). The increased resolution of genetic markea such as
microsatellite DNA suggests one may be able to identify a single GIC origin within the
Pleistocene.
The generally accepted existence of an ice-free refugium on Banks Island in North
America dunng the Last Glacial Maximum (LGM)of the recent Wisconsin Glaciation (24 000 to 10 000 y.b.p.) suggests a study of muskox microsatellite variation may provide a definitive test of the diversQing role of LGM ice-refuges in Arctic biota
(Hughes 1998). The current muskox distribution encompasses large portions of the
North American Arctic and much of ice-fiee Greenland, and includes the ice-free refuge
on Banks Island and other possible ice-free LGM refugia (see Figure 3-1). Preliminary
suggestions of lirnited genetic divergence between the two subspecies suggests a recent,
possibly Pleistocene ongin (summarized in Groves 1997). Estimation of genealogical
relationships among recently diverged muskox using microsatellite DNA markers may
be informative as such markers are likely to be neutral with respect to environmental
gradients across the muskox range and have a rapid rate of evolution (Endler 1977;
Endler 1982).
Lote Wisconsin Ice - Free Refuges in Arctic North America
Although ice-free refuges probably changed position with successive glaciations,
most of Banks Island has been ice free during the last 700 000 years of the Pleistocene
(evidence for the Illinoian, Sangamonian and Wisconsin Glaciations summarized in
Hughes (1998), see also Figure 2 in Vincent (1984)). During the LGM,this refuge
penisted for at least 18 000 years, with passage to the mainland and other Arctic Islands
impeded by ice sheets on surrounding islands, ice shelves on the surrounding ocean and
later by the Arctic Ocean. AIthough this refuge was physically separated from the
mainland by ice for the duration of the Late Wisconsin maximum at other times it was
separated ftom the mainland by approximately 200 km of Arctic Ocean. A second late Wisconsin refuge on the Arctic islands of Noah America may have existed on parts of the Rignes Islands, northem Ellesmere Island and or part of
Gnenland (J. Engiand pers. comm. 1999). Support for such a refuge is less certain and is closely related to the debate on the extent of ice cover on the Queen Elizabeth Islands during the late Wisconsin LGM (Mayewski et al. 198 1; Zreda et al. 1999). These Arctic islands were either covered by an extensive Innuitian ice sheet (Blake 1970 in Mayewski et al. (1981); Zreda et al. 1999) or by a more iimited Franklin Ice Cornplex (England
1976 in Zreda et al. (1999)). A large High Arctic refuge is more consistent with the latter.
Genetic Differentiation in Muskoxen
The lack of variation in the control region of mitochondrial (mt) DNA across the two muskoxen subspecies suggests either that the morphological differences are environmentally induced or the subspecies diverged very recently (Groves 1997). Mt
DNA displacement @) loop and cytochrome B sequences are almost invariant from
Greenland through to Alaska in muskoxen; for example only 10 sites out of 697 bp of D loop sequence varied in 37 muskox across their range (Groves and Shields 1996; Groves
1997). These sampIes included animals from Alaska (which originally were transplanted from Greenland), Western Greeniand and from 5 different Canadian locations. The inclusion of animals from the extremes of their range - Mainland Canada and Greenland animais - coupled with the relatively rapid rate of rnitochondrial D-Ioop sequence substitution suggest that further mtDNA analysis is unlikely to reveal genetic differences at the population level (Pesole et al. 1999). On the other hand microsatellite DNA, with different transmission properties, faster rates of evolution than mtDNA and putative selective neutrality may recover recent muskox genealogies and allow tests of refugial divergence (Bowcock et al. 1994; Goldstein et al. 1995a; Slatkin 1995; Paetkau et al.
1.997).
Eipectations from ModeLr of Recent Muskox Diversijfcation
If some muskoxen were isolated in Late Wisconsin ice free refugia, this history
should result in specific patterns of genetic divenity. As a first expectation, genealogical
relationships must be congruent with glaciation-deglaciation patterns dunng and after the
Wisconsin LGM. Altemate sequences of glacial refuge isolation, should result in a
different set of relationships arnong muskox refuge descendants. Three of these
alternatives are illustrated in Figure 3-2, where for illustrative purposes we hypothesize
muskoxen being isolated in both of the Arctic Island refuges detailed above. Since
Wisconsin glaciation precipitated differentiation, a second expectation is that sister taxa
should be separated by small genetic "distances". Differentiation during the late
Wisconsin will result in estimates of isolation < %O00 y.b.p. Taxa recently isolated in
glacial refugia for - 18 000 years should have lower levels of genetic variability
cornpared to sister taxa not isolated in refugia. This leads to the expectation of different
ievels of genetic variability when comparing those taxa whose ancestors were isolated in
small ice-free refugia for long periods of time with those that were not. This is in
contnst to the results arising from the incarcention of al1 ancestral taxa in different small reiùgia for similar lengths of time. In this case dl descendant taxa should have low but different levels of variability. Finally, after an extensive period of allopatric divergence in one (or more) Pleistocene refugia these ancestors would have dispened to contact zones with the withdrawal of the Laurentide Ice sheet, leading to the fourth expectation that contact zones among refugial descendants will be secondary. Data from a microsatellite survey in muskoxen that satisfies these expectations is good evidence for the importance of Late Wisconsin Ice Free refuges in generating extant muskoxen diversity.
Refugial isolation is not the only mechanism that may have shaped the genetic structure of muskoxen recently. Two others are divergence along environmental clines and divergence as a result of extreme fluctuations in population size. Substantial clines in environmental variables exist in different parts of the muskox range (Edland and Alt
1989; Forchhammer and Boertmann 1993; Everett and Fitzhams 1998). Even in the face of gene flow it is possible for taxa subjected to different evolutionary pressures to evolve independently (Endler 1977). This mode of divergence leads to ai least two expectations that are distinct from those of refugial divergence. First, clinal differentiation will necessarily result in more recent muskoxen divergence following the
Holocene withdrawal of the large ice sheets that covered much of the muskox range.
Second, divergence along clines will mean that parapatric muskox will share a primary contact zone. As a result populations that straddle a contact zone will be each others closest relatives. In contrast, contacting populations derived fiom different refugial ancestors will not be each others closest relatives. It is dso possible that muskox genetic structure will reflect a species that has highiy temporally and spatially variable densities across it's range. Although information from the entire muskox range does not exist, Forchharnmer and Boertmann
(1993) have recorded Greenland muskox population densities that have changed by as much as 50% in only two years. Similarly, Fournier and Gunn (1998) provide evidence of extremely variable population sizes at Canadian locations within the recent pst. It is possible that in the longer term, muskoxen across the range are characterized by a history of extinction-recolonisation episodes. Both fluctuating yet persistent populations and a metapopulation with a repeated extinction-recolonisation dynamic promote a loss of heterozygosity within and divergence among populations when compared to a collection of populations with more stable dynamics (Barton and Whitiock 1997). These expectations are similar to the product of recent refuge isolation. Thus one must gather additional evidence to prove muskox refugial isolation; depressed genetic variability relative to non-rehigial populations is not enough.
We examined variation at 14 microsatellite loci in 172 muskox from throughout their Arctic range of 5 million square kilometen. Our data indicate that diagnostic genealogical relationships, limited genetic divergence and differences in genetic variability within muskoxen support isolation of Arctic Island muskox in a Wisconsin ice-free rehige on Banks Island. Our data aiso support post-glacial dïerentiation of
Arctic muskox into two lineages &ter the withdrawal of the Ice from the Queen
Elizabeth Islands - approximately 10 000 y.b.p. These data support an increasing number of recent studies that point to a major diversifying role in Arctic taxa of an ice- free Banks Island at LGM during the Wisconsin (Holder et ai. 1999; Tremblay and
Schoen 1999; Ehnch et al. 2000; Nagy et al. 2000)
Sampling and DNA Extraction
172 muskoxen compnsing 169 animals from 11 locations and 3 additional individuals not easily assigned to these 11 locations were used in this study (see Figure
3-1 and Table 3-1). Fresh skin and or muscle from harvested muskoxen were collected through Hunter and Trapper councils from the cornmunities of Baker Lake, Holman,
Sachs Harbour, Cambridge Bay, Kugluktuk, Lutsel Ke, Gjoa Haven and Grise Fiord
(N=135). Samples from Greenland, the Arctic Islands including Axe! Heiberg, Bathurst,
Cornwallis, Devon, Prince of Wales and Sornerset Islands, as well as Ellesmere Island
National Park Reserve and the Thelon Game Sanctuary consisted of tissue flakes collected from carcasses of animals long or recentfy deceased (N=37).
DNA was extracted from hunter collected samples using standard phenol- chloroform procedures (Maniatis et al. 1989).DNA from the desiccated tissue flakes was extracted using standard phenolchloroform extraction procedures, and then further purified by elution from a silica mauix using the QIAMP 0 Tissue Kit (QIAGEN,Inc.). MicrosatelfiteTyping
The optimization of the 14 variable dinucleotide microsatellite loci used in this study has been described elsewhere (Chapter 2). Ten loci were cloned from muskoxen including MX- 1, MX-2 and MX-5(Holm et al. 1999); OM50-08,OMS 1 - 16,OM51 - 19,
OM 53-38,OM54-23,OM55-04 and OM56-30 (Chapter 2) two (RT-6and RT-9) from the Caribou Rangfer tarandus (Wilson et al. 1997), one (BM 1225) from the cow Bos sp. (Bishop et ai. 1994) and one (MM-70) ftom sheep Ovis sp. (Buchanan and Crawford
1992). The primer sequences and amplification conditions for the OM loci are descnbed in Chapter 2. Variation of microsatellite repeat length at these 14 loci was assayed for ail 172 muskoxen tissue sarnples.
Microsatellite Variability at the Sample Location Level
For correct estimates of variability and geneaiogical relationships within muskoxen populations, ail loci mut be in linkage equilibrium. We tested for linkage disequilibrium for each pair of loci in each sample using probability or exact tests.
These results were combined across ail samples. Disequilibriurn calculations were completed using GENEPOP v. 3.1 d (Raymond and Rousset 1997).
We used two measures to describe microsatellite variation in muskoxen. For each sample location we caiculated an unbiased estimate of expected heterozygosity (Nei and Roychoudhury 1974). A second measure of variability, the Probability of Identity
PD, was calculated for each locus and across al1 loci for each sample location. This measure of calculating the probability that two randomly drawn individuals will share a genotype by chance is given by the formula:
3 2 2 n (2a2 - Q) - 2n (a3 + Saz) + n(9a2 + 2) - 6 P, = (n-1 )(n-2)(n-3)
where n is the sarnple size ,ai equals
and pj is the frequency of the jth allele (Paetkau et al. 1998). A low Pa,indicates that individuals are genotypically very different. These calculations were made using the heterozygosity caiculator at htt~://~ause.biolog~.ualbertaca/ibrzusto/JEANS .html
Genealogical Relationships among Sumple Locations
To determine genealogical relationships within rnuskoxen. we constmcted unrooted networks from microsatellite ailele frequency data for 169 muskoxen at I 1 sarnple locations. Pairwise distance estimates among the sample locations were calculated using 1) Nei's Standard Ds (Nei 1972) which perfonns well under the assumption of the Infinite Allele Mode1 ([AM) (Nei et al. 1983 ). and 2) Paetkau et al.>
(1997) likelihood distance Dm which makes no assumptions of niolecular evolution at microsatellite loci. In an evaiuation of 6 distance measures applied to intraspecific microsatellite divergence in the continuously distributed Arctic Brown Bear Ursus
Arctos, Ds and Du had lower variances than Nei's Minimum DM (Nei 1973 in Takezaki and Nei (1996)), Shriver et d.'s (1995) Dsw, Goldstein et d.'s (1995a) DmpdNei et al.'s
(1983) Improved Distance DA.These results suggest that intraspecific genealogical relationships across 0.moschatus which have similar wide distributions are best estimated with Ds and DLR.Distance matrixes and Neighbor Joining trees were constructed from the microsatellite data using a calculator at htt~://~ause.biolo~y~~alberta.ca/ibrzusto/E~S.ht~.
Critical to the evaluation of altemate muskox divergence models is support for the branching patterns in the microsatellite topologies. We conducted a stability analysis of the Neighbor Joining trees for Ds and Dm by exarnining the branching patterns of
1ûOdatasets created by resampling loci with replacement across al1 individuds. If a particular branch had arisen due to differences between taxa at one or a few loci, then that branch would have weak bootstrap support. Ds and Dm were calculated for each replicate and those branches that appeared in 758 or more of the replicates are most likely supported by the data. Resampled replicates for both Dsand Dm were computed Analysis of Muskox Lineages
Definition of major muskox lineages
An examination of refùgid divergence hypotheses requires the delineation of potential descendants of muskox refugial isolates. As a fint step we determine the major genedogical subdivisions from Our 11 muskox sample locations and hypothesize three muskox lineages. To better estimate evolutionary divergence and the genetic properties of the muskox lineages we used the Assignment test of Paetkau and Strobeck (1995) to assign al1 172 individual muskoxen to one of the three major lineages (assignment calculator at http://~ause.biolo9y.ualberta.ca/ibrzusto/S- - .html).
As an alternative to topologies based on evolutionary distance, we estimate divergence among the 3 lineages using pairwise tests of allele frequency differences across al1 loci (Goudet et al. 1996). We specifically test the hypothesis that allele distributions are equal across operational taxonomie units (OTU's). The acceptance of this test across al1 loci across groups indicates that OTU's should be combined and the rejection of this hypothesis across all loci indicates that OTU's have a unique history.
With recently diverged taxa, it is likely that some but not all loci may have identical distributions. With our 14 loci, we may be able io discriminate among differentiation events in recently diverged taxa. Specifically, those pain with the most similar allele distributions diverged most recently. Genetic divergence among muskox lineages
We estimated genetic divergence arnong the three lineages by 1) constmcting a topology of genealogical relations among lineages, 2) estimating their relative times of divergence and 3) comparing microsatellite genetic vuiability.
Topological relationships: - The location and potentially different times of creation of LGM glacial rehigia make different predictions of topological relationships among descendant muskox lineages (See Figure 5-2).
Relative time of divergence: - An estimate of the recency of divergence among the muskox taxa is critical to the test of refugial isolation in muskox. Late Wisconsin divergence predicts that muskox populations split between 10 and 70 000 y.b.p. In contrast should muskox have diverged more recently as a result of environmental clines that exist across the Arctic, divergence within muskox should be more recent. We used relative genetic distance estimates arnong muskox lineages to evaluate alternate divergence hypotheses.
Genetic variability: - In contrast to refugial models where ancestors to al1 extant muskox were isolated in different ice free rehigia, the isolation of some but not al1 anceston to extant muskox lineages in small ice free refugia will result in very different levels of heterozygosity among descendants. Specifically we will expect to see relatively depressed levels of genetic variation among refugial descendants venus those whose ancestors were not isolated in glacial refuges. We estimated genetic variability in the thelineages using Pm and heterozygosity. Sumple Location Microsatellite Diversity
Genetic variubilip
The 14 locus genotypes for 172 muskoxen are shown in Appendix 1. These loci are in linkage equilibrium across the Il samples. Of the 9 1 paiwise cornparisons of
14 loci across al1 populations only two were significant at a= 0.05. The microsatellite data suggested that loci RT-6and MX-02 were linked as were MAI30 and MX54-23 (X2
= 32.157, df = 20, a = 0.042; X2 = 27.55 1, df = 14, a= 0.0 16 ). However, this number of significant tests is no higher than expected due to Type 1 error of 5% if the nul1 hypothesis (no linkage disequilibrium) was tme. We assume for further analyses that al1
Ioci are al1 unlinked.
The extension of these 14 variable microsatellites from an initial survey of 18 muskoxen from across the range revealed a taon with geographically heterogeneous microsatellite divenity (Chapter 2). The unbiased estimate of heterozygosity at these 14 loci from this initial sample was H, = 0.5 18 t 0.039 (BE)with a PD = 5.00 10" (n= L 8).
In this broader study heterozygosity varies from a high of He= 0.5 12 f 0.01 8 at the rnainland location Baker Lake, to a low of H. = 0.169 f 0.077 for samples from
Greenland. Similady, PD estirnates vary from a high of 2.5 X IO-' at the mainland location of Baker Lake and Lutsel Ke' to r low of 2.8 X 10" at Kidjuut Lake on Victoria
Island - û. difference of 5 orders of magnitude (see Table 3-1). The microsatellite variability data indicate that mainland muskoxen are mon variable than Arctic island muskoxen. The average heterozygosity and PD for the 4
7 mainland locations were He = 0.498 and 1.25 X 10' . This group includes animals from
Gjoa Haven, Baker Lake, Kugluktuk and Lutsel Ke'. In contrast the Arctic island muskoxen are less variable with an average heterozygosity and Pm of He= 0.243 and
1.51 X 10.' respectively. This group includes animals from the 7 sarnple locations of
Bathurst Island, Greenland, Grise Fiord, Kidjuut Lake, Northem Ellesmere, Sachs
Harbour and Wellington Bay. The lack of variability in the Arctic muskoxen is exemplified by the fact that 7 of the 134 animals in this group had identical 14 locus genotypes.
Genealogical relatioriships among muskox sample locations
The two methods for estimating topologies suggest muskoxen include two major groups. Both Dsand DLRindicate at Ieast two lineages within muskox with the group including mainland muskoxen - Gjoa Haven, Baker Lake, Kugluktuk and Lutsel Ke' - being supported in al1 10 000 bootstrapped replicates (see Figures 3-3a, 3-3b; pairwise divergence estimates in Appendix 2). The remaining Arctic Island rnuskoxen, including animals from Bathurst Island, Greenland, Grise Fiord, Kidjuut Lake, Northern Ellesmere,
Sachs Harbour and Wellington Bay, form a second lineage.
There is dso evidence for firther subdivision within the Arctic Island muskoxen.
Particularly, the close relationship of Northern Ellesmere, Greenland and Grise Fiord muskoxen is supported in al1 10 000 Dsand trees. The relationship of the remaining
4 muskox samples to this group is less clear. In the Dm network (see Figure 3-3a) the group comprising muskoxen from Kidjuut Lake, Sachs Harbour and Wellington Bay are
55 recovered in all 10 000 replicates. However, this groups is not supported in the Ds network. With both distances the affinities of Bathurst Island muskox to the other arctic island muskox is not clear.
Samples sizes
Both Ds and Dm between pain of muskox populations are significanily negatively correlated with the average microsatellite heterozygosity of the pair (Paetkau et al. 1997; Hednck 1999b). Hence the correct genealogy among sarnples depends on accurate estimates of rnicrosatellite variability. The correct sample size for determining microsatellite variability depends on polymorphism at the locus, but 30 animals from a given location appears to be a good initial sample for microsatellite loci (Paetkau et al.
1999). With large, widely dispersed mainmals this is difficult, but more so with
muskoxen which live in inhospitable Arctic areas where sarnpling is very difficult.
Despite the small sample size of some of the locations, we believe our estimates
of rnicrosatellite polymorphism in muskoxen are accurate for two reasons. Fint, the
unbiased estimates of expected heterozygosity from small initial sarnples of size 5 for
each location were close to those obtained from larger sample from the same location
with sizes between 9 and 23 (initial H, estimates with n=5 were within 0.8 -1.2% of final
H, estimates). This indicates it is unlikely thai we have incorrectly estimated variability
in these sample locations. For example, muskoxen from Kidjuut Lake show H, = 0.189
f 0.002 and it is unlikely that they have sirnilar levels of variability as nearby Kugluktuk
muskoxen where He=0.446 f 0.046. Second, Holm et al. (1999) have confirmed Our
low estimates of microsatellite variability in Greenland muskox. They surveyed 34
anirnals in western GreenIand (transplanted From eastem Greenland) with 6 microsatellite loci cloned from muskoxen. They estimated heterozygosity in these animals at He= 0.0 18.
DISCUSSION
Genetic Structure in Muskox
The main findings of our study are: 1) there are at least two genetic clusters of muskoxen - one on the mainland and at least one on the Arctic islands and 2) muskoxen have very different Ievels of genetic variation across their range, with Arctic island muskoxen king far less variable than Mainland muskoxen. We argue that three lineages exisr; the Northem Arctic Island (NAD lineage including Greenland (GD), Northem
Ellesmere (NE) and Grise Fiord; the Southem Arctic Island (SAI) lineage including muskox from Bathurst Island (BI), Kidjuut Lake (KL),Wellington Bay (WB) and Sachs
Harbour; and the Mainland lineage including animals from Baker Lake (BL), Gjoa
Haven (GH),Kugluktuk (KU) and Lutsel Ke (LK). After showing why we think these taxa are real we can evaluate the altemate models of ment muskoxen divergence proposed earlier.
Evidence for three lineages
At the level of nominal subspecies. it appears that adjacent sarnple locations are each other's closest relative, with the four Barrenground muskoxen (O. m. muschatus) populations being more closely related to each other than to any of the White Faced muskoxen (O. m. wardi). In addition, there is support for 2 lineages of Arctic Island muskoxen. The Northem Arctic Island (NAI) lineage is supported by boih Dm and Ds topologies. We have grouped the remaining Arctic Island muskoxen from Bathurst
Island, Kidjuut Lake Sachs Harbour and Wellington Bay into a Southern Arctic Island lineage (SAI). As indicated above the support for this latter group is weakest, with the
KL+SH+WB grouping in lm%of Dm but in none of the Dsreplicates. We argue below that the Bathurst Island sample represents a zone of introgression between the two Arctic
Island lineages and thus its placement does not receive unequivocal support from the 10
000 bootstrapped DLRreplicates. None-the-less Figure 3-3a and the fact that most of BI muskoxen are allied with other SA1 muskoxen (see below) suggest that the grouping
with SAI muskoxen is correct. It is interesting to note that the Dstree and the 10 000 Ds
bootstrap replicates do not support the BI+KL+SH+ WB grouping. This may refl ect the
fact that the assumptions of the Infinite Ailele Model (IAM) are violated in the 14 loci
under study (Goldstein and Pollock 1997).
The network in Figure 3-3a was used to assign the sample locations to one of
three lineages. Based on their 14 locus genotype, the 169 individuals from the 11
sarnples and three individuais were assigned to one of the Southem Arctic Island lineage
(N=73),the Northem Arctic Island lineage (N=36)or the Mainland lineage (N=61). Of
the 172 muskoxen, only 3 were assigned to a lineage other than the one they came from
and switches only occurred arnong Southern and Northern Arctic Lineages (Appendix 4).
Two of these animals were assigned a Northem Arctic Lineage origin but were sampled
with Southem Arctic animais (CI4 and CI-8), and the single muskox from Foa Ross
(FR-2) could have corne from either of the two Arctic Island lineages or may represent the FI hybrid of a cross between individuds From different lineages. The low levels of mis-assignrnent support isolation and divergence of the ancestors of these three taxa.
The majonty of muskoxen were assigned to one of the three lineages with great confidence. The validity of specific assignments can be estimated by calculating the ratio of the assignment probability to one group venus any of the other groups. One hundred and sixty eight muskoxen were assigned to a specific lineage with at least a
10times greater probability than of king assigned to any other (Appendix 3). Of the remaining 4, the assignments of BI-1, BI-30, and CM-1 to the Southem Arctic lineage are less than a maximum of 1000 times more likely than their assignment to the Northem
Arctic lineage. Similarly, although FR-2 was assigned to the Northem Arctic lineage, its assignment probability to the Southem Arctic lineage was only marginally less. As mentioned above these data are reflected in the lack of support from 10 000 DU( trees for strong -nities of Bathurst Island muskoxen to other SA1 muskoxen (Figure 3-3a).
The evolution of three muskox lineages is further supported by the heterogeneity
in allele frequencies at most loci among the three muskox lineages. Importantly, pairwise tests of homogeneity of allele frequency distributions indicate that 9 of the 14
loci had significantiy different distributions among NA1 and SA1 lineages (Table 3-2) -
indicating a unique but recent history for each lineage. Further, differentiation between
Mainland and Arctic Island muskoxen is strongly supported, with the allele distributions
being significantly different at 12 loci in Mainland and Southem Arctic Island
muskoxen and Mainland and Northern Arctic muskoxen differing at al1 loci.
Genetic divergence and diversity within and among 3 muskox lineages Northern Arctic and Southern Arctic island muskox are sister taxa. Both the and Dsnetworks suggest Mainland muskox are quite diverged from Arctic Island muskox (see Figure 3-3) with Arctic Island muskox king closely related. This conclusion is supported by allele frequency heterogeneity tests (Table 3-2). We calculated between the three lineages (see topology in Figure 3-4, Appendix 5). The
tree is consistent with the anceston to the island muskox king separated from mainland
muskox as a result of glacial expansion durhg LGM,with subsequent divergence of
island muskoxen. For convenience this topology is rooted at the midpoint of the longest
branch length.
The relative amount of genetic divergence supports late Wisconsin muskox
differentiation. Although we are not able to extrapolate accurate times of divergence
from Our microsatellite divergence estimates, the low mkrosatellite diversity within and
among muskoxen and the difference in relative divergence times among these taxa
argues strongly for - at the earliest - Late Wisconsin divergence. Unlike estimating times
of separation from DNA sequence divergence estimates, especially those from mtDNA
(Holder et al. 1999), the use of microsatellite divergence in this context is not
straightforward. The common assumption of the Single Step Mutation Mode1 of an
average allele length change of zero (Goldstein et al. 1995a; Slatkin 1995) coupled with
variable mutation rates and differing allele size range constraints across loci, and
mutational asymmetries in increase or decrease of alleles size, combine to impede the
simple calculation of divergence times from microsatellite data (summarized in
Coldstein and Pollock (1997)). As an alternative to a general distance-divergence time
rule, Goldstein et al. (199%) have suggested the use of absolute dating with pedigrees to caiibrate mutational rates of the loci. which can be used to estimate tirnes of divergence.
Our study would suggest a large and deep pedigree is needed to calibrate the mutational rate of muskoxen microsatellite loci. With respect to limited muskox divergence, although we describe polyrnorphism for 14 variable loci, our preliminary survey of 30 microsatellite loci that arnplified muskox microsatellites resulted in 16 of these loci not being used becausel 3 were invariant and 3 had only 2 alleles. The inclusion of these loci would have reduced average divergence among these taxa. The recent divergence time of muskox populations is further supported by lirnited muskox D-loop variation
(Groves 1997). The maximum percent sequence divergence among 8 muskox D-loop haplotypes is 1.29 1(Groves 1997). D-hop divergence estimates - averaged across the slower evolving central and the two faster evolving peripheral ETAS and CSB domains
- has been recently calibrated for marnmals at 12.6 I3.2 % per million yean (Pesole et
al. 1999). Using these data, the haplotypes diverged from each other no later than 100
000 years ago, supporting late Wisconsin divergence of muskox. Finally, the average
Duc between mainland and Arctic lineages is 22.46 whereas the distance between Arctic
island lineages is 8.68 (see Appendix 5). If one follows Paetkau et al. (1997) and
assumes that DLRmaintains linearity with time at this level of intraspecific divergence,
this suggests the Arctic Island lineage diverged from the Mainland lineage at Ieast two
times earlier than the two Arctic lineages diverged fiom each other.
In contrast to the Mainland, the two Arctic island lineages have greatly depressed
microsatellite variation (see Table 33). When analysed as three groups an individual
fiom the more variable Mainland (He= 0.535 f 0.068) is twice as likely to be
heterozygous than the next most variable Southem Arctic Island lineage (H,= 0.249 f
61 0.049). Similady, the Pm estimates Vary from a high of 1.5 X 1w8in the Mainiand to a low of low of 6.2 X 10% the Southern Arctic Island lineage. These data are consistent with the isolation of the ancestors of the Arctic Island muskox in small glacial refuges for extended period of tirne, whereas the Mainland anceston were not kept at low numbers for an extended period of time. Unlike inferences made from the sample location data, sarnples size is not a concern at the lineage level.
Recent Muskox Diversification
Whereas the isolation of a single Arctic Island lineage in an ice-free refuge is supported by the extensive glaciation of the Arctic Islands under an Innuitian Ice sheet at
LGM,the formation of the two Arctic Island lineages as a result of the isolation of muskoxen in two ice free refuges is not. Recent evidence suggests that The Queen
Elizabeth Islands were extensively glaciated by huitiun Ice and it is unlikely that two refuges large enough to harbour muskoxen penisted through LGM (Hughes 1998; Zreda et al. 1999). A second large refuge on the Queen Elizabeth Islands could only have been possible if these islands were covered by the Franklin Ice Cornplex at LGM,however this hypothesis appean increasingly unlikely (Hughes 1998; Zreda et ai. 1999).
We have shown that the divergence between the themuskox lineages is limited and in keeping with Late Wisconsin differentiation. Irnportantly, the relative divergence between the three lineages - an average qR of 22.46 between Mainland and the Arctic
Island lineages versus 8.68 between the two Arctic Island lineages - indicates that it is more than likely that SAI and NA1 diverged after the withdrawal of the Innuitian Ice Sheet. Had the two Arctic Island lineages diverged in two ice free refugia on the Arctic
Islands during LGM,al1 three lineages should be as divergent from one another as
Mainland muskoxen are from the Arctic Island muskoxen, i.e. 22.46 units.
Strong evidence for the isolation of the ancestors of Arctic Island Muskoxen in an ice-free refuge, includes the 3 - 4 orders magnitude difference in muskox genetic variability (as measured by Pm) between Mainland and Arctic Island muskoxen.
Animals isolated in rehiges will lose variability and particularly so if their effective
population size Ne remained low for a long period. This is more important for a large
ungulate such as Ovibos moschatw, as the carrying capacity of [the refuge] would be
reduced relative to smaller sized organisrns. The low genetic variability of both SA1 and
NA1 may suggest two separate ice-free refuges but we have shown above that this is
unlikely given the increasing likelihood of an Innuitian Ice sheet. This coupled with the
lirnited recent divergence between the two Arctic Island Iineages. makes it plausible that
a single refbgial Muskox isolate with low polymorphism differentiated into SAI and NAI
after the deglaciation of the Arctic Islands.
The final piece of evidence to refute independent ice-free refuge origins for each
of the two Arctic Island lineages is the qualitative difference between the two contact
zones we survey in this snidy. We argue that the Mainland - Southem Arctic Island
contact is secondary and the Northem Arctic Island - Southem Arctic Island contact
zone is primary. These arguments are based on marked differences in genetic variability
among these lineages (discussed above) and differences in movement across these
contact zones. Although Our data support previous evidence of muskoxen traveling great
distances(Le Henaff and Crete 1989; Smith l989), movement through the two putative contact zones in this study is clearly unequal with Mainland - SA1 exchange king rare.
The individual assignment probabilities of a given muskox allow one to distinguish between recent immigrants and residents in a sample, and therefore detect muskox movements between samples and lineages (see Wasser and Strobeck (1998)). As an example of great movement within lineages, Bathurst Island samples (CI-7and BI-381, are assigned to Sachs Harbour from the same Southern Arctic Island lineage - approx.
880 km away. In keeping with these findings, sorne individuals are mis-assigned between the NA1 - SA1 lineages. At Southem Arctic location Bathurst Island, 2 of the
16 animals (CI4 and CI-1) were from the NA1 lineage (Grise Fiord - approx. 400 km away). As implied above, the assignments of BI-1,BI-30 and CM-1 to the SA1 lineage are tentative. With more loci, their assignments could switch to a Northem Arctic origin.
Such movements are not seen across the Mainland - SA1 contact. Of the 123 samples of muskoxen surveyed from both Mainland and Southem Arctic lineages (excluding samples from Bathurst Island) we had no evidence of immigration into either lineage.
The maximum distance between the SM sarnple locations Kidjuut Lake or Wellington
Bay and Mainland sample locations Kugluknik and Gjoa Haven is only 360 km.
However, these locations only contain muskoxen from their respective lineage [data not shown]. Also, in a more detailed study of a Mer86 animals from Kugluktuk and
Surrey lake (near Kidjuut Lake) with a subset of 9 of these loci - we only found one SA1 muskox among mainland muskoxen from Kugluktuk (Van Coeverden de Groot unpubfished data). Finally, we have no evidence for a NAI - Mainland contact zone, but we suggest this would be secondary contact. In sum, our data support a major but not exclusive role for an ice-free refuge on
Banks Island during the LGM in generating extant muskox genetic diversity. We propose that recent muskox differentiation involved isolation of Arctic Island ancestors frorn Mainland muskoxen in ice-fiee refuge on Banks Island - 30 000 y.b.p. (Harrington
1977). That Banks Island was a refuge at LGM is supported by the recovery of a 30 000 year old muskox bone on the island (Hmington 1977). No other muskox bones of this age or younger have been recovered from the Arctic Islands and Greenland, which suggests that evidence of pre-late Wisconsin muskox habitation was subsequently removed by extensive glaciation. With the withdrawal of the ice from the Queen
Elizabeth Islands, the Arctic Island muskoxen diverged in parapatry possibly dong an environmental gradient some 10 000 y.b.p. (see also Groves (1997)). These ideas are captured in Scenario 3 in Figure 2. We do not ascribe a significant role to fluctuating population sizes in the generating the major divisions within muskox. However it is
likely that size fluctuations and possible extinction - recolonisation population dynarnic
has contributed to the low variability in the Arctic Island Iineages in this species
(Gliddon and Goudet 1994). A similar mechanism of oscillating population size - as a
result of Holocene climate fluctuations - has ken invoked to explain low mtDNA
diversity in Canadian Arctic populations of the collared lemming Dicrostonyx
groenlundicus (Ehrich et al. 20). Mainland muskoxen were believed to have been
isolated below the Laurentide ice sheet at LGM. where they existed with at least one
congenenc muskox - Symbos the "helmeted muskox" (Harrington 1977; Rowell 1990).
This latter cornmon ice age rnuskox went extinct 110y.b.p. Ieaving only Ovibos which
survives to this day (Harrington 1977). Evidence for the Diversify irtg Role of North American Arctic Refuges
Our findings add to recent molecular data for a number of Arctic taxa that strongly support the diversifying role of an ice free refuge on Banks Island during LGM.
Of interest in this regard are microsatellite polyrnorphisms in Peari caribou Rangfer tarandus pearyi and the Barren Ground Caribou Rangfer tarandus groenlandicus. The true Peari caribou are distributed similarly to the Northem Arctic Island muskox lineage and muskox of the Southem Arctic Island lineage found north of the Parry Channel (for example Bathurst and Melville Islands). The range of the Barrenground Caribou includes that of the Mainland muskox. In a survey of 6 di-nucleotide microsatellites,
-3 Peari caribou (n=157) had Pa>estimates of 1 in 7.5 X 10 (Keri Zittlau, pers. comm.
1999) whereas the PD estimates for the same loci for Barrenground Caribou (n=23 1) was
1 in 7.6 X 1o*~ (Nagy et al. 2000). The drop in genetic variability among these two caribou taxa is remarkably similar to that among Mainland and Arctic Island rnuskox and rnay suggest a common refugial origin and demographic history.
The importance of this refuge was presaged by (MacPherson 1965) but only now with increasingly sensitive molecular markers and congruent genealogies among unrelated taxa can we argue for its role in shaping extant Arctic biodiversity (Lynch
1988). Along with my muskox rnicrosatetlite data, strong support for the divenifying
role of this refuge is found in mtDNA and nuclear intmn data for the rock ptannagin
Lagopus mutus (Holder et al. 1999), mtDNA variation in the North Amencan collared lemming Dicrostonyx groenlandicus (Ehrich et ai. 2000) and chloroplast DNA variation in the arctic plant Drycrs integrifolia (Tremblay and Schoen 1999).
We especially thank D. Michaud and C. Davis for invaluable assistance in the laboratory. Thanks also to J. Kushny and L. Mutch for laboratory assistance. We thank S. Akeeagok, P. Aastrup, L. Coady, E. Coleman, M. Forchhammer, J. Hunter, J. Kuneyuna, T. Lockhardt, R. Mulder, J. Nishi and A. Williams for assistance with sample collection in Canada and Greenland. M. Meban and S. Gnffin provided invaluable field assistance. Special thanks to the venerable F. Miller who provided valuable samples and logistic help. D. Paetkau and C. Strobeck provided invaluable assistance in applying their new method to the analysis of microsatellites. In this regard thanks to J. Bmtowski for his useful and expedient programming. Financial support for field work was provided by Polar Continental Shelf Project of the Geological Survey Canada, and Northern Students Training Program of the Department of Indian and Northern Main, Govemment of Canada. Further logistic support was provided by Parks Canada The laboratory work was funded by a gant from the National Research CounciI of Canada to PTB. PJVCDG was hinded by a Queen's Graduate Award, a Grants-In-Aid award from the Amencan Society of Mammalogists and an award from Sigma Xi. FIGURE LEGENDS
Figure 3-1. Geographic limits of the white faced muskox Ovibos moschatus wardi and the Barmground muskox Ovibos moschatus moschatus. Sarnple abbreviations, geographic co-ordinates and sample sizes for this study are listed in Table 3- 1. represents either the location of the community that provided muskox samples (BL, GF, KU, KL, SH and W), or the approximate center of a collection of muskox collected by researchen (BI, GD, NE, LK). V represents the single samples FR-2,PW-4 and TH-27 (see Appendix 1 for individual CO-ordinates).The numben represent current populations estimates of muskox on the mainland, Canadian Arctic islands and Greenland (Boertmann et al. 1992; Fournier and Gunn 1998 and John Nagy pers. comm. 1999). Also shown are two proposed Late Glacial Maximum refugia ,one on Banks Island (Hughes 1998) and one hypothesized for Northem Greenland. The "?" indicates that the position and size of this refuge is uncertain.
Figure 3-2. Altemate muskoxen genealogies resulting from different recent divergence scenarios. In Scenario 1 muskoxen are first isolated in a High Arctic Island refuge pior to isolation of muskoxen in a more southerly ice-free refuge. In Scenario 2, Arctic Island muskoxen diverge in two refugia after their isolation from Mainland muskoxen. In the 2 refuge scenarios (1 and 2) divergence occurred with the onset of the last glacial maximum some 35 000 y.b.p. In Scenario 3, after a period of time in a single refuge the two Arctic Island muskox lineages diverged after the withdrawal of the Laurentide ice- sheet some 10 000 y.b.p. Although Scenario 2 and 3 have the same topology, divergence of Arctic Island muskoxen from Mainland muskoxen prior to the formation of two arctic island lineages is much smaller in 2 vs. 3.
Figure 3-3. Consensus of unrooted networks of 10 000 resarnpled replicates for the genealogical relationships among the 11 sample locations for two microsatellite distance measures: DLR(Paetkau et al. 1997) (Figure 3a) and Ds(Nei 1972) (Figure 3b). Those nodes supponed in 100% of replicates have a solid circle with al1 other nodes receiving less than 50% support. The enlarged boxes represent those portions of the network with small evolutionary distance between nodes. The topology supports three unique lineages of muskox: Southem Arctic Island (SAI) of Bathurst Island, Kidjuut lake, Sachs Harbour and Wellington Bay; Northem Arctic Island (NAI) of Greenland, Grise Fiord and Norihem Ellesmere and the Mainland lineage of Baker Lake, Gjoa Haven, Kugluktuk and Lutsel Ke'. The branching pattern of the Dm network is to evaluate refugial divergence in muskoxen. (See text for details.)
Figure 3-4. Evolutionary relationships among the themuskox lineages. The Neighbor Joining topology of assignment distances Dm clearly shows close afinity of the Southem Arctic Island lineage (SAI) and the Northem Arctic Island lineage o.The muskox of the Mainland have a sister relationship to all Arctic Island muskox. The topology is rooted at the longest branch length although branch lengths are not shown. White faced muskox Banengrouad muskox Hypothesized LGM refugia
Figure 3-1 - - 35 000 y.b.p. 4 + BANKS ISLAND
J REFUGE
a) Scenario 1
HIGH ARCTIC ISLAND REFUGE
BANKS ISLAND REFUGE
b) Scenario 2
NORTHERN ARCTIC ISLAND LINEAGE SOUTHERN ARCTlC ISLAND LINEAGE
c) Scenario 3
Figure 3-2 W.B. i
Bathurst Island Northern Ellesmere Grise Fiord Greenland \
- = 1 D, unit Lutsel Ke \ #aven Kugluktuk
Greenland ......
Gjoa Lutsel Ke Haven Kugluktuk
Figure 3-3 Figure 3-4 Table 3- 1.
Variability at 14 microsatellite loci in 169 muskoxen from I 1 sample locations ncross their range. Locations are arranged from approximately North to South, wiih abbreviations in brackets. The unbiased estimate of expected heterozygosity (Nei and Roychoudhury 1974) is shown f standard error (SE). The number of alleles per sample location and the number of polymorphic loci per location Vary among locations. Also shown is the probability of any rnuskox from a given location being identical - Probability of Identity (PjD)- to another from the same area using their 14 microsatellite locus genotypes. The Pioformula used is given in Paetkau et al. 1998. Data for three individunls TH-27, PW-4 and FR-2are not shown in this table but approximate locations are shown in Figure 3- 1
Northem Sample Heterozygosity Number Polymorphic P. of Identity Latitude size +SE of Alleles Loci (Pm)
Northern Ellesmere Grise Fiord Bathurst Island Green land Sachs Harbour Kidjuut Lake Welling ton Bay Kugluktuk Gjon Haven Buker Lake Lutsel Ke Table 3-2.
Results of pairwise genic (allele frequency) differentiation tests across the three lineages for each locus. Nine of the 14 loci had different distributions in the Southem and Northem Arctic Island lineages, 12 of the 14 wcre different in the Southern Arctic Island and Mainland lineoges, and the Northern Arctic Island and Mainland line~geshad different allele distributions at al1 loci. The P-values are the probability (Fisher exact test) of getting the observed result if the Ho of no difference in allele frequencies among lineages was tnie (Raymond and Rousset 1997). SE is the standard enor in estimated P. A P of 1 .O00 indicates identical allele distributions in both populations and (--) represents a single shared allele present in both populations. Test were conducted using a Markov chah with 1Oûû demorisation steps, 50 batches and 10iterations per batch using the program GENEPOP v 3.1 (Raymond and Rousset 1997). MAIN = Mainland Lineage, NA1 = Northzrn Arctic Island Lineage and SA1 = Southern Arctic Island Lineage (see Figure 3-4 for opproximate distri butions).
Lineages Compared LOCI
MX-O 1
SA1 & NA1 -- "-- & - SA1 MAIN <0.001 ~0.001 NA1 & MAIN <0.001 <0.001
SA1 & NA1 SA1 & MAIN NA1 & MAIN
BM-1225 SA1 & NA1 ~UU1 Summary of microsatellite vnriability in the three muskox lineages. Unbiased estimales of expected heierozygosity (Nei and Roychoudhury 1974) and their standard errors are shown. Pio = probability of Identity as ddefined in Paetknu et al. 1998 and the total number of alleles in each lineage are also shown. Lineage Sample Expected size Heterozygosity ISE Souihern Arctic Island lineage 75 0.2472 0,028 6.20 E-04 35 Northern Arctic Island lineoge Chapter 4 THE ROLE OF THE ARCTXC OCEAN IN GENETIC EXCHANGE AMONG ISLAND MUSKOXEN OVIBOS MOSCHATUS: EVIDENCE FROM MICROSATELLlTES PETER J. VAN COEVERDEN DE GROOT'~,AND PET= BOAG ' 1. Department of B iology, Queen's University, Kingston, Ontario, K7L 3N6 Canada 2. Corresponding author, email peteri 8 biolo~.aueensu.ca The role of the Arctic Ocean in genetic exchange in the muskox Ovibos moschatus was investigated using an 11 locus genotype for 158 muskoxen from the Arctic Islands and Mainland. An initial cornparison of Arctic Island and Mainland muskoxen produced contradictory results. Simple regression of the shared allele distance DsA on geographic distance, and a Generalized Mantel Analysis (GMA) suggest genetic exchange among the Island rnuskoxen is impeded relative to Mainland muskoxen. Convenely multiple regression anaiysis indicates that ocean waterways expedite the movement of Arctic muskoxen. When two putative Arctic Island lineages of muskoxen are analysed independently, the results from our three analyses make sense, suggesting a varying role of the Arctic Ocean in genetic exchange among Arctic Island muskoxen. The multiple regression analysis indicate the Arctic Ocean expedites genetic exchange in the more rugged Northem Arctic Island muskox range and GMA analysis suggested the Arctic Ocean both retards and expedites genetic exchange across Arctic waterways in the Southem Arctic Island muskox range. Many large mammal species were once continuously distributed over large expanses. Owing largely to human disturbance, their current habitat is increasingly fragmented into much srnaller spaces. As their range becomes fragmented, populations of a species are thought to become increasingly subdivided and isolated. Genetic exchange is reduced, with a predicted loss of genetic diversity within these new isolates if Ne is small enough (Templeton 1990). A logical first step in explonng the consequences of range fragmentation for any taon is to test the hypothesis that the surviving populations are indeed expenencing substantially Iess genetic exchange than their contiguous ancestors did. Unfortunately in most cases this test cannot be made after habitat disturbance has occurred due to the absence of pre-disturbance genetic data. The muskox Ovibos moschatw presents a rare opportunity to test for reduced genetic exchange in a large ungulate inhabiting a naturaily fragmented range (see Figure 4-1). This is one of a few large ungulates still present over much of their historical range on Mainland Canada and on the Canadian Arctic Islands and Greenland. The barrenground muskox Ovibos moschatus moschatus is found on the mainland. Although there are many lakes, no part of the mainland range is isolated by water fiom the other mainland areas. The white faced muskox Ovibos moschatus wardi inhabits many islands in the Canadian Arctic archipelago and Greenland. In contrast to the habitat of bamnground muskox, the Arctic Ocean sunounding the Arctic islands may represent a substantial barrîer to muskox movement. Where the ice melts during the sumrner months the open sea prohibits mvel and during the winter months the ice usually presents an inhospitable passageway with no food or water. ln this regard, muskoxen have been reported frozen in the ice after attempts to cross between islands (Frank Miller, pers. comm. 1999; Anne Gunn pers. comm. 2001). If the Arctic Ocean surrounding the Arctic Islands reduces genetic exchange among Island muskox relative to their Mainland conspecifics, this system may serve as natural mode1 for assessing the effect of anthropogenic range fragmentation in large ungulates. finally, our previous work has shown little or no genetic exchange arnong Mainiand and Arctic Island muskoxen across the water gap between Banks and Victoria islands and the Mainland, permitting a valid cornparison of the effects of the Arctic Ocean across these two groups (Chapter 3). Genetic Exchange and Geographic Distance Central to this study is the measurement of genetic exchange, its relationship to geographic distance and the contrast between Arctic Island and Mainland muskoxen. The comrnonly used measure Nm - the number of migrants per generation among populations of conspecifics - appears to be an inappropriate estimator of genetic exchange in muskoxen. One reason is that the unique geometnes and natural history of real fragmented populations usually violate the assumptions of the Random Models underlying most calculations of Nm. For example, it is unlikely that al1 populations are panrnictic and experiencing the sarne amount reciprocal of gene flow with al1 other populations - assumptions of the N-island Mode1 (Wright 1951; Hutchinson and Templeton 1999). Although more realism may be achieved with recent methods that estimate asymmetric pairwise Nm estimates between populations (Beerli and Felsenstein 1999), the dificulty of defining muskox populations hampers population level analyses. A second reason is that the relatively low levels of genetic divenity in muskoxen make a genetic definition of muskox populations difficult (Chapter 2.3;Groves and Shields 1996; Groves 1997). Although muskoxen are mostly found in mixed sex and age herds of 5 to 30 animals, with herds tending to be srnailest during the late summer rut and larger in the winter (between 5 and 12 and 12-30 respectively; Tener 1965; Reynolds 1993), the lack of genetic variation in muskoxen suggests that the use of herds or groups of herds as different populations will result in estimates of Nm,which suggest panmixia in these animals. In a detailed shidy of 9 variable microsatellites in 80 Mainland muskoxen separated by no more than 225 km, no genetic evidence for herd structure was found (L. Mutch unpl. data). Unlike gene flow between populations, a second measure of genetic exchange, genetic distance, can be relatively easily applied to individuais. Coupled with the difficulty of defining muskox populations, the large range of Ovibos - - 5 million sqüare kilometen - and the expense of sarnpling Arctic Island muskox places practical Iimits on the sarnple size of muskoxen. However, the development of hypervariable microsatellites and more precise estimates of inter-individual genetic distances ailows an initial andysis of genetic and geographic distance at the level of the individual (Bowcock et al. 1994; Smouse and Peakall 1999). In this paper we investigate the relationship of the Shared Ailele distance, DsAand geographic distance between pairs of individual muskoxen across the various landscapes (Bowcock et al. 1994; Goldstein et al. 1999). Differen t Genetic and Geographic Distance RelationFhips for Different Landscapes Critical to this study is the comparison of the relationship of genetic and geographic distance between muskoxen separated by water and those that are not. An obvious fust step is the comparison of slopes of the simple linear regression of genetic on geographic distance in Arctic Island (including Greenland) versus Mainland muskoxen. If the Arctic Ocean always impedes genetic exchange among muskoxen on adjacent islands relative to the Mainland, the dope and possibly intercept a will be greater for Arctic Island than Mainland muskoxen. A second approach is the analysis of Arctic Island muskoxen separated by water and those that are not. It is expected that the presence of the Arctic Ocean will increase pairwise &A relative to Island muskoxen on contiguous land. In a multiple regression andysis where the presence or absence of the Arctic Ocean between Arctic Island muskox pain is coded as a binary variable, this Water effect should be significant and positive. Since simple linear regression groups water separated pain and pain on contiguous land into a single analysis, by separating these data points, multipIe regression analysis is more sensitive to smaller Arctic Ocean contributions to genetic exchange. It is important to remembcr that in both simple and multiple regnssion analyses the nature of the water gap between any two islands is not charactensed. Two characteristics are likely to be important Fit,the distance between islands varies as some islands can be > 60 km apart whereas a large number are c lOkm apart. Second, dthough many of these waterways are frozen in the winter, the nature of the ice varies substantially across the Arctic Ocean (for maps see htt~://www.cis.ec.~c.ca/cia/climateproductdcis ice atladatlas E.htm). In some cases the ice may be easily crossed, whereas in other cases it is very rough and difficult to traverse. The importance of these different waterway properties is not known. The above two arguments suggest that it is possible the Arctic Ocean plays a varying role in the movement of muskoxen throughout their Island range. Furthemore, it is possible that a varying role of the Arctic watenvays results in no difference between the Arctic Island and Mainland linear regressions and a non significant water effect in the multiple regression analysis. In contrast to the above regression analyses which group al1 data points together, Generalized Mante1 Analysis (GMA)partitions these data into different size classes. This partitioning may detect a variable Arctic Ocean role. In GMA, the normalized Mante1 statistic rm of pairwise DSAand geographic distance is calculated across a series of geographic distance classes and these results are presented in a correlogram (Smouse et al. 1986; Sokal 1986). The rm are essentially regression coefficients of DsAon geographic distance at different scales (Smouse et al. 1986). Here again the contrast between Arctic Island and Mainland muskoxen is important as the following two examples illustrate. If the presence of the Arctic Ocean has no effect on muskox movement, the relationship of rm with distance class will be the sarne across the Mainiand and Arctic Island portions of their range. On the other hand, if the Arctic Island muskox GMA correlogram oscillates between positive and negative rm while a Mainland correlogram does not, a varying role of the Arctic ocean in rnuskox genetic exchange may be suspected. If a distance class includes a number of muskox pairs that straddle a water gap which impedes muskox movement, ryx will be less (even negative) versus Mainland muskox. The rm will be more than the Mainland values if the distance class includes muskox pairs that straddle a water gap which expedites muskox movement. To determine the role the Arctic Ocean plays in the genetic exchange of muskoxen between Arctic Islands, we used three regression analyses to examine the relationship of DsA- cdculated from 1 1 di-nucleotide microsatellite loci - and geographic distance in 158 muskoxen from throughout their range. Fint, we compared the simple linear regression slopes in Arctic island and Mainland muskoxen. Second, the presence or absence of water was included in a multiple regression of interindividuai DSA on geographic distance in Island distributed muskoxen. Third, we compared GMA correlograms in Arctic Island and Mainland muskoxen. METHODS Samples and Their Geography The 158 muskox samples for this study were provided by Hunter and Trapper Councils (H. T. C.) from communities in Northwest Temtories and Nunavut, Canada or collected by the authors and other researchers. The location data and number of samples are listed in Table 44b. The H.T.C.'s from Baker Lake (BL), Cambridge Bay, Gjoa Haven (GH),Grise Fiord (GF), Hoùnan, Kugluktuk (KU), Lutsel Ke (LK) and Sachs Harbour (SH) provided fresh samples of liverlkidney/heartlmuscle taken from muskoxen hunted as part of an annual quota (see Chapter 5 for details). Other samples came from carcasses encountered by the authon by air or on foot. Most of these salvaged samples were desiccated small tissue flakes which often yielded degraded DNA. Optirnization of DNA extraction and amplification procedures are described in Chapter 2. For Our analyses each individual must have a unique geographic location. The precision and accuracy of location data varied across samples, with different rnethods used to assign individuals to unique locations (data in Table 4- 1b and Appendix 1). For example, individuals from Baker Lake (BL),Kugluktuk 0and Grise Fiord (GF) Northern Ellesmere (NE), Bathurst Island (BI) had accurate geographic locations. The location of the community of origin (BL, KU and GF) or the centre of the sarnpling distribution (NE and BI) is show in Table 4-1 b Individuals from Greenland (GD), Kidjuut Lake (KL - provided by the Holman H. T. C.), Lutsel Ke (LK)and Wellington Bay (WB - provided by the Cambridge Bay H. T. C.) did not have such precise location data. Sarnples from these areas (except Greenland) were taken by huntea from defined areas, the centre of which is listed in Table 4- 1b. For KL, LK and WB,the sarnples were collected from 1 or 2 nearby herds, allowing us to randornly assign co-ordinates to individuals within the hunted area. These cdculations involved randomiy assigning a sample a geographic co-ordinate that differed from any other muskox in the same sample by no less than 0.Olminutes latitude or longitude. This resulted in animals differing from their closest neighbour by no less than 0.08 km and from their hrthest neighbour by no more than 23.4 km. The new unique coordinates for these samples are described in the UNIQUE column in Appendix 1. Greenland (GD) samples were fiom deceased muskoxen on Zackenberg (7) and Jamieson Land (3) on Northeast Greenland. The rnidpoint between Zackenberg and Jamieson Land is listed in Table 4lb. These muskoxen were assigned unique correlates using the process descrïbed for LK, WB and KL samples. H. T. C sarnples from Sachs Harbour (SH) and Gjoa Haven (GH) have the least accurate location data. SH sarnples were collected as part of a large annual hunt on Banks Islands where - 5000 animals are taken annually. Smailer groups of muskoxen are herded together from Southern parts of the Island to form groups of 400 to 500 muskoxen. These are then dnven to Sachs Harbour and harvested (John Nagy pers. comm. 1999). The latitude and longitude of Sachs Harbour is listed in Table 4-1 b with individual geographic correlates king assigned around this centre the same way as for LK,WB and KL. Finally although Gjoa Haven is located on King William Island, the GH muskoxen were hunted on the mainland, south of the Adelaide Peninsula. The coordinates of Gjoa Haven are listed in Table 4-lb with unique geographic correlates assigned about this centre as with LK,WB and KL samples. Microsatellite Loci We determined microsatellite genotypes with Il variable loci in the 158 muskox. We have shown that muskoxen have relatively low microsatellite variability and from a Iarger survey of 14 loci across 172 muskoxen, we used the subset of 11 loci that were variable in ail of the three major muskox lineages (see Figure 4-1, Chapter 2.3). The muskox were scored for MX-2and MX-5 (Holm et al. 1999); OM 51-16,51-19.53-38, 54-23,55-04,5630 (Chapter 2). RT-6 (Wilson et al. 1997); MAF-70 (Buchanan and Crawford 1992) and BM-1225 (Bishop et al. 1994). From the 172 muskoxen onIy those which could be assigned a geographic location were used. Reaction conditions for OM loci are described in Chapter 2 with the conditions for the other loci detailed in the original papes. Analyses Simple linear regression of shared allele distance on geographic distance We first compared the slopes of the simple regression of inter-individual shared allele distance DsAon geographic distance across mainland and al1 Arctic island muskoxen combined. DsAis given by the formula: DsA= 1 - Ps number of shared alleles sumrned over loci where Ps = 2 X number of loci compared and painvise calculations were made using a calculator at http:ll~ause.biolow.udberta.cdibmsto/shedist.h. Painvise geographic distances in km were calculated from sample location data using the DISGEO utility in the R - PACKAGE (Legendre and Vadour 1991). Painvise genetic distances are not independent, thus we determined the significance of B through evaluation of 100randomized data sets using the ISOLDE utility in GENEPOP v. 3 (Raymond and Rousset 1997) for each lineage. We calculated the significance of the difference between the two slopes using randomization procedures. The absolute value of the computed t value for md- B-hd was compared to Itl values calculated from 4999 pairs of randomized datasets. The calculation of a Itl value from a pair of randomized datasets involved pooling equal numbers (56 1) of distance and DsA pairs from Arctic island and mainland muskoxen, randornly assigning half to the Arctic Island group with the remaining half being mainland muskoxen. The P values represent the number of randomized datasets with It[ values for ~mC~~d- Pmainland as large or larger than the Itl value from the original data, divided by the total number of datasets. In al1 cases this latter value was 5000 (4999 +1). Multiple regression of Dû(on geogruphic distance and presence or absence of Arctic Ocean between individuals We evaluated the significance of Water and Water*Distance effects in a multiple regression of DsAon geographic distance and the presence or absence of Arctic Ocean between Arctic island muskoxen. The presence or absence of a waterway between 2 sampled muskoxen was scored as 1 or O respectively and was included as a dummy variable with pairwise geographic and DsAdistances in a multiple regression andysis. The sign and significance of the Water effect and the interaction term Water*Distance within each group of muskox is relevant. A significant positive partial regression coefficient for Water and a non significant Water*Distance interaction indicates that the presence of water increases the genetic distance between water- separated muskoxen by a fixed amount. However the increase in DsA per km is the same regardless of whether the muskox pairs are separated by water or not. On the other hand, a significant positive partial regression coefficient for Water and Wafer*Distance indicates muskoxen separated by water show increased differentiation pet km relative to those on a common landmass. We also report the standardized Beta values indicating which effects explain most of the variation accounted for in the regression. Generalized Mantel Analysis We calculated one dimension codograms of a Generalized Mantel Analysis of DsA and geographic distance in Arctic island and mainland muskoxen. The unequd sample sizes of mainland (n=5 1) and Arctic island muskoxen (n=107)and the unequal number of muskoxen in diffcrent distance classes (see below) mean that a cornparison of the Mantel statistic Zn (Mantel 1967). The nomalised Mantel statistic ryx removes the effect of different sample sizes and effectively calculates a regression cwfficient between DSAand geographic distance in each distance class (Smouse et al. 1986). We calculated norrnalized Mantel statistics r~xfor distance classes of -1ûûkm across Arctic island and mainland muskox separately. These results are presented in 1 dimensional correlograms (Sokal 1986). We set Our distance classes at - 100 km. Although the size of the distance class is somewhat arbitrary, 100 km was a good fit given the expanse and nature of muskox habitat, and our muskox sample database. Sixteen of the named Arctic islands have a longest distance greater than 100 km, whereas the remaining 17 have a longest distance of less than 100 km. A smaller distance class, for example 50 km, would have resulted in low sample size in many classes and this would provide no information as to the relationship between genetic distance and geography (see below). On the other hand a larger sized distance class - for example 200 km - could obscure a varying role of the Arctic Ocean this anaiysis was designed to detect. Also, our method of assigning latitudes and longitudes to individuais at certain locations resulted in a maximum dispersion of 23.38 km between the "furthest" two samples at a sample location. Consequently al1 the muskoxen from these areas fit into single 100 km distance class. Finaily no island in this Archipelago is separated by more than 100 km fiom its nearest adjacent island. The exact size of the distance class size for Arctic Island and Mainland lineages was set to 102 km and 105 km respectively; these were slightly different from 100 km given the method of creating size classes in AUTOCOR utility of the R- PACKAGE (Legendre and Vadour 199 1). A correlogram is significant if the Bonferroni corrected a value is less that 0.05. This is the case if one of the significance values (P) for a distance class is less than a/ # of distance classes. P of rm at each distance class was estimated by transforming the ryx value into a t-value (Mantel 1967; Legendre and Vadour 1991). Al1 rm calculations. including significance tests for each distance class in each lineage, were calculated using the MANTEL utility in the R-PACKAGE(Legendre and Vadour 199 1). Distance classes with 6 or fewer individuals include too few muskox pairs to make any inference about the relationship between genetic distance and geographic distance. Finally, we are unaware of any statistical tests to determine if two correlograms are different. However, qualitatively different correlograms provide sufficient evidence for dissimilar population genetic stnicture in taxa (Legendre and Fortin 1989; Peter Smouse pers. cornm. 1999). Simple Linear Regression Our initial analyses suggest the Arctic Ocean impedes the movement of muskox. The linear regression of DsAon geographic distance for pairs of individuals was significant for both groups (P < 0.001). The genetic divergence per kilometer for Arctic island muskoxen is significandy greater than for mainland muskoxen: bh& irlnnd = 1.30 x 10-4 z bhdmd = 6.87 x (t = 3.09, P < 0.001; see Table 4-2a). Multiple Regression In contrast to the above, the multiple regression results suggest the Arctic Ocean is expediting genetic exchange in Arctic Island muskoxen. Although the DsAbetween muskox pairs is linearly dependent on geographic distance and the presence or absence of water in Arctic Island muskoxen, a negative Water partial regression coefficients and a significant Water*Distance interaction in Arctic Island muskoxen indicate increased genetic distance arnong muskoxen not separated by Arctic Ocean relative to water separated muskoxen (Table 4-3a). It should also be noted that the addition of Water as a variable in a multiple regression mode1 explains marginally more variation in the DSAin Arctic Island muskoxen than simple Iinear regression involving only Distance (R2 = 0.400 vs. R~= 0.388, Table 4-2a and Table 4-3a.) The contrast between the correlograms of al1 Arctic Island muskoxen combined and rnainland muskoxen suggests that Arctic Ocean plays a varying role in the movement of muskoxen in the Arctic Islands (see Figures 4-2a and b). The correlograms are both significant at the Bonferroni corrected a. In Arctic Island muskoxen for distance classes of 100km or less, the correlograrn oscillates between a positive relationship between genetic distance and geographic distance and no relationship between the two variables. Beyond 1ûûû km the relationship between the two is either negative or nonexistent. In this analysis the 2401-2500 km class had too few points to be informative and class 250 1-26ûûkm had no data. By contrast, for mainland muskoxen over comparable distance classes, the ryx is significantly positive for only the O - 105 km class. Between 106 and 630 km there is no relationship between inter-individual distance and geographic distance. The three rm at distance classes between 841 to 1050 km are al1 negative. Also in mainland muskoxen, al1 distance classes have enough pairwise distances to be informative. Accounting for Genealogical Structure in Arctic Island Muskoxen Our conflicting findings of simple linear regression indicating an impeding role, multiple regression suggesting an expediting role and GMA suggesting a varying role of the Arctic Ocean waterways may be a result of a small but significant hierarchical structure in Arctic Island muskoxen. We have demonstrated microsatellite evidence for two putative lineages in Arctic Island muskoxen: a Northem Arctic Island (NAI) lineage and a Southern Arctic Island (SAI) lineage (see Figure 4- 1, Chapter 3). Hierarchical structure will inflate estimates of B in the regression of DsAon geographic distance for the pooled dataset - the sarne effect resulting from the reduction of muskox genetic exchange by the Arctic Ocean. Furthemore, the substantial contribution to an oscillating correlogram of genetic structure was suggested in GMA of al1 muskox combined (data not shown). Here the correlogram oscillated between significant positive and significant negative from 300 to 1ûûû km. As we have shown when analysed separaiely the comlograms of mainland and Arctic island muskoxen were quite different (Figure 4-2 a, b). Thus we repeated our analyses on NA1 and SA1 muskoxen independently. Muskoxen from the 7 Arctic island locations (see Table 4-1 b) were assigned to NAI or SA1 lineage based on their 1 1 locus genotype using the assignment calculator at http://gause.bio1ogyYualberta.ca/ibruzsto/ieans.html Simple linear regression Genetic divergence per kilometer in the SA1 and NAI lineages is not significantly different from Mainland muskoxen (Table 4-2b). The borderline P value for the difference in the regression slopes of Mainland and NA1 muskoxen (P=0.0508)suggests with more data and bctter estimates of pairwise geographic distance (see below) the hypothesis of equal slopes might be rejected. Multiple regression In contrast to the results of the simple linear regression, when the presence or absence of water is included, the Arctic Ocean appears to play different roles in NA1 and SA1 muskoxen. Similar to the analysis of combined Arctic Island muskoxen, NA1 animals 91 have significantly negative Water and a significant Water*Distance interaction (Tables 4-33). Aiso, it is interesting to note that in this lineage, Water* Distance contributes as much to the mode1 as does Distance done: std 0.934 and 0.937 respectively. By contrast, Water and Water*Distunce interaction are not significant in SM, suggesting that in this lineage the Arctic Ocean does not impede or expedite the movement of muskoxen (Table 4-3b). Finally, the R~for the analysis of al1 Arctic Island muskoxen dropped from 0.400 to 0.1 9 1 for NA1 and 0.072 for SA1 muskoxen (Table 4-3a,b). Similar to the decay of R~in the simple linear regression of NA1 and SM independently, these results indicate that much of the variation in Dsa of the original analysis was an artifact of the 'hidden historical' genetic structure in Arctic Island muskoxen (Table 4- W). Generalized Mantel analysis GMA analysis suggests that the Arctic ocean is playing a varying role in the movement of muskoxen in the SA1 lineage whereas the lack of data for NA1 muskoxen prevents us reaching a significant conclusion. To keep our analyses comparable with those of the combined Arctic island and mainland muskoxen, we set the distance classes for both NAI and SA1 at 102 km resulting in 23 and 10 distance classes respectively. The comlograms are both significant at the Bonferroni corrected a and SA1 muskoxen do not show a clinal or gradient relationship between DSAand geographic distance (Figure 4-2c,d). There are few NAI muskox pairs (n=561) over a large number of distances classes resulting in many - 9 of 23 distance classes - having no or too few values for the correlogram to be informative. In these muskoxen, rm is signifcantly positive at - 100km, while genetic divergence and geographic distance are unrelated 92 between 200 and 400 km, and rw is significantly positive between 400 and 500 km (Figure4-2c). Beyond 500 km genetic distance and geographic distance are unrelated, negatively related or we have insuficient data to reach any conclusions. In contrat, SA1 muskoxen include more animais so only 1 of 10 classes is not informative. In SAI rm altemates between positive and negative significance in the first 3 distance classes (Figure 4-2d). Distance class 307 to 408 km has too few data to be informative (n4) and distance class 409 to 5 10 km is non-significant. At distances 2 600 km al1 rm between genetic divergence and geographic distance are significantly negative. Although differences in correlograrns canot be quantified, SM and Mainland muskoxen clearly have a different relationship with distance, particularly at the shorter distance classes. For example, at - 200 km the rm in SA1 muskoxen is significantly negative whereas Mainland rm is not different from zero. Also at 300 km the rm in SA1 muskoxen is significantly positive whereas Mainiand rm is no different from zero. We suggest the difference in pattern between the Arctic island muskoxen and the Mainland muskoxen GMA is a result of a water effect. Each Island distance class is expected to include at least 62% water separated muskox pain: in NA1 and SA1 muskoxen 382 of 56 1 and 16 18 of 2628 muskoxen pairs straddle a watenvay respectively. In Mainland muskoxen no pairs straddie a watenvay. DISCUSSION Swnmary of Findings Our initial results based on an Arctic Island vs. Mainland analysis were contradictory. The slope of the simple linear regression of Dsa on geographic distance is greater in Arctic Island versus Mainland muskoxen - suggesting the Arctic Ocean rnight impede muskoxen movement. On the other hand, with a negative Water and a significant Water*Distance effect, the multiple regression analysis indicates the Arctic Ocean facilitates muskox movement among the Arctic Islands. Finally, a varying role of the Arctic ocean throughout the range of the Island animals is suggested by the cornparison of Mainland and Arctic Island muskoxen in a GMA analysis. When these data are re-analysed taking into account the histoncal genetic stnicture in Arctic island muskoxen, the results from the three analyses make sense and show an Arctic Ocean that can either expedite or retard muskox movement relative to continuously distributed mainland muskox. Multiple regression indicates the Arctic Ocean expedites movement between the Arctic islands in NA1 muskoxen. This is not the case in SA1 muskoxen where the Arctic ocean appean to have no effect on muskox movement (see Table 4-3b). Finally the GMA results show a varying role for the Arctic Ocean in the movement of muskoxen between Arctic Islands in SA1 muskoxen depending on watergap. Insufficient data exist for GMA analysis of NAI muskoxen at Iûûkm. Interindividual Genetic Distance and Varying Geographic Scale Elucidating the varying role of Arctic ocean channels is only possible in muskoxen with the high resolution of individual microsatellite genotypes which permit the estimation of pairwise genetic distances. In this regard DsAshould be considered an initial estimate of pairwise genetic distance. The distance assumes an infinite allele mode1 and is non-Euclidean. However it is conceptually easy to undentand and in low variability species like muskoxen, its formulation suggest it may provide an accurate estirnate of relative painvise distance. Although we followed other authors and used DsA (Bowcock et al. 1994; Goldstein et al. 1999), Our conclusions can also be corroborated with other estimates of intenndividual genetic distance (Smouse and Peakall 1999). Along with the large number of pairwise genetic distances from microsatellite data and the potentid for partitioning out of the effects of different waterway, GMA allows the investigation of the relationship between genetic and geographic distance at different scales. In these analyses, a large number of data points in small distance classes cannot mask different relationships at larger scales (Legendre and Fortin 1989). In our study, this property is particularly useful as most Arctic islands were sampled on a local scale resulting in by far the largest number of pairwise distances in the O - 100 km class (data not shown). As a result, this class contributes substantially to the significance of the simple linear regression and is likely to be a major reason for the hypothesis of equal in the simple linear regression among NAI, SA1 and MAINLAND muskoxen. Two concetnr Geographic Distance md Genetic polymorphim Concems that our use of Euclidean distances and the large difference in genetic polymorphism between Arctic Island and Mainland muskoxen could undermine Our conclusions are probably unfounded for a least two general reasons. Geographic distance The use of Euclidean geographic distances means we have probably overestimated BNAI uable 4-2b). The many glaciers in this range means the Euclidean distances between pain of muskoxen likely underestimate the distance a muskox would have to travel to get from A to B. This is particularly ûue for any distance estimate between Greenland and non-Greenland muskoxen as only the edges of Greenland are free from the ice cap. As a result the distance we use, for example, for a Greenland (GD) - Grise Fiord (GF) pair, certainly underestimates the distance muskoxen would have to travel between the two locations. Thus, the tme regression dope in NA1 muskoxen is likely lower than our estimate, meaning it is probably significantly lower than the Mainland and possibly SA1 slopes, which would then agree with the negative Water effect in the multiple regression analysis. In contrast, in both the Mainland and Southem Arctic Island areas there are no substantial glaciers or other impassable topography between muskox pairs. At this stage we think it best to be consistent among lineages by using Euclidean distance for al1 geographic distance caiculations. Genetic polymophism Although the lower levels of genetic variability in the Arctic Island relative to Mainland lineages can depress DSAper unit km in the former relative to the latter, this rnay only affect the conclusions from simple linear regressions (Table 4-la). The more heterozygous a taxon the less likely individuals are to share the same alleles hence the pater the expected DSA. This leads to the possibility that the lower P in the Arctic Islands is a result of diminished heterozygosity and not increased genetic exchange. Low genetic variability coupled with the underestimation of tme geographic painvise distance (see above) may explain the lower simple linear regression pNM. However, the multiple regression analyses are conducted for Arctic Island muskoxen only, and the cornparison between water-separated and contiguous muskox pain in these lineages removes the effect of low genetic polymorphism. Finally, since these potential effects on DSAare present in al1 distance classes, the changes of sign in the GMA of SA1 muskoxen at short distances is not an artifact of low genetic variability and supports a conclusion of a varying role in the Arctic Ocean in this lineage. The Varied Rote of the Arctic Ocean Results of this study indicate the Arctic Ocean does not appear to be a generally important impediment to the movement of muskoxen (Figure 4-1). Instead its effects Vary across the Arctic Island muskox range with a generally expediting role in NA1 muskoxen and a retarding and expediting role in SA1 muskoxen. These findings rnay be tme, but two specific concems remind us that these results must be regarded as preliminary. Fint, in coding the presence of waterways as O or 1, we assumed waterways are of equal length and that ice conditions are the same between al1 Arctic Islands. From Figure 4-1 it is obvious that the lengths of the waterways among Arctic islands are not equal. Similady, the ice conditions, may vary considerably making some Arctic Ocean crossings a lot more diffrcult than others [Anne Gunn pers. corn. 20011. A possible solution would be to incorporate different waterway attributes as added variables in a more complex multiple regression analysis. Our limited sample coverage means the data points in the caiegones of the different variables would be small, hence inferences of significance for added affects would be suspect at this stage. The second reason for considering these results as preliminary is that Our linear regression models may not be the best analytical tool for addressing genetic exchange of muskoxen across their landscape. In general littie variation in DsAis explained by either linear or multiple regression models. The highest value - R' = 0.333 for simple linear regression of al1 Arctic Island muskoxen - was largely due to the hierarchical structure in this taxon and decayed to R' = 0.1 10 in NA1 and R~= 0.033 in SA1 when each lineage was analysed independently. The coding of the presence or absence of the Arctic Ocean of water marginally improved the fit of our linear models as R' values increased from 0.1 10 to 0.191 in NAI and 0.033 to 0.072 in SA1 (Tables 4-2b and 4-3b). A major reason for the low explanatory power of these models is the varying role of the Arctic Ocean. Evidence for this role is largely from GMA where the data are repartitioned over many different scales and the analysis is sensitive to deviations frorn an isotropie Water effect - an implicit assumption in linear regression models. The role of the Arctic Ocean in facilitating genetic exchange among NA1 animals may result fiom patchy food distribution coupled with the presence of large glaciers and a rugged landscape. If the distances among good habitat patches are greater than the shorter lengths of the Arctic Ocean separating the islands in the NAI range, and if the ice is easily traversable, muskox movement between food patches via sea ice may actually be favoured. For example, muskoxen on Axe1 Heiberg Island and Ellesmere Island are separated by a maximum distance < 10 km of water. On the other hand for the SA1 lineage, the distribution of food for muskox is not intermpted by glaciers or rugged terrain. However, the length of water between Bathurst Island and Banks and Victoria Islands is > 50 km. Thus for this lineage the stretches of Arctic Ocean between islands are great in cornparison to distances between within island food patches. If the ice between these islands is not easily traversable, movement across these waterways will be infrequent. Finally it is important to note that in spatial autocorrelation studies of NA[ rnuskoxen at 200 km (Chapter 5), the area of positive autocomlation is greater in NA1 vs. SA1 muskoxen which is consistent with a facilitating role of the Arctic Ocean in this lineage. An extreme example of the impeding role of an Arctic Ocean is the watergap between Banks and Victoria Island - part of the range of SA1 muskoxen - and the Mainland. This stretch of ocean was not included in the above analysis because it is the defining line between Arctic Island and Mainland muskoxen. This watergap has impeded genetic exchange so as to maintain siknifcant different genetic differences among the Mainland and Arctic Island muskoxen and we found no SM or MAINLAND muskoxen mis-assigned to each others lineage (Chapter 3). The lack of exchange across this waterway was confimeci in a more detailed study of another 86 animais from Kugluktuk and Surrey lake (near Kidjuut Lake) with a subset of 9 of 11 microsatellite loci used in this study (L. Mutch unpl. data). Here only one SA1 muskox was found among mainland muskoxen From Kugluktuk - and this Likely reflects muskoxen that were forced over the ice 7 years ago by a local hunter (Anne Gunn pers. comm. 2000). No other Arctic waterway seems to have played such a significant role in recent muskox evolution. In keeping with a varying role of the Arctic Ocean, the gap between Cornwallis and Bathurst Island (SM muskoxen) and Devon Island (NAI muskoxen) did not significantly impede muskox movement as 2 muskoxen found on Bathurst (SA1 muskox) onginated on Devon (Chapter 3). Conclusions and Implications The varying eRect of the Arctic ocean on the movernent of muskoxen among the Arctic Islands suggests muskoxen on islands do not consistently experience less genetic exchange with their conspecifics on other islands when compared to Mainland muskoxen. As a result, the contrast between Arctic Island and Mainland, and water separated and contiguous Arctic island muskoxen cannot immediately be used to examine the consequences of fragmentation in large ungulates. This study indicates that for most waterways, in the SM range, the specific role of Arctic ocean cannot be predicted Further characterization will require estimates of genetic exchange among each pair of Islands and a cornparison with similar estimates over contiguous land These values may be best calculated using asymmetric pairwise Nrn methods (Beerli and Felsenstein 1999) or fixed mode1 assignment probabilities (Paetkau et al. 1995). In contrast most Arctic Ocean waterways are expected to expedite the movernent of NAI muskoxen relative to contiguous land in this range. Of particular intenst is the role of the Parry Channel separating the more southerly Arctic Islands (e.g. Banks, Victoria, Somerset, Prince of Wales) frorn the more northerly Islands (Melville , Bathurst, Cornwallis and Devon). Other than the gap between Banks Island and the Mainland this waterway is the widest waterway among the Arctic Islands and in Our limited dataset is straddled by membea of the SA1 lineage. The immediate implications of these results are two-fold. In each of the three muskox lineages, muskoxen within 100 km of each other are genetically related. In Mainland, NA1 and SA1 muskoxen the rw values for this class are al1 positive at 0.25, 0.38 and 0.23 respectively. At distance classes beyond ~100km each muskox lineage has a different relationship between DsA and geographic distance. In continuously distributed populations, the largest distance class with positive autocorrelation is regarded as a coarse estimate of the neighbourhood area (Sokal 1986). Although rm and autocorrelation statistics are not identical, GMA is a good proxy for this analysis allowing the use of 100 km as an initial estirnate of a meaninghil genetic unit (Legendre and Vadour 199 1; and Smouse pers. cornm. 2000). We refine these estimates with autocorrelation of the Smouse and Peakall(1999) distance in another study (Chapter 5). The second implication involves anticipating the consequence of Global warming. In the western Arctic, the Arctic Ocean is expected to warm and reduced ice cover will make passage across waterways between SA1 islands more difîïcult, reducing genetic exchange in a genetically depauperate taxon (Maxwell 1997). On the other hand, the Northem and Eastern Arctic is expected to cool and implications for the generally expeditious role of the Arctic Ocean are unclear (Maxwell 1997). The impacts of these changes on other large mammals can also be anticipated. For example polar bear Ursus Arctos one can anticipate a northward movement of polar bears to take advantage of more persistent sea ice for feeding opportunities. ACKNOWLEDGEMENTS We especially thank D. Michaud and C. Davis for invaluable assistance in the laboratory. Thanks also to J. Kushny and L. Mutch for laboratory assistance. We thank S. Akeeagok, P. Aastrup, L. Coady, E. Coleman, M. Forchhammer, J. Hunter, J. Kuneyuna, T. Lockhardt, R. Mulder, J. Nishi, and A. Williams for assistance with sample collection in Canada and Greenland. This study would not have been possible without the diplornatic touch of our colleague Anne Gunn who also provided useful feedback on this document. Special thanks to the venerable F. Miller who provided valuable sarnples and logistic help. We thank J. Pither for writing the randomization programmes to test the difference in slope. Financial support for field work was provided by Polar Continental Shelf Project of the Geological Survey Canada, and Northem Students Training Program of the Department of Indian and Northem Affin, Govemment of Canada to PlvCdG. The laboratory work was hinded by a gant from the National Research Council of Canada to PTB. FIGURE LEGENDS Figure 4-1. Geographic Iimits and genealogical relationship within the muskox Ovibos moschatus based on microsatellite differentiation (Chapter 3). Whereas the support for the Mainiand - Arctic island subdivision is unequivocal, the weaker support for the two Arctic Island lineages (the Northem Arctic Island (NAI) and Southem Arctic Island (SAI)) is npresented by the dashed Line. represents either the location of the community that provided muskox samples with or without specific geographic coordinates for each sample (BL, GF, KU, KL, SH and WB), or the approximate center of a collection of muskox collected by resemhers (BI, GD, NE, LK). V represents single samples FR-2PW-4 and TH-27. Geographic CO-ordinatesand sample sizes for this study are listed in Table 4-1. (see text for more details and Appendix A for individual CO-ordinates) Figure 4-2. Al1 directions correlograms of r, for inter-individual DsAfor 1 1 variable microsatellite loci and geographic distance for different muskox lineages: Al1 Arctic Island Muskox (a), Mainland (b), Northern Arctic Island (c) and Southern Arctic Island (d). Distance classes are - 1OOkrn (text for details). Al1 correlograrns are globally significant for each lineage at the their respective Bonferroni corrected a =O.OS/[# classes]. Al1 three correlograrns show significant positive ryx between genetic distance and geographic distance from O to - 100 km. For subsequent distance classes the sign of r, and its associated significance differ among the lineages (see text for details). Significance of r, values are calculated using the t statistic of Mante1 (1967). w = r~x significant for distance class (P c O.OS), O = r, informative (n 27) but not significant for distance class (P < 0.05) and * = too few data points (n 5 6) for distance class to be informative. BarrengrouncUMAINLAND muskox SA1 muskoxen a NAI muskoxen Figure 4-1 GMA correlogram for all Arctic Island muskoxen Distance in km Figure 4-2a GMA correlogram for Maidand muskoxen 500 lûûû 1500 2000 2500 Distance in km Figure 4-2b GMA correlograrn for Northem Arctic Island (NAI) muskoxen 500 lûûû 1500 2000 250 Distance in km Figure 4-2c GMA correlogram for Southem Arctic Island (Sm muskoxen 500 lûûû 1500 2000 2500 Distance in km Figure 4-2d The different levels of microsatellite variation across 14 variable dinucleotide microsûtellite loci in Arctic Island O. tn. wrdi und mainland O. ln. nzoschatus (Chapter 3). There is evidence for subdivision of ihc Arctic lsland O. m. wûrdi into two lineages, the Southern Arctic lsland lineage (SAI) and the Northern Arctic Island lineage (NAI). Genetic polymorphism estimates are shown for these two lineages. Unbinsed estimates of expected heierozygosity (Nei and Roychoudhury 1 974) and their standard errors are shown. Pio = probability of identity as defined in (Paetkau et al. 1998). Also shown are the current census size estimates of each lineage (duta inferred from (Fournier and Gunn 1998; John Nagy pers. comm. 1999) Lineage Sample Expected PID # of Census Size Size He~rcxz~gosi t y Alleles Mainland 6 1 0.535M.068 1. ISE-08 58 24000 Arctic Island Muskoxen 111 0.423&û.002 2.19E-05 47 1 19000 Southern Arctic Island Muskoxen 75 O. 247I0.028 6,20E-04 35 1 00000 (SA0 Northern Arctic Island Muskoxen 36 0.294I0,049 3.89E-05 40 15000 (NAI) Table 4- l b, Samples sizes and sample locations used in this study (see also Figure 4-1). For samples collected by the Hunter and Trapper Council of n single comrnunity, the community location was used whereas for sarnples collected by the authors and other researchers, the centrepoint of a nearby group of samples was used (sec texi for details). The sampling locations are ordered from North to South. The assignment of these populations to Arctic Island or Mainland groups is also shown. The Arctic Island muskoxen are funher assigned to one of two putative lineoges: NA1 = Northern Arctic Island Lineage or SA1 = Southern Arctic Island Lineage (Chapter 3). The three extra sumples refer to individuals from the Thelon Game Sanctuary (MAIN),Fort Ross on Somerset Island (NAI) and the northwest shore of Prince of Wales Island (SAI). Sampling Loc~tion Longitude Latitude N Mainland 1 Arctic Island Northern Ellesmere Arctic Island (NAI) Grise Fiord Arctic Island (NAI) Bathurst Island Arctic Island (SAI) Greenland Arctic Island (NAI) Sachs Harbour Arctic Island (SAI) Kidjuut Lake Arctic Island (SAI) Wellington Bay Arctic Island (SAI) Kugluktuk Main land Gjuo Haven Mainland Baker Lake Müinlund Lutsel Kc Mainland Table 4-2û, Results of simple linear regression of DsA(Bowcock et al. 1994) on geogrnphic distance for pairs of individuals from the Arctic Islands and the mainland. The significance of each regression was evaluated using a permutation procedure in GENEPOP v 3 (Raymond and Rousset 1997). Both groups show significant positive regression of genetic divergence and geographic distance (P<0.001). Arctic Island muskoxen have significantly greater divergence per km than Mainland muskoxen. The 111 is the paromeiric absolute t value of the difference between PAmtici,,.,,~ and PmoinImd.Signific~nce is detennined through randomization procedures (see text for details), Regression of qAon geographic distance (km) -- -- Lineage # of ind, R~ a (intercept) b (slo e) P (significance) kS Mainiand 5 1 0.036 0.439 6.87E-5-t 1 E-5 < 0.00 1 Cornparison of regression slope of DS A on geognphic distance (km)bet ween Arctic Island and Moinland muskoxen original 111 P (signi ficance) 3.09 Table 4-3a Multiple Regression of DSAon geographic distance and the presence or absence of water between Arctic Island and Greenland muskoxen. The presence or absence of water was coded as 1 or O respectively. The linear mode1 is significant, however the effect of Water is negative with the presence of a waterway between muskoxen pairs resulting in decreased DSAin cornparison to those pain not separated by the Arctic Ocean. The interaction term Distance*Water is also significant. ANOVA Source DF Sum of Squares Mean Square F Ratio Prob. > F Mode1 Error Total Parameter Estimates and significance Term Estimate Std Error t-Ratio Prob.>lti Std Beta Intercept 0.253 1 0.003 I 8 1.95 <.O001 0.00 Distance in Km 0.0002 0.0000 14.32 <.O001 0.96 Water [0-11 -0.0306 0.003 1 -9.9 1 c.0001 -0.13 Distance*Water [O-11 0.0001 0.0000 5.77 <.O001 0.40 # of observations 567 1 Table 4-3b. Multiple Regression of DsAon geographic distance and the presence or absence of water in the two putative Arctic island muskox lineages - NA1 and SAI. The presence or absence of water was coded as 1 or O respectively. The linear model is significant in both lineages. In NA1muskoxen the effect of Water is significantly negative with Distance*Water dso significant. In SA1 muskoxen both Water and Distance*Water are not significant. R~values indicate less variation in DsAis explained by the 2 variable Iinear model in either of these lineages, than in al1 the Arctic Island muskoxen combined (see Table 3a). Source Sum of Square Mean Square F Ratio Prob. > F Northem Arctic Island Mode1 Error Total Southern Arctic Island Mode1 Error Total Parameter estimates Term Estimate Std Error t-Ratio Prob.>l Std Beta Northem Arctic Island Intercept Distance Water [O- 1] Distance*Water [O- 11 Southern Arctic Island Intercept Distance Water [O- 11 Distance*Water [O- 11 # Obs. Northern Arctic Island Southern Arctic Island Chapter 5 USING GENETICS TO EVALUATE CONSERVATION PRACTICES FOR MUSKOXEN OVIBOS MOSCHATUS: EVIDENCE FROM MICROSATEIUTES PETER J. VAN COEVERDEN DE GROOTI*' AND PETER BOAG ' 1. Department of Biology, Queen's University, Kingston, Ontario, K7L 3N6 Canada 2. Corresponding author, email peten'@ biobfl.~~eensrrca ABSTRACT After surveying variation at 14 microsatellite loci in 158 muskoxen from Nonhem Canada and Greenland, we used the method of Petit et al. (1998) to determine the relative contribution of each of the 1 1 populations to the genetic diversity of three muskox lineages we identified earlier. In addition we determined the area of positive autocorrelation - a correlate of dispersal - in each of MAINLAND, Northem Arctic Island (NAI) and Southem Arctic Island (SAI) muskoxen. We found muskoxen from the Thelon Game Sanctuary to be most diverse of al1 muskoxen and muskoxen from Bathurst Island being the most diverse of Al1 Arctic Island muskoxen. Also Mainland muskoxen seem to have relatively lower dispersal compared to SM muskoxen, 195 km versus 320km respectively. Too few NA1 points exist for us to make any definitive statements about dispersal in these muskoxen. Both MAINLAND and SN are not likely to be at quasi-stationarity - a measure of short term demographic equilibnurn. As a result their areas of positive autocorrelation are expected to increase with time. Using these data and the three major lineages we described earlier we evaluated muskoxen conservation and management plans. Our findings were: 1) Al1 three muskox lineages are protected within a conservation area 2) In two of the three lineages, MAINLAND and SAI, the most diverse populations we sarnpled currently or are likely to receive some protection. 3) One of the conservation areas in the range of MAINLAND and NAI muskoxen appear to be of suficient size to conserve the process of dispersal in their respective muskoxen. Hunting masare generally smaller than the area of positive autocorrelation in MANLAND and SA1 muskoxen. Musbx Conservation: A Unique Large Ungulate Opportunity The fist stage in evaluating the success of conservation and management practices for any species involves the setting of rigorous critena that should be met to ensure the long tem persistence of the species. In the case of large mamrnals, these cntena can include many different considerations, for example estimating minimum viable population for the species (MW)(Caughley and Gunn 1996), minimizing the impacts of potential epizootics, sustainable harvest limits and the preservation of major genetic subdivisions. Some of these criteria take a long time to characterize, for example an MVP - which requires estimates of variance in birth and death rates which cm only be accurately estimated after many years. Still othen are difficult to accurately determine such as the vulnerability to epizootics. On the other hand, criteria for the success of conservation genetic issues such as identification of major extant genetic divisions, the distribution of genetic divenity within those divisions, and a description of recurrent microevolutionary processes such as gene flow cm be accurately quantified in a short period of time. This makes it possible to ascertain if curent management plans for a taon are likely to meet genetic objectives favouring long term penistence. Unlike most large ungulates, the evduation of al1 three "genetic" critena for successful conservation is possible for endemic populations of the muskox Ovibos rnoschatur in the Canadian Arctic and Greenland. The range occupied by two subspecies of muskox - the white faced muskox O. m wurdi on the Arctic Islands and the banenground muskox O. m. moschatus on the Arctic mainland - is nearly 5 million km2 (see Figure 5-1). Most of the habitat in this range remains unchanged by human activity. The situation is much different for most large ungulates, where the current ranges are fragmented and reduced, preventing the accurate description of historical undisturbed genetic structure and providing little oppominity to observe the pre-fragmentation micro- evolutionary processes. Current Conservation and Management of Endemic Muskoxen Across their range, muskoxen conservation involves protection from habitat changes in National Parks and control of subsistence hunting in the Thelon Game Sanctuary (See Figure 5-2). Henceforth we refer to these as conservation areas. In Canada, three national parks harbour muskoxen. These include Aulavik N.P. (12 000 km') on Banks Island, Quittinirpaaq N.P. (37 775 km2)on Ellesmere Island, and Tuktut Nogait N.P. (16 974 lu$) on the Arctic mainland. There is also a proposed national park, Tuktusiuqvialik N.P. (8 442 km2) on northern Bathurst Island In Canada, the largest tract of area habitable by muskox - much of the large Quininirpaaq N.P. consists of ice fields - is the Thelon Game Sanctuary (38 400 km2)on the Arctic Mainland. The status of this area is currently being evaluated, however aboriginal people (Dene and Inuit) travelling through this area may take muskoxen if starvation is imminent. Much of the range of native muskoxen in North and Northeastem Greenland is included in the National Park of North and East Greenland (972 000 km2) although only 200 000 km2of this park is ice-free and able to support muskoxen. Muskoxen hunting is not allowed in the park, however if there is a need to supply a dog team a maximum of 1 muskox per sled can be taken and current policy States this should be a male if possible. Canadian muskoxen are harvested by the inhabitants of northem communities. Muskox quotas were first allotted to northem communities in 1969 with total tags numbering 252 by 1979 (Fournier and Gunn 1998). As muskox numbers increased, the quota allocations were also raised and currently 13 089 muskox tags are available for use by the local comrnunities, a limit set usually at no more than 58of census size of a given management unit. The quotas are allocated to one of 29 Muskox management units in the Northwest Temtories and Nunavut (See Table 5-1 and Figure 5-2). The units reflect local hunting areas, geographic features and survey areas (Fournier and Gunn 1998). The biology of muskoxen is not knowingly refiected in the spatial limits of these units. To avoid fùrther confusion with management units as defined in the conservation literature, we will rcfer to the 29 units as Hunting Areas (Moritz 1994; Paetkau 1999). Most of the Muskoxen in North and Northeastem Greenland are in the Northeast Greenland N. P. and are not hunted. Limited hunting is ailowed in the southem part of this muskox range. The yearly quota for this areas, known as Jarnieson Land, has ken 150-200 animais for the last few years and this represents between 5 and 10% of the Jarneson Land population (Aastmp and Mosbech 2000). Defning the Criteriafor Evaluation of Conservation and Management of Muskoxen The quantification of the three genetic criteria for evaluating the conservation and management initiatives for muskoxen - description of major genetic subdivisions, distribution of variation within these divisions and estimates of recurrent gene flow - faces two major challenges. First, muskoxen are characterised by low levels of allozyme and mtDNA diversity (Fleischrnann 1986; Groves 1997). For example, in a survey of 697 base pairs of the fast evolving mitochondrial D-loop from muskoxen only 10 polymorphic nucleotide sites were recorded (Groves 1997). These data suggest that polymorphism at the putatively more variable microsatellite DNA in Ovibos may be more informative. Second, comprehensive sarnpling is handicapped by the extraordinarily large range of this species and the great expense of working in the Arctic - particulariy in the more remote Arctic Islands and Greenland. This means population snidies are often limited to a few data points. As we detail below, our individual based andysis is one way of using a relatively small muskox dataset from a broad geographic range. Criterion I: Delineution of major genetic subdivisions of muskoxen Although genetic polymorphisrn is generally low in muskoxen, we found three major divisions in muskoxen using variable microsatellites (Table 52%Figure 5-3, Chapter 2 and 3). In consenration genetic parlance the MAINLAND, Northem Arctic Island (NAI) and Southem Arctic Island (SAI) muskoxen are Management Units because they have statistically different dele frequencies at nuclear loci (Moritz 1994; Paetkau 1999). This designation indicates that these units warrant individual conservation and that muskox genetic divenity and dispersal (see below) be investigated within lineages. The degree to which each of these lineages are conserved by cumnt conservation and management practice is part of the evaluation. Criterion 2: Relative genetic diversity of different muskoxen. To evaluate if conservation areas conserve the most diverse muskoxen, a useful criterion would be estimates of the relative contribution of different sampled areas to the total genetic diversity of each of the muskoxen lineages. Microsatellite polymorphism varies substantially across the three major lineages. With 14 microsatellite loci, estimates of genetic variability range from & = 0.5 1W.026 (SE)in Mainland muskoxen to H, = 0.169 i 0.065 in muskoxen from the Southern Arctic Islands (Tables 3-1 and 3-2, Chapter 3; Nei and Roychoudhury 1974). The extent to which polymorphism varies within each of these lineages remains to be characterized. Recentiy Petit et al. (1998) proposed a measure Cdk),which estimates the relative contribution of a specific population k to the total genetic diversity observed across a study species. Cdk) is partitioned into Cdk) which is the contribution to total diversity of the ph population due to its own diversity and Cdk)due to its divergence. They also advocate the use of Allelic Richness Hg) which measure the number of allele per locus (El Mousadik and Petit 1996). In contrast to the ofien used genic diversity h (Nei 1973a), dg)is sensitive to effective population size and makes no assumptions about the underiying allele frequency distributions. Such an analysis can identify populations that are both more diverse and include more unique dleles than other populations. The fit between geneticdly important populations and existing conservation areas for each of the major groups is a part of the genetic evaluation of cumnt muskoxen conservation practices. Criterion 3: Dispersal - a recurrent micro-evolutionaryprocess Where possible, conservation initiatives should accommodate recurrent genetic exchange among animals. In the context of muskoxen, the use of the common Fn based inter-population estimator of gent flow - Nm - would appear troublesome for two reasons. First, this estimator assumes groups of animals are separated by some distance, that they are resident in their respective locations and that within each population mating is assumed to be random (Wright 1951). It is not clear these assumptions apply to muskoxen. Second, the lack of clearly defined muskox populations within each lineage means population-based analyses of genetic exchange are inappropriate. Muskoxen are mostly found in mixed sex and age herds of 5 to 30 animals, with herds tending to be smallest during the late summer rut when herds tend to be between 5 and 12 compared to 12-30 in winter (Tener 1965; Reynolds 1993). The difficulty in defining a muskox herd is reflected by genetic data. In an additional survey of 86 Kugluktuk (KU) muskoxen separated by up to 270 km for 9 of the rnost variable 14 loci, we found no evidence of herd structure (Van Covereden de Groot unpub data). Further complicating a population-based analysis, is a range wide population dynamic characterized by locally variable muskox persistence times which clearly violates the assumption of equilibrium used in the calculation of Nm (Fems 1977; Barr 1991; Forchhammer and Boertmann 1993; Hutchinson and Templeton 1999). For example, in some parts of the Greenland range muskoxen have changed in density by as much as 50% over a two year period and in other parts persistence is characterized by diesffs and extinction's (Fems 1977; Forchhammer and Boertmann 1993). Similarly, signifcant numbers of muskoxen vacated Bailey Point on Melville Island during the severe winter 1996-97 and many muskoxen are known to have moved to Cornwallis Island during severe early snow conditions in 1973 (Miller et al. 1977; Miller 1988; Miller 1989). The survival of muskoxen forced to make such movements is unknown but substantiai numbers have been found dead on the sea-ice (F. Miller pers. comm. 1999). As an alternative. genetic exchange in muskoxen cm be examined in the context of continuous populations. Spatial autocorrelation of individual genetic and geographic distances can be used to quanti@ the relationship between genetic divergence and geographic distance arnong individuai muskoxen (Sokal and Jaquez 199 1; Epperson 1993b; Epperson 1995a; Hardy and Vekemans 1999) and also to estimate the area of positive autocomlation (Sokal and Wartenberg 1983). The distance between individuais at which the autocorrelation coefficient approaches zero has been used to define the area of positive autocorrelation (Sokal and Wartenberg 1983). This area is correlated with axial dispersa1 in continuous populations (Sokd and Wartenberg 1983; Eppenon and Li 1997; Epperson et ai. 1999) and its size cm be used as guide for the minimum size of a conservation area - the third criterion in the evduation of conservation and management of muskoxen. In the context of continuous populations, a usefbl measure of equilibnum dispersai is quasi-statiunarity - evidenced when a conelogram does not change fiom generation to generation. Simulation data suggest this point is reached after a minimum of 50 generations (Sokal and Wartenberg 1983; Epperson and Li 1996). Importantly, the significance of a recent (within 50 generations) contraction event can be determined using the properties of a correlogram at equilibrium (quasi-stutionarity). First, the assumption of isotropie dispersal across the lineage range means that the addition of extra sarnples should not change the general shape of a correlogram at quasi-stationarity. Second, an increase in geographic scale should result in a decrease in the magnitude of autocorrelation coupled with an increase in the area of positive autocorrelation, while the generai shape of the correlogram should stay the same (Fortin 1999). By using these properties one can determine if the lineage is at equilibnum, and how the important a recent disturbance was. Regular, depamires from short term equilibrium should be incorporated in conservation and management plans. A Genetic Evaluation of Curren t Conservation and Management In this paper we evahate conservation and management of endemic muskoxen with respect to the three criteria: 1) The effectiveness of conservation of major genetic divisions, 2) The conservation of the population(s) that contributes the most allelic richness to each lineage and 3) The size of the conservation I hunting area compared to a lineage specific estimate of the scale of dispersai. To do this we fitanalyze genetic divenity by calculating the contribution of muskoxen from 11 geographic anas to the alleIic richness dg) of each of their respective lineages. We then calculate correlograms for muskoxen in each of the three lineages using pairwise genetic distances from 14 locus microsatellite genotypes (Smouse and Peakall 1999). From this analysis we estimate the area of positive autocorrelation for each lineage. Using these cnteria ahd incorporating data fiom an additional survey based on 13 muskoxen for which only bone samples fiom the Thelon Game Sanctuary were available, Our data show that d 3 major lineages of endemic muskoxen receive protection in existing conservation areas, that the most diverse populations within the MAINLAND and SA1 lineages receive (or will receive) protection, and that one conservation area in each of MADLWD and NA1 muskoxen is of suficient size to conserve dispersal processes. With regards to the 29 Canadian Hunting Areas only 4 are of the sarne size or larger than areas of positive autocorrelation, with dl of these on the Canadian Mainland. This means that by and large, Hunting Areas are not biologically meaningful. Based on these findings we make suggestions for conservation action and provide guiding pnnciples for the proper design of Hunting Units METHODS Samples und their Geography The collection and geographic locations of the 158 muskox samples used in this study are described in Chapter 4. In addition we collected 13 muskoxen bone samples from the Thelon Game Sancniary (See Figure 5-2). Molecular Methods We previously determined the microsatellite genotype for the 158 samples at 14 variable di-nucleotide loci (Chapter 3, Appendix 1). The optimum conditions for the amplification of MX- 1, MX-2 and MX4 (Holm et al. 1999); OMSQ-08,OMS 1-16, OM5 l-l!I,OM53-38,OM54-23,OMS5-O4and OM56-30 (Chapter 2 ), RT-6 and RT-9 (Wilson et al. 1997); BM 1225 (Bishop et al. 1994) and MAF-70 (Buchanan and Crawford 1992) in muskoxen have ken described elsewhere (Chapter 2). Using standard methods (Yang et al. 1997), we genotyped 13 rnuskox bone samples at OM51- 16,OMSS-04,OM56-30 and MX-5. Analyses Comparing microsatellite variability cicross al1 muskox The small sizes of sorne of Our samples suggest two measures of genetic diveaity for Canadian and Greenland muskoxen: the unbiased estimate of expected heterozygosity, H, (Nei and Roychoudhury 1974), and the Probability of Identity (Pm) the probability two genotypes are identicai in a given sarnple (Paetkau et al. 1998). The pam'tioning of genetic dntersity Within the three putative muskox lineages MAINLAND, NA1 and SAI, we cm evaluate the relative contribution of each population to the overall allelic richness dg) (El Mousadik and Petit 1996). The contribution of each sampled population to the total genetic diversity of their respective lineage (CTk,)W~S calculated for the 11 populations. Also the contribution to CW,due to the samples own diversity, Cw, and its divergence, Cakb were calculated (Petit et al. 1998). To standardize the unequal sample sizes in these calculations we used rarefaction to generate similar sizes for al1 samples (Petit et al. 1998). Here, X alleles are randomly selected from each population sample, where X = two times the number of individuals in the smallest population. The smallest sample in our study was 9 for both Greenland and Northem Ellesmere Island samples, and rarefaction in each lineage was conducted at r(g) = 18 for ail muskoxen. Since monomorphic loci contribute no information to the relative diversity of a lineage, only polyrnorphic loci are used. Therefore, MAINLAND muskoxen were analysed for 14, NA1 for 11 and SM for 1 1 loci respectively. In these analyses a negative value indicates that a sarnple's contribution is lower than the mean. These calculations were performed on allelic count data with the program CONTRIB (Petit 1999). Spatial autocorrelation We calculate correlograms based on a measure of inter-individual genetic distance across different geographic distance classes to estimate the areas of positive autocorrelation and to characterize the relationship between genetic and geographic distance for each lineage. Afkr calculating a multivariate genetic distance arnong individual microsatellite genotypes using the method of Smouse and Peakall(1999), these distances among individuals were autocomlated in different geographic distance classes using fh'(Smouse and Peakall 1999). In the calculation of inter-individual distances, the few individuais not scored for a locus were accorded the most common genotype in the lineage. To make meaningful comparisons across lineages, spatial autocorrelation analyses should be conducted at the same scale (Sokal and Wartenberg 1983). The extensive ranges of the muskox lineages - each > 104 km2- and low sampling coverage in each lineage, suggested an initial distance class of 100km. The overall significance of spatial autocorrelation in each lineage was determined using a rnulticlass T~,which evaluates how often 999 randomized datasets deviate as far from the multivariate centroid as does the observed vector of autocorrelation coefficients [of the different distance classes] (Smouse and Peakall 1999). The significance of auto- correlation at specific distances was computed by comparing the observed Sh' with a confidence interval spanning 90 8 of the Sh)calculated from randomized samples of the distance class data (Legendre and Vadour 199 1; Smouse and Peakall 1999). The observed r'" values and the 95% and 5% randornized confidence limits for each distance class are presented in a correlogram. Finally dl analyses were aiso conducted at 200 km to investigate the effect of increased scale on the area of positive autocorrelation and the shape of the correlogram. Al1 calculations were performed on GENAEX (B) (Peakall and Smouse 1998). From these correlograrns we infer the distance at which r'h)becomes not significantly different from zero and we report the Sh' at the fiat distance class. RESULTS Comparative Variability across AI1 Murkox Generally muskoxen from the Mainland showed the highest polymorphism with 14 microsatellites (see Table 5-2b). Baker Lake (BL) muskoxen were the most variable with H. = 0.519 f 0.026 and PD = 1.39 E-08. The least variable sample was from Greenland (GD) with H, = 0.169 f 0.077 and PD = 3.94 E-03. In general, relative heterozygosity values rank similarly to relative PD values, indicating they can be used interchangeably in the discussion of relative genetic variability in muskoxen. Relative Contribution to Diversity MAINLAND muskoxen samples With the four MAINLAND populations analysed for 14 loci, no particular population contributed disproportionately to the overall divenity of the lineage. As anticipated from the description of genetic divenity across dl muskoxen in Table 5-2b, the Contribution Analysis of Petit et al. (1998) indicated that Baker Lake muskoxen contribute most to the overall allelic nchness in MAINLAND muskoxen (Cm,= 4.056; Table 5-3 and Figure Ma). In this sample both the contributions due to allelic diversity and allelic differentiation are positive. The total contribution of Kugluktuk (KU) rnuskoxen to this lineage is at a similar level (CTtk)=3.4%), but in this case it is largely due to the increased differentiation of KU muskoxen. On the other hand, Gjoa Haven muskoxen have a negative contribution when compared to other MAINLAND muskoxen, while Lutsel Ke muskoxen make a positive r(g) contribution of Cnk,= 1.3%. This latter value is Iess than Cm for both BL and KU. Northem Arctic Island (NAI) muskoxen samples In cornparison to MAINLAND muskoxen, there is greater difference in the relative contributions of the three NA1 muskoxen sarnples (Table 5-3 and Figure 5-4b). Grise Fiord (GF) had the largest relative contribution to allelic richness in NA1 muskoxen with Cr*,=7.4%, and this is alI due to merentiation from the other NA1 muskoxen. As expected Greenland had the lowest contribution to allelic richness in this lineage with CT(k,= 0.02%. Southern Arctic Island (SA0 muskoxen samples Muskoxen from Bathurst Island (BI) contribute the most to genetic diversity relative to other samples in the SAI lineage (Cm)= 15.2%; Table 5-3 and Figure 54). The contribution from sample diversity and sample differentiation is similar with = Cmk,= 7.6%. Spatial Autocorrelation When analysed for al1 14 loci, dl correlograms except NA1 at 100 km are globally significant indicating that muskoxen in al1 three lineages are not randomly distributed in space with respect to genotype. However each of the lineages have different relationships between animals and space and each suggests a different area of positive autocorrelation (Figure 5-5, Table 5-4). This area was calculated by squaring the distance where becomes no different €rom zero (Table 5-4) (Epperson 1995a). The small number of sarnples in a given distance class produce relatively broad confidence limits. For each of the conelograrns we follow Smouse and Peakall(1999) and did not plot r'" or confidence limits for the last distance class. UAINLAND muskoxen At a scale of lOOkm the correlogram for the MAINLAND muskoxen is globally significant (T2= 102.739, P c 0.001) with positive autocorrelation in the 100 km distance class. Autocorrelation then genedly decreases with increasing distance classes (Figure Sa),with Sh) at 100 km = 0.128 and becoming not signifcantly different from zero at - 195 km (Figure 54%Table 5-4). The pattern of decreasing autocorrelation is expected if a mode1 of isolation by distance obtains in a continuous population (Hardy and Vekemans 1999). At the scale of 200km the general pattern of positive autocorrelation at small distance classes and decreasing with Iarger distance classes is preserved (Figure 5- 5b). The correlogram is globdly significant (T2= 118.12 1, P < 0.001) with autocorrelation in the fint 200 km = 0.088 and with a)becoming zero at about 350 km Figure 5-31,Table 5-4). NA1 muskoxen The large expanse and small sarnple size (N=34)allow only preliminary inference of the relationship between r "' and distance in NAI muskoxen. At the scale of 100 km few inferences are possible as 3 distance classes - 1000km, l5OOkm and 2300k.m - have no data points and a number of classes have small samples resulting in broad confidence limits (Figure 5-Sc). With empty distance classes, global significance of the correlograrn cannot be evaluated. There is some suggestion of decreasing with increasing distance, as P)becomes no different from zero at 190-2 10km and r at 100 km = 0.265. At 200 km the correlogram is globally significant (T2= 133.14, P c 0.001) and these muskoxen show stronger evidence of isolation by distance. At this scale, becomes no different frorn zero at - 440 km with a value of O. 1 12 at the fmt 200km class (Figure 5-Sb). SA1 muskoxen The spatial autocorrelation of inter-individual distances in SA1 also suggests isolation by distance. The correlogram is globally significant at 100 km (Tt = 80.46, P < 0.001) with P)becoming no different from zero at 320 km and at lOOkm = 0.047 (Figure 5-Sa, Table 5-4). Small sample size in the 301 - 400 km distance class translates into broad confidence limits for this interval at this scale. The general pattern is repeated with 200 km classes. This correlogram is signifcant (T' = 8 1.83, P < 0.001) with fh' becoming no different from zero at 420 km, and Sh)= 0.056 at 200km (Figures-Sb, Table 5-4). DISCUSSION With 14 microsatellite loci, Our analyses indicate that two sampling areas (Baker Lake (BL)and Kugluhk 0contribute the most to allelic richness in the MAINLAND lineage. By contras&single sampling areas appear to contribute most to the allelic richness in NA1 and SAI muskoxen: Grise Fiord (GF)in NA1 muskoxen and Bathurst Island (BI) in SA1 muskoxen (see Figure 5-4). At first glance al1 three muskox lineages appear to show isolation by distance (Figure 5-Sb, d) and have different areas of positive autocorrelation (Table 5-4). The smaller the distance class used in these analyses the better the estimate of autocorrelation over al1 distances and thus the more accurate is the estimate of area of positive autocorrelation (Shapcott 1995; Fortin 1999). In calculating this area, we follow other authors and assume a square bounded on one side by the distance at which is no different from zero (Sokal and Wartenberg 1983; Epperson 1995a). At the scale of 100 km, MAINLAND muskoxen appear to have the lowest area of positive autocorrelation at 38 025 km' with SA1 muskoxen having a larger area of 102 406 km2. The lack of data in the 100 km analysis mean our initial estimate for NAI muskoxen is made at 200 km, which gives a very large estimate area of 193 600 km2. The Recent History of Muskoxen Although muskoxen numben are currently above 130 000 animals (Figure 5-l), numben were low at the turn of the century - panicularly on the Arctic Mainland Banks Island and Victoria island. The two main Rasons for the precipitous decline in numben were overhunting and exveme environmental conditions. Current Mainland estimates are -24 000 (Figure 5-l), however as recently as 1917, these muskoxen numbered as few as 400 to 500 animals (data sumrnarized in Barr (1991)). They were restncted to 4 main areas: the Thelon - Hanbury River basin (in the present day Thelon Game Sanctuary), and pockeis of animals Northeast, Northwest and Southeast of the Thelon Game Sanctuary (Figure 5-6). Most of the survivors were in the current Thelon Game Sanctuary, with estimates there as low as 250-300 animals. These low numben were largely a result of unregulated commercial harvesting for coach fur rugs in Europe as bison numbers had been drastically reduced by this time. From 1860-1916 it is estimated that between 21 000 and 22 000 muskoxen were removed fkom the Arctic mainland (Barr 199 1). Unlike the mainland muskoxen, the low numbers on the Arctic island were probably a result of extreme weather conditions. Muskoxen were almost absent from Banks Island by the tum of the 19' Century (Bam 1991) and in 1930 only a small remnant population of no more than 20 animals remained on Victoria Island (Anderson 1930 in Barr (1991)). Catastrophic ice storms were possibly the reason for the precipitous decline of SA1 muskoxen at the turn of the century (Gunn et ai. 199 1). Recent records suggest that three areas have consistently served as refbgia for SA1 muskoxen dunng extreme weather conditions: Baileys Point on Melville Island, Polar Bear Pass on Bathurst Island and the Thomsen River Valley on Banks Island (see Figure 5-6; Miller et al. 1977; Thomas et al. 198 1; Barr, 199 1). In contrast to Mainland and Banks and Victoria Island muskoxen, details of recent population fluctuations and hence the relative effects of hunting and variable environments across the range of NA1 muskoxen are less known (but see Fems 1977). Although the remoteness of the lineage may have translated into reduced hunting pressure, exploitation of Ellesmere and Axel Heiberg Island muskoxen between 1875- 19 17 may have been signifiant with 1252 published accounts of harvested rnuskoxen (Barr 1991). Sirnilar to SA1 muskoxen there are three areas in the NA1 Iineage which appear to harbour muskoxen dunng times of extreme weather conditions: Truelove Inlet on Devon Island, Fosheim Peninsula on Ellesmere Island and Mokka Fiord on Axel Heiberg Island (Figure 5- 6; Thomas et ai. 198 1). A more inclusive genetic description of MAINLAND rnuskoxen The above considerations suggest that the analysis of MAINLAND muskoxen is incomplete without samples from the Thelon Game Sanctuary. Since no muskoxen are legally hunted in the Thelon Game Sanctuary and because it is so remote, fresh tissue from these animals is difficult to obtain. We used a collection of bone samples from 13 individuals to assess Thelon muskox variability. Genotyping from this material is dificult and only 4 of 14 microsatellite loci worked reliably. None-the-less. these data suggest the contribution of these muskoxen to MAINUND allelic richness far exceecis any of the other four locations, while autocorrelation analysis of these limited data indicates MAINLAND muskoxen are not at equilibrium (see below). The total positive contribution to allelic richness of Thelon Game Sanctuary samples is = 22.8645, split between a large diversity contribution = 9.4% and a large differentiation contribution Cwkj=13.5% (Table 5-3b and Fig 5-7b). Al1 other samples had negative Cm. Similarly, the inclusion of the Thelon Game Sanctuary samples results in a qualitatively different conelogram compared to the originai 4 locations for the same 4 loci at both lûûkm and 2ûûkm scales flable 54, Figure 5-8a and b). The correlograrns including the Thelon bone data were globally significant at both 100 and 200 km scales with T~= 53.45, P c 0.005 and T' = 41.986, P < 0.005 respectively. The exclusion of the Thelon data from the more limited analysis of 4 microsatellite loci resulted in non- significant correlograms at both des. As we discuss below, this is evidence that MAINLAND muskoxen are not at quasi-stationariry. Similar to the MAIi&UW lineage, a more complete SA1 analysis should include animals fiom Baileys Point. Unfortunately these data are not available. Departures from Quari-Stationarity - a Measure of Short Term Equilibrium Muskoxen are likely to be at evolutionary equilibrium with respect to colonisation of their Arctic range after the withdrawal of the Laurentide ice-sheet, but it is unlikely they are at demographic equilibrium with respect to a more recent history of contraction due to hunting or environmental catastrophes at the turn of the century. As a result it is possible that current areas of positive autocorrelation reflect recolonisation of former ranges after these events rather than dispersal at equilibrium under average environmental conditions. Further to this, muskoxen exhibit very different recolonisation rates. For exarnple muskoxen have been recorded covering hundreds of kilometen in a few years when colonising new ranges in Northern Quebec, Canada (Le Henaff and Crete 1989). Elsewhere, the eastward rate of spread of MAINLAND muskoxen was estimated at 13 km/year during the 1970s and 1980s (A. Gunn unpublished data). Hence it is possible that differences in areas of positive autocorrelation reflect differences in recolonisation rate in different habitats. The recency of the contraction due to overhamesting suggests that MAINLAND muskoxen are not at equilibrium. If we are to assume a generation time of 3-4 years in Ovibos, only 20 or so generations have passed since the ranges of these animals were severely restricted on the Canadian mainland - significantly less than the 50 or more generations needed before quasi-stutionarity is reached (Tener 1965; Sokal and Wartenberg 1983; Eppenon and Li 1996). This theoretical expectation is confirmed with the addition data from the Thelon bone samples. When four microsatellite loci are anaiysed, the exclusion of the Thelon bone sample results in a correlogram that is not globaily significant (Figure 5-8). In addition, the correlograms which include Thelon samples do not have the same shape over 100 and 200 km scales. Analyses from 4 loci can still be considered valid as most simulation studies deal with one or two microsatellites (Eppenon 1995b; Epperson 1995a; Eppenon and Li 1997) and the number of microsatellite loci used in field studies to date is between 6 and 7 (Chikhi et ai. 1998; Streiff et al. 1998; Reusch et al. 1999). As a result. the initial inference that isolation by distance obtains in MAINLAND muskoxen is pre-mature and it is likely that the conelograms for this lineage refiect a significant recolonisation component. Further analysis of polymorphic loci in this lineage is unlikely to help clarify the nature of the correlogram at equilibrium - more time is needed. The recent contraction of SA1 muskoxen on Banks and Victoria Islands also means that too few generations have passed for SAI animals to reach equilibrium. The depmre from this state could be confirmed with the inclusion of animals from Melville Island - with a recent (1997) estimated census size of 2200 - and a larger sample than the single animal from Prince of Wales Island - with recent (1995) estimated census size of 5300 - in SA1 correlograms (data summarized in Fournier and Gunn (1998)). Simila.to MAINLAND muskoxen. this lineage may not be characterized by isolation by distance and the comlogram likely includes a significant recolonisation component. Unlike MAINLAND and SA1 muskoxen, few predictions regarding short terrn equilibrium in NA1 muskoxen can be made. On the one hand, Canadian and Greenland muskoxen in this lineage were not hunted as heavily as MAINLAND muskoxen (summarized in Barr (1991)). Although fur hunters began to operate in north and northeast Greenland in 1908 and continued until 1960, these hunters only took muskoxen for food for themselves and their dogs (Mikkelsen 1994). Although the National Park was established in 1974, hunting restrictions were set in force as early as 1950 in Greenland. On the other hand, these muskoxen do experience nanirai fluctuations as evidenced by Northeast Greenland muskoxen which experienced a substantial natural decline and increase in number through the 1980's (Boertmann et al. 1992; Forchhammer and Boertmann (1993); see also Fems (1977)). Our sample size is small and only increased sarnpling of this lineage will determine if quasi -stationnrity obtains and will provide a reduced area of positive autocorrelation. Future changes in esthates of area of positive autocorrelation Although correlograms not at equilibrium can look quite different from those at quasi-stationarity, simulations indicate the approach to equilibrium will see the distance at which becomes zero increase (Sokal and Wartenberg 1983). This suggests that the area of positive autocorrelation will increase in both MAINLAND and SA1 muskoxen as time passes and in the absence of environmentai catastrophes. The calculated areas for these lineages should be regarded as minima, with the areas of positive autocorrelation increasing with time. By contrast, this value at quasi-stationarizyin NA1 muskoxen will be less than the current estimate of 193 600 km2from autocorrelation at 200km. Genetic Evaluation of Current Conservation and Management of Muskoxen The immediate goals of this snidy were to complete an analysis of allelic richness in each of the three muskox lineages and provide an initiai estimate of the area of positive autocomlation for each lineage. With these data we can now evaluate current muskoxen conservation and management practices against the three criteria of 1) effectiveness of conservation of major genetic subdivisions 2) conservation of the most genetically diverse lineages within the major subdivisions and 3) conservation of a lineage specific correlate of dispersal - the area of positive autocomlation. Conservation of major genetic subdivisions Representatives of al1 three lineages are conserved in existing or planned conservation areas (Table 5-5). Muskoxen from the MAlNLAND lineage are afforded protection in the Thelon Game Sanctuary and Tuktut Nogait NP., while NA1 muskoxen are protected in the North East Greenland N.P and Quittinirpaaq N.P., and SA1 muskoxen are protected in the Aulavik N.P. and the proposed Tuktusiuqvialik N.P. With these conservation areas, the major groups resulting from isolation of Arctic Island muskox ancestors in an ice-free refugium on Banks island during the last Glacial maximum of the Wisconsin Glaciation and the subsequent divergence of the two Arctic lineages after the withdrawal of the Laurentide Ice sheet 10 0 y.b.p., are conserved (Chapter 3). Conservation of the most diverse geographic areas within lineages. Those sampling areas which contribute the most to MAWLAND and SA1 muskoxen allelic richness have some sort of protection. e-g. the Thelon Game Sanctuary and the proposed Tuktusiuqvialik N.P. respectively. The Grise Fiord animals are the most diverse of the NA1 muskoxen but currently receive no protection. However muskoxen from this lineage are well preserved outside Canada, in the National Park of North and East Greenland and Quininirpaaq N.P. Conservation of dispersal opportunities The size of at least one of the protected areas in MAINLAND and NA1 muskoxen are on a scale close to Our different estimates of area of positive autocorrelation for the two Iineages. For MAINLAND animals the large Thelon Garne Sanctuary is of a similar scale to the calculated area of positive autocorrelation for this iineage, but the smaller Tuktut Nogait N.P. is not (Table 5-5). However these areas are expected to increase at qua.siistutionurity at which time the Thelon may be too small. Although much of the immense National Park of North and East Greenland is covered by glacier, 200 000 km2 is ice-free which is larger than the conservative estimate of positive autocorrelation for this lineage of 193 600 km2. Quittinirpaaq N.P. is smaller than this estimate. The two National parks in the SA1 range - the existing Aulavik N.P and the proposed Tuktusiuqvialik N.P. - are much smaller than the scale of dispend in this lineage. The lack of fit will become greater as this lineage approaches equilibrium. It must be noted that in these analyses we do not consider the shape of conservation areas (OCHunting Areas - see below) when comparing them to a square area of positive autocorrelation. In large hunting areas, for exarnple on Banks Island and Mainland, the shape is likely not important, however where the muskoxen disperse over narrow coastal comdors, for example in Greenland, the actual geometry of population distributions may be critical. In sumrnary, Our results suggest that much of the extant genetic diversity in Ovibos moscham is conserved and in two of the thelineages, at least one conservation area is the same size as the area of positive autocorrelation. Specifically: 1) representatives of the three muskox lineages are conserved; 2) the most diverse populations receive some protection in the MAINLAND and SA1 lineage but not the NA1 lineage; and 3) at least one conservation area is of the same scale as the area of positive autocorrelation in the MAINLAND and NA1lineages, although the 2 parks in the SA1 range are smaller than the area of positive autocorrelation in this lineage. At this juncture it is instructive to compare the above evaluation with that anived at using the criterion of reciprocal monophyly of mtDNA aileles to identifj Evolutionary Significant Units (ESU)or allele frequency differences to define Management Units (MU) - for conservation (Moritz 1994). Based on the very limited mtDNA, polymorphism al1 muskoxen fom one ESU. If the preservation of a Muskoxen ESU were the prime objective, the preservation of any one of the 6 conservation areas would be sufficient from a conservation genetic perspective (Groves 1997). In this context, the three lineages may be best considered as Management Units in the traditional sense (Moritz 1994) and we have identified areas which harbour the most diverse rnuskoxen in these uni6 and an initial guide to the size of conservation areas. Implications for Hunting Areus. We did not try to determine if each of the current 29 Canadian Hunting Areas are genetically distinct, but rather we attempted to determine an appropriate size for these areas. As Figure 5-2 and Table 5-1 demonstrate, these Hunting Areas Vary substantially in size across the range of muskox and many are smaller than the area of positive autoconelation within the different lineages. As a result of our snidy, we provide the following general biological guidelines for cumnt and future muskox Hunting Areas. Hunting Areas should not straddle different muskoxen lineages. In this regard, the 3 hunting areas that encompass Prince of WaIes, Someaet Island and the Boothia Peninsula were not well sampled in Our study and the assignment of these muskoxen to any of the three lineages remains unclear. Although we have no samples from the hunting area on Melville Island, these are probably SA1 muskoxen. The smaller area of positive autocorrelation in MAINLAND muskoxen (38025 km2)means that 4 of these hunting areas are larger than the area of positive autocorrelation and hence are of the same scale as dispersal in these animals. Furthemore, 5 of these areas are > 30 000 km', near the size of the area of positive autocorrelation. The smaller areas should not be regarded as biologically meaningful groups of muskoxen. The larger area of positive autocorrelation in NAX muskoxen, means the 4 Hunting Areas in this lineage each appear to be smaller than the respective area of positive autocorrelation (193600 krd). Although we have attempted to show the area of positive autocorrelation is likely to decrease with proper sampling, it is likely these areas will remain smaller than this estimate. The current estimate of positive autocorrelation of 102 400krn2 for SA1 muskoxen means that no Hunting Area within this lineage is large enough. Although some of the units are near this size, the smaller ones are not biologically meaningful (See Table 5.1 for further details). Suggested short tenn actions Based on Our evaluation, we make the following four suggestions: 1) Since the Thelon Game Sanctuary likely harbours the most diverse muskoxen and is the only Conservation Area in Canada that is of the sarne scale as Our estimate of dispersal for any of the three lineages, it's crucial role for muskox conservation should be recognized during any review of its status. 2) The creation of Tuktusiuqvialik NP. is of high priority as it represents a contact zone between SA1 and NA1 muskoxen (Chapter 3) and dong with Grise Fiord animals contains the most variable of al1 Arctic Island and Greenland muskoxen. Efforts to increase the size of this park, so as to encompass an area of positive autocorrelation for SAI (or NAI muskoxen) should be made so as to preserve dispenal opportunities for these muskox in order to prevent increased inbreeding. 3) Melville Island muskoxen need to be characterized as it is possible that these muskoxen have increased diversity relative to other SA1 muskoxen and their characterization is critical to the accuracy of estimates of area of positive autocorrelation for SM muskoxen. 4) Boothia, Prince of Wales Island, and Somerset Island muskoxen need to be accurately genoiyped in order to determine their assignment to each lineage. ACKNOWLEDGEMENTS We extend grateful thanks to L. Much for laboratory assistance. We thank S. Akeeagok, L. Coady, E. Coleman, M. Forchhammer. J. Hunter, J. Kuneyuna, T. Lockhardt, R. Mulder, J. Nishi, and A. Williams for assistance with sample collection in Canada and Greenland Special thanks to the venerable F. Miller who provided vaiuable samples and logistic help. Similarly Barry Troke and Parks Canada provided assistance in collecting samples from Northem Ellesmere Island. Direct logistic support for field work was provided by Polar Continental Shelf Roject of the Geological Survey Canada. Direct financial support for field work was provided by the Northem Students Training Program of the Deputment of Indian and Northem Affairs, Government of Canada to PJvCdG. The laboratory work was funded by a gant from the National Sciences and Engineering Research Council (NSERC) of Canada to PTB. FIGURE LEGENDS Figure 5-1. Distribution map of Muskoxen in Canada and Greenland. The white faced muskox Ovibos moschatus wardi is found largely on the Arctic Islands and Greenland whereas the barren ground muskox Ovibos moschatus moschatus is found on the mainland. Numbers of muskoxen are also shown: Mainland muskoxen = 24000, Canadian Arctic Island muskoxen = 108 000 and Greenland rnuskoxen = 1lOûû. (Fournier and Gunn (1998) and Gunn and M. Campbell 2000 unpublished data) Figure 5-2. Protected areas and Management or Hunting areas in the range of naturally distributed Canadian and Greenland muskoxen. Shaded polygons are protected areas: 1 = Aulavik NP. (12000 Inn'), 2 = proposed Tuhsiuqvialik N.P. (8 442 km2), 3 = Quittinirpaaq N.P (37 775 km2),4 = North East Greenland N.P (1 000 MX) km2), 5 = Thelon Game Sanctuary (38 400 km2) and 6 = Tuktut Nogait NP. (16 974 km2). The clear polygons are Hunting Areas (management units). Unequal sampling in these areas is reflected by ** = more than 10, * = less than 5 and a clear area indicating no samples were from the hunting area Figure 5-3. Evolutionary relationships in extant muskoxen based on 14 microsatellites (Chapter 3). MAINLAND refers to the more variable muskoxen on the mainland of northem Canada (Table 5-1 and 5-2). NAI refen to the Northem Arctic island muskoxen found on Axe1 Heiberg, Ellesmere, Devon and srnaller nearby islands and Greenland. SM refers to the Southern Arctic Island muskoxen found on Bathurst Island and the more southerly Arctic Islands. AIso shown are centers of sampling efforts including the center of a sample of bones collected from Thelon Game Sanctuary (See Table 5-2). Figure 54. Contribution to ailelic nchness r(g) of each sample to respective lineages. These analyses surveyed 14 loci with rarefaction = 18. A) MAINLAND: Baker lake (BL) and Kugluktuk (KU) contributed the most to the relative diversity in this lineage with Ct(k)= 4.0 % and 3.4% respectively. B) NAI: Gt%e Fiord (GF) contributed the most to this Iineage with Cm)= 7.4% with the low sample diversity in Greenland (GD) translating to a negligible allelic richness contribution to the lineage. C) SAI: Bathurst Island (BI) was the only sampling location that contributed positively to this lineage Cr@ = 15.2% (see Table 5-3). Figure 5-5. Comlograms of spatial autocorrelation of interindividual genetic distance for 14 microsatellite loci (Smouse and Peakall 1999) and geographic distance in each of the three muskox lineages. Analyses were conducted at 100 and 200 km scaies and the figures include 90% randornized confidence intervals. Al1 correlograms except NAI at 100 km were globally signif~cant.A) Correlograms for MAINLAND and SA1 muskoxen. The vertical lines indicate the infemd distance at which first become no different from zero in each lineage: MAINLAND = 195 km and SA1 = 320km. B) Correlograms for MAINLAND and SAI muskoxen at scaie of 200 km with estirnates of rm' becoming no difference hmzero for MAINLAND = 350 km and SA1 = 420krn. C) Comlogram of NAI rnuskoxen at 100 km with estimates of rm)becorning no different fiom zero at 190-210krn. D) Correlogram of NA1rnuskoxen at 200 km with estimates of becoming no diffe~ntfiom zero at 440 km (see text and Table 5-4 for more details) Figure 5-6. The estimated numbers of muskoxen on Canadian mainland and Banks and Victoria island when muskox hunting for commercial purposes was made illegal in 1917. The total number of mainland muskoxen was estimated to be 400 -500 muskoxen distributed in a number of small groups with the Thelon -Hanbury River basins harbouring the greatest number at 250-300 animais. No animals were believed to be on Banks Island with only 20 or less on Victoria Island by 1930. The estimates of muskoxen for the other Arctic Islands cannot be made for this time period. These data are summarized in Barr (1991). The map highlights areas considered to be criticai refugia dunng extreme weather conditions in the Arctic Islands: Baileys Point (Melville Island), Fosheim Peninsula (Ellesmere Island), Mokka Fiord (&el Heiberg Island), Polar Bear Pass (Bathurst Island), Thomsen River Valley (Banks Island) and Truelove Lowlands (Devon Island) (Thomaset al. 198 1). Locations sampled for this snidy are included as are locations which require sampling: 1 = Boothia Peninsula, 2 = Melville Island, 3 = Prince of Wales Island and 4 = Somerset lsIand (See text for details). Figure 5-7. The contribution to allelic richness in MAINLAND muskoxen of Thelon Game Sanctuary (TH) samples for 4 variable loci and rarefaction = 18. A) The relative contributions of the original 4 sample locations for 4 microsatellite loci. In this analysis Kugluktuk (KU) contributed the most to the relative diversity. In contrast to figure 5-44 Lutsel Ke (LK)had a positive contribution to the lineage and Baker Lake (BL) had a negative relative contribution. B) The results of the same analysis in figure 5-6a but with the inclusion of data froml3 bone samples. In this case the Thelon Game Sanctuary (TH) samples had the only positive relative contribution with the original 4 locations having negative relative contributions. Figure 5-8. Correlograms of MAINLAND showing the effect of including the Thelon Game Sanctuary bone samples on the spatial autocomlation of inter-individual genetic distance based on 4 microsatellite loci (Smouse and Peakall 1999) and geographic distance at 100 and 200 km scales. The ephemerd nature of the second area of autocorrelation at 600 km in the 100 km analysis suggests the lineage is not near quasi- stationarity. Only the correlograms with the inclusion of the bone data were globally significant. A) Correlograms for MAINLAND with and without the Thelon Game Sanctuary bones at 100 km. B) Correlograms for MAINLAND with and without the Thelon Game Sanctuary bones at 2ûûkm. The vertical lines indicate the inferred distance at which r@)becomes ao different from zero in each lineage: 100 km = 200 km and 200 km = 275 km (see text and Table 5-4 for more details) Banengound muskox Figure 5-1 Conservation Areas Figure 5-2 MAINLAND muskox SAImuskoxen NA1 muskoxen Figure 5-3 BL GH KU LK MATNLAND muskox population GD NE GF NA1 muskox population KL SH BI SA1 muskox population Figure 5-4 0.40' -MAIN rCh) , A = 100 km classes upper 90% CL. .5 . SA1 rfhj 0.30 : : for SAI - LAND ! -0.4 1 100 20 300 400 500 600 700 800 900 1ûûû Upper value of distance class in km 1 B = 200 km classes upper 90% C.L. for SA1 I lower 90% CL. for SA1 SA1 Upper value of distance class in km Figure 5-5 0.8 ' h NAI C = 100 km classes o. . - rch' . Cf, 0.6 ' /+ ; -NA1 90% upper 90% CL. : . 0.4' for NAI .::.' Iower 90% CL. for NAi -0.6- 200 400 600 800 1000 1200 1400 1600 1800 2000 2200 2400 Upper value of distance class in km 0.8' D = 200 km classes 0.6' *O*. :-. 0.4' .. *. upper 90% CL. .-*. y for SA1 0.2' Iower 90% C.L. for SA1 200 400 600 800 LOO0 1200 1400 1600 180 2000 2200 2400 Upper value of distance class in km Figure 5-5 Figure 5-6 BL GH KU LK MAINLAND muskox population GH BL KU LK TH MAINLAND muskox population Figure 5-7 - dh)with T.G.S. bones - - flhJ without T.G.S bones upper 90% CL.no bones - with bones 90%CL l \ -4- without bones 90%CL **-*v=-\ loweer 90% CL. no bones K) 300 400 500 600 700 800 90 1000 Upper value of distance class in km B = 200 km classes upper 90%CL. no bones \ lower 90% C.L. no bones 400 600 800 IO00 Upper value of distance class in km Figure 5-8 Table 5- 1, The properties of hunting areas for Muskoxen in the Northwest Territories (NWT)and Nunavut Canada. The bolded numbers refer to those Hunting Areas which are larger than the areo of positive autocorrelation - a correlate of dispersal - for those muskoxen (see text for details). Not al1 hunting areas have estimates of muskoxen. Also included are estimates of population sizes for the Thelon Game Sanctuary and Beaverhill lake. H.A. = the name of the hunting area. Nunavut km2 and NWT km2= the size of the Hunting Areas in Nunavut and NWT respectively. Nunavut and NWT quota = the number of muskox tags the community is allowed on an annual basis in Nunavut and NWT hunting areas respectively. Nunavut estimate and NWT estimate = the number of animals estimlited in the unit including the standard error. Date = the date of the survey. Sources are available from the author. Geographic name H.A. Nunavut NWT Nunavut NWT Nunavut NWT km2 km2 quota quota estimate estimate Date . BE HE South Ellesmere N/MX/O2 20589 60 N/MX/04 4192 4 202W285 1991 N/MX/03 4534 10 Melville Island VMX/O 1 26 1 42 6 223W308 1997 Bathurst Island N/MX/OI 44873 40 126145 1 997 Banks Island IfMW02 68258 1 0,000 4583351 938 1998 Devon Island N/MX/OS 34825 15 400 1 990 Prince of Wales N/MX/06 95683 20 5259I4 14 1995 Somerset Island N/MX/08 1 1488 12 Northwesi Victoria IlMW04 5 1257 750 186513A338 1998 West Victoria VMW03 28890 350 Nort herist Victoria N/MX/07 47497 1 O0 672ûk790 1992 Southeast Victoria N/MX/l 1 48300 1000 187 f Of2035 1999 Southwest Victoria N/MX/ 1 O 30658 1 O0 3934k 1225 1 994 rir wV) Table 5- 1 contd. - - Geographic name H.A. Nunavut NWT Nunavut NWT Nunavut NWT km2 km2 quota quota estimate estimate Date South Paulatuk West Kugluktuk North Great Bear Kent Peninsula Adelaide Peninsula Bathurst Inlet Queen Moud Gulf North Contwoyto McAlpine Lake Garry Lukes Central Kivalliq Alymer Loke Artillery Loke Boothia Peninsula King Williüm Island Beaverhill Lake Thelon Sunctuciry The di ffemt levels of microsatellite variation across 14 variable dinucleot ide microsatellite loci in Arctic Island (including Greenlünd) O. m. wardi and Mainland O. m. moschatus from n survey of 172 muskoxen (Chapter 3). There is evidence for subdivision of the Arctic Island 0.m. wardi into two lineages, the Southern Arctic Island lineage (SAI) and the Northern Arctic Island lineûge (NAI) (Chapter 3). Genetic polymorphism estimates are also shown for these two lineages. Unbiased estimates of expected heterozygosity (Nei and Roychoudhury 1974) and their standard errors are shown. Pio is the probability of identity as defined in (Paetkau et al. 1998). Also shown are the current census size esiimates for each lineage (data inferred from (Fournier and Gunn 1998) and John Nagy pers. comm. 1999). See Figure 5-3 for the distribution of lineages. -- - Lineng Sample Ex pectcd Pio # of Census Size Size Heterozygos i t y Alleles 'SE Arctic Island Muskoxen 111 0.42310.002 2.19E-05 47 1 l9ûûû Southern Arctic Island Muskoxen 75 0.247IQ.028 6.2OE-04 35 100000 (SAU Northern Arctic Island Muskoxen 36 0.294st0.049 3.89E-05 40 15000 (NAI) Table 5-2b. Variability at 14 microsatellite loci in 158 muskoxen from 1 1 sample locations across their range. Locations are arranged from approximately North to South, with abbreviations in brackets. The unbiased estimate of expecied heterozygosity (Nei und Roychoudhury 1974) is shown f standard error (SE). The table includes the probability of any two muskoxen from a given location being genetically identical - Probability of Identity (PID). The Pio formula used is given in Paetkau et al. (1998). Most entries are the snme as those in Table 3- 1. However for the cnlculotions in this table only those samples with specific location data were included resulting in decreiised sample sizes for Kuglukuk (KU, Baker Lake (BL) and Bathurst Island (BI) samples. In ihe case of Grise Fiord an additional sample was included. Locations are shown in Figure 5-3. Location Northern Sample Heterozygosity P. of identity Latitude Size f SE (PID) Northern Ellesmere (NE) Grise Fiord (GF) Bathurst Island (BI) Greenland (GD) Sachs Harbour (SW) Kidjuut Lake (KL) Wellington Bay (WB) Kugluktuk (KL) Gjor Haven (GH) Baker Lake (BL) - Lutsel Ke (LK) 63.O0 10 0.478f+ 0.05 2SOE-O8 Table 5-3a. The contribution of each sample of muskoxen to the allelic nchness in their respective lineages for 14 microsatellite loci (Petit et al. 1998). Cr(k,= total contribution to allelic richness of the sample (k), contribution of sample due to allelic diversity and Cmk) = contribution of a sample due to differentiation from al1 other samples of the same lineage. Sample abbreviations and lineages are defined in the text and dl calculation performed with CONTRIB (Petit 1999). NAi Table 5-3b. Contribution analysis showing the high relative contribution of bone samples from the Thelon Garne Sanctuary (TH) to allelic richness of the MAINLAND lineage (Petit et al. 1998). This analysis was only conducted for 4 of the 14 loci used in the majonty of the study. Title abbreviations, and sample abbreviations and lineages defined in the text and al1 calculation performed with CONTRIB (Petit 1999). Lineage SampIe Cnt, CSW Cm, Table 5-4, Results of spatial autocorrelation analysis for each lineage of muskoxen across 100 and 200 km scnles. Area of positive nutocorrelation and for the first distance class for each lineage are shown. The distance values where r'h)does not differ from O were taken from the Figures 5-5 and 5-8. The area of positive autocorrelation is this distance value squared. Also shown are the estimaies when a sample of 13 bones from the Thelon Game Sanctuary was analysed with 4 loci. All correlograms except NA1 at 100 km were globally significani (see text for detoils). MAINLAND NA1 SA1 r"" ut first th'is no Area of a fir/"' is no Area of th)at first Jh' is no Arcu of distance different positive distance di fferent positive distance different from O positive clnss from O in autocorrelation class frorn O in üutocorrelotion closs in km' autocorrelütio km in km2 km" in km2 n in km2 lncluding Thelon Bones '= These values are estimated from Figures 5-5 and 5-7.' = NA1 muskoxen contüin few samples and ai 100 km the correlogram is not 2 globnlly significant. Evaluution of the current conservation of endemic muskoxen with respect to major subdivisions and estimüted areus of positive autocorrelotion in three different lineages (MAINLAND, Southern Arctic Island (SAI) and Northern Arctic Island (NAI)). In al1 colculations except the Highest Allelic Richness values of MAINLAND muskoxen 14. loci were used. For this calculation 4 loci were used. The three lineages have been identified previously (Chapter 3). Those samples with the highest allelic richness in each study were identified in this study using CONTRIB (Petit 1999). The Scale of dispersal refers to the area of positive autocorrelation we identified in this study using spatial autocorrelation of inter-individual genetic distances and geographic distances. For these analyses we used GENAIEX P (Peakall and Smouse 1998). The protected arens are shown in Figure 5-2 and the distribution of lineages in Figure 5-3 (see text for further details). - Lineage Highest Allelic Richness Protected Areas Size of protected areas in km2 Scale of dispersal in km2 Thelon G. S. 38 400 MAINLAND Thelon G.s.~ Tuktut Nogait N.P. 16 974 N. P. of North and 200 0ood East Greenland NA1 Grise Fiord (GF) Quittinirpanq N.P. 37 775 Aulwik NP 12 000 102400 SA1 Bathurst Island (BI) - Tuktusiuqvialik NP. Tuktusiuqvialik N.P." 8 442 1 024ûû = These data from Table 5-4. = Based on 4 variable loci. The next highest regions are KU and BL. KU sampling is very close to the Tuktut Nogait N.P. ' = The most diverse sampling are in this lineage (GF) is not protected. = The actual park size is 972 000 km2 - but only 200 000 km2 is ice-free. = This park is proposed - negotiations with Inuit and other stakeholders are ongoing. Chapter 6 GENEML DISCUSSION AND SUMMARY The implications of the major findings of my thesis are discussed in each chapter. To improve on this study there is an obvious need for pater sample coverage. That having ken said, in this final chapter, 1discuss four questions raised as a result of my study and suggest ways to address them. Specifically: 1) did the Banks Island Refuge structure genetic variation in muskoxen; 2) what are the effects of specific Ocean watergaps on muskox movement; 3) does each sex contribute equally to area of positive autocomlation and 4) what are the looming environmental threats which could affect management plans for muskoxen. A Test of the Banks Island Refuge The surprise of this snidy was the very different levels of microsatellite variability in mainland venus Arctic Island muskoxen. When coupled with hierarchical analyses, these data suggest that the anceston to Arctic Island muskoxen were isolated in an ice- free refuge on Banks Island at Last Glacial Maximum as proposed by Macpherson (1965). At first glance this hypothesis cm be tested using the Wested - Clade" approach of Templeton and CO-workers(Templeton and Georgiadis 1995; Templeton 1998; Cruzan and Templeton 2000). This cladistic approach to the analysis of organelle DNA with low sequence variation predicts that refuges wili be implicated if a) there are clusters of closely related mtDNA haplotypes one or a few of which are distributed across the entire range of the species and b) nested clade analysis reveals a set of haplotypes with restricted but overlapping distributions that are displaced a large distance from the clade center (Cmzan and Templeton 2000). Although promising, this anaiysis could be compromised if the recent reduction in population size of Banks Island muskoxen is in fact a recurrent feature of muskoxen post-glacial history. It was this concem - and the high probability that 1 would be unable to detect an Arctic Ocean effect with rntDNA polyrnorphism - that inhibited me from applying this method. However, if the sole objective is to test the importance of a Banks Island refuge theory, application of the nested clade approach with a large mtDNA survey might be fruitful. Two important results would flow from such an analysis. First, the importance of population fluctuations such as those recorded in the last 150 years for post-glacial muskox evolution on the Arctic islands could be evaluated. Second, such data could mess the likelihood of multiple refugial origins of Arctic Island muskoxen as hypothesized in Chapter 3 (Cnizan and Templeton 2000). The main stumbling block to such an analysis would be the exceptionally low level of variation found in even the hypewariable control region area of muskox mtDNA (Groves 1997) A Better Testfor Arctic Ocean Watergaps In my analysis of major genetic muskox lineages, I found that at least one watergap, that between the Mainland and Banks and Victoria Islands, is a substantial barrier to muskox gene flow (Chapter 3). Although the overall results would suggest that no other Arctic water gap is Wrely to be equal to this as a barrier to muskoxen, some other gaps may be important for muskox genetic stmcturing. Of particular interest is the Parry Channel, which lies between several Southern Arctic Islands (e.g. Victoria, Banks, Prince of Wdes) and Northem Arctic Islands such as Devon, Bathurst and Melville. Roed et al. (1986) found discontinuities in the allozyrne locus transfemn variation which suggested that this same watergap appears to impede the movement of Peari Caribou Rangifer tarandus pearyi (Roed 1986). The importance of this banier to muskox movement should be assessed, To more accurately estimate the effect of specific Arctic Ocean watergaps, two analyses might be useful, both of which are predicated on more extensive sampling of dl the remaining islands that harbour muskoxen. The fiat anaiysis would be similar to the regression analyses presented in Chapter 4 but would use a multiple regression including additional gap descnpton such as the length of each water gap, the length of tirne a gap is ice-f~ein the summer and the nature of the ice surface in the winter. This would help dari@ the important attributes of waterways that could either facilitate or impede muskox movement at different times of the year or in different yean depending on ice conditions. With the increase in number of variables it is important that potential multi-colinearity among predictors be examined. This cm be evaiuated by checking for strong correlations among predicton, and by obse~ngthe value of partial regression coefficients when the input order of the variables in the regression is changed. The value of the partiai regression coefficient for relatively orthogonal variables should not change with input order or with the inclusionfexcIusion of other variables. A second potentially useful analysis would be to calculate the "assignment matrix" for al1 Arctic Island muskox based on multilocus microsatellite genotypes (Paetkau et al. 1995). An investigation of the patterns in such a matrix should reveal which watergaps muskox cross more frequently and then direction of movements. The Relative Contribution of Males and Females to Dispersal Estimates Departures from quasi-stationarity in both the MAINLAND and NA1 muskoxen suggests I cannot estimate dispersal per se even with more data in the spatial autocorrelation analysis. However, with additionai data we could investigate the contribution of each sex to the area of positive autocorrelation and hence estimate relative dispersal of males and females. The correlograms of males and females are expected to differ given Our knowledge of muskox behaviour. Since the dominant bulls that do most of the mating with reproductively mature females in a harem are likely to be unrelated to the females, whereas harem females are probably more closely related, males must on average disperse further to locate a herd (Gray 1990). Also the frequent observation that when colonizing new areas it is muskox males that venture far beyond the core group to explore new habitats implies that males are likely to have larger areas of positive autocorrelation than femaies (Le Henaff and Crete 1989; Smith 1989). This in tum suggests the majority of gene flow between island populations may well occur via the males. Greutest Perceived Threuts to Murkoxen Populations My genetic evaluation of current conservation practices for muskoxen dong with the suggestions made above are based on the distribution of genetic variation in the species and are made under the assumption that Arctic environments have not changed significantly since the 1st glaciation. However, it is likely that the climatic conditions in the western Arctic are in the process of changing substantially (Maxwell 1997; Tynan and Demaster 1997). The immediate predicted impacts of increased Arctic temperature resulting from global warming are: 1) exposure of muskoxen to elevated pathogen loads as more temperate mammal species move north; and 2) that the water gaps between Arctic Islands will remain ice-free for longer periods of time and possibly al1 year, leading to reduced genetic exchange arnong muskox populations . With respect to the first threat, one set of genetic loci that could play a large role in determining the wlnerability of muskoxen to increased pathogen exposure are those in the Major Histocompatibility Complex (MHC) (Apinius et al. 1997). Mikko et al. (1999) showed that a 230 bp segment of the cade DRB3 MHC locus was invariant in SA1 muskoxen, suggesting that these muskoxen might be poorly positioned to resist infectious diseases. This conclusion, may be premature, insofar as: 1) the survey did not include animals from MAINLAND muskox populations; 2) only a small sequence of single MHC Class I[ locus was anaiysed; and 3) MHC loci are likely subject to balancing selection resulting in increased polymorphisrn relative to other DNA sequences (Hughes and Yeager 1998; Hednck 1999a). This would mean that high levels of polymorphism might develop quickly despite ment bonlenecks despite ment bottlenecks as was found in the MHC DRB3 locus for the African Buffalo (Syncencs caffer) (Wenink et al. 1998). Finally, the relationship between increased disease susceptibility and decreased MHC polymorphism remains unclear for wild ruminants (Mikko et al. 1999). As a first step to assessing this nsk, one should examine MHC polymorphism in al1 three muskoxen lineages. If the distribution of MHC variability does not match my microsatellite contribution analysis, the relative importance of these kinds of genetic polymorphism need to be evaluated before suggestions are made to change current conservation and management plans. With global waming one can anticipate that waterways will remain ice-free for longer in the sumrner. This might isolate islands which are currently connected by crossable ice for most of the year, resulting in reduced genetic exchange among Arctic Island muskox populations. This effect might be particularly important in NAI muskoxen where ice seems to expedite muskox movement now (Chapter 4). The evolutionary consequences of reduced genetic exchange would include increased breeding among relatives and increased genetic dnft in the isoiated populations prone to periods of reduced size (Templeton 1990). The net effect would be an incieased rate of loss of genetic diversity in an already genetically depauperate species. This impact is probably less of a concern to long term Ovibos survival than is the nsk of increased pathogen exposure as other mammals migrate further north with new diseases and disease vectors. The main findings of this thesis are: Muskoxen peflect di-nucleotide microsatellite loci are significantly more variable than imperfect loci. Heterozygosity at 30 microsatellite loci including perfect and ndmpe rfect loci from muskoxen and other ungulate taxa is H, = 0.29M.009 which is substantially higher than earlier estimates for Ovibos. Microsatellite polymorphism varies substantially in muskoxen, with Arctic Island animals being far less variable than mainland animais. Stability analysis of the Iikelihood distance indicates 3 lineages: MAINLAND, Southem Arctic Island (SAI) and Northern Arctic Island (NAI). These data suggest isolation in an ice-free refuge duhgthe Last Glacial Maximum of the Wisconsin. The MANLAND lineage has almost double the heterozygosity of the two Arctic Island lineages (H,= 0.535, SM.068 venus H, = 0.247, SM.028 in the SA1 lineage, H, =0.294, SE= 0.049 in the NA1 lineage). Multiple regression analyss of the Shared Allele distance DsAand geographic distance indicates that Arctic Ocean water gaps expedite dispersal in NA1muskoxen Generalized Mante1 Analysis (GMA)of the Shared Allele distance DsA and geographic distance indicates that Arctic Ocean water gaps can either expedite or retard dispersa1 in SA1 muskoxen. Muskoxen From the Thelon Garne Sanctuary are the most diverse of ali muskoxen, with rnuskoxen from Bathurst Island being the most diverse Arctic Island muskoxen. 9. Spatial autocorrelation analyses of interindividual distances suggest dispersal distances in MAINLAND muskoxen are significantly less than those of SA1 muskoxen at 195 km and 320 respectively. 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Original = the original geographic CO- ordinate - In some cases samples provided by certain Hunter and Trapper Councils have the sarne location data, Unique = unique CO- ordinates assigned the samples (see chapter 4 for details). Only those samples wiih unique geographic coordinates were used in the regression analyses of Chapter 4. Sample Assign MX-1 MAlN 122 122 MAlN 122 148 MAlN 122 122 MAlN 122 140 MAlN 122 140 MAlN 122 148 MAlN 122 148 MAlN 148 148 MAlN 122 122 MAlN 122 122 MAlN 122 122 MAlN 148 148 MAlN 122 122 MAlN 122 148 MAlN 122 148 MAlN 122 148 NAIN 122 122 MAIN 122 148 MAlN 122 148 MAIN 122 148 MAlN 122 148 MAlN 122 148 Appendix 1 Contd. Sample Assign Pop Original Unique Lat. Long Lat. Long BL-02 MAlN BL 84.40 07.93 64.40 07,93 BL-03 MAlN BL 64.10 07.07 64.10 97.07 BL-04 MAlN BL BL-OS MAlN BL BL46 MAlN BL BL-07 MAlN BL BL-09 MAlN BL BL-1O MAlN DL BL-11 MAIN BL BL-12 MAlN 8C BL-13 MAlN Bi. BL-15 MAIN BI. EL-16 MAlN BL BL-17 MAIN BL Bbl8 MAlN BL BL-20 MAlN BL BL-2 1 MAlN BL DL-22 MAIN BL CH-O1 MAlN Bi. CH45 MAlN BL CH46 MAlN BL CH-O7 MAIN BL Appendix 1 Contd. Smple Assigned Pop OM50-O8 OMS 1- 16 OMS 1- 19 MX-1 MAlN BL 148 148 MAlN GH 122 148 MAlN ÛH 122 122 MAIN GH 148 148 MAlN ÛH 122 148 MAlN GH 122 148 MAlN GIH 122 148 MAlN OH 122 148 MAIN Wl 122 148 MAlN GH 122 122 MAlN GH 122 122 MAlN KU 134 134 MAlN KU 122 134 MAlN KU 122 134 MAlN KU 122 122 MAlN KU 122 134 MAlN KU 134 134 MAlN KU 122 136 MAlN KU 122 134 MAlN KU 122 134 MAlN KU 134 134 MAlN KU 122 134 MAIN KU 122 134 MAlN KU 134 134 MAlN KU 122 122 MAlN KU 134 136 MAlN KU 134 136 MAlN KU 134 134 MAlN LK 122 136 MAlN LK 122 134 Appendix 1 Contd. Sarnple Assigned Pop MAlN MAlN MAlN MAlN MAlN MAlN MAlN MAIN MAlN NAI NA1 NAI NAI NA1 NA1 NA1 NA1 NA1 NA1 NA1 NA1 NA1 NA! NAI NA1 NA1 NA1 N AI NA1 NA! Appendix I Contd. Sarnple Assign Pop Original Unique Lat. Long Lat. Long MAlN LK 63.00 107.50 62.96 107.54 MAlN LK û3.00 107,50 62.98 107.66 MAlN LK 63.00 107.60 63.00 107.50 MAlN LK 63.00 107.60 63.02 107.62 MAN LK 63.00 107.60 63.04 107.54 MAlN 63.00 107.50 63.06 107.56 MAIN 63.00 107.50 63.08 107.58 MAlN 63.00 107.50 63.10 107.60 MAIN 64.20 102.50 64,20 102.50 NA1 NA1 NA1 NAI NA1 NA) NA1 NA1 NAI NAI NA1 NA1 NA1 NA1 NA1 NA1 NA1 NA1 NAI NAI NAI Appendix 1 Contd. Sample Assignecl Pop OM50-08 MX-I NA1 122 122 NA1 122 122 NA1 122 122 NA1 122 122 NA1 122 122 NA1 122 122 NA! 122 122 NA! 122 122 NAI 122 122 NA1 122 122 NA1 122 122 NAI 122 122 NAI 122 122 NAI 122 122 NA1 122 122 SA1 122 122 SA1 122 122 SA1 122 122 SA1 122 122 SAI 122 122 SA1 122 122 SA1 122 122 SA1 122 122 SA1 122 122 SA1 122 122 SA1 122 122 SA1 122 122 SAI 122 122 SA1 122 122 122 122 Appendix 1 Contd. Sample Assign Pop Original Unique Lat, Long Lat. Long NA1 77.20 84.60 77.20 84.50 NA1 77.10 84.50 7.10 84.51 NAI 7?.20 84B3 77.20 84.83 NA1 77-00 84.02 T7.00 84.92 NAt 77.10 84.50 n.io w.so NAI 79.00 88.13 79.90 88.13 NA1 70.90 88.60 79.00 88.60 NA1 81.80 72.62 8180 72.62 NA1 81.60 74.65 81.50 74.65 NA1 81.60 74.63 81.50 74.63 NA1 80.10 05.69 80.10 85.69 NA1 80.00 85.70 80.00 85.70 NA1 78.40 85.83 78.40 85.83 NA1 78.80 82.67 78.80 82.67 NA1 72.00 04.31 72.00 94.31 SA1 74.80 106.30 74.80 106,30 SAI 76.00 07.67 76,Ol 07.67 SA1 76.00 97.67 76.00 97.68 SA1 76.80 97.65 75.9t 97.65 SA1 75.90 97.65 75.90 07.66 SA1 75.80 97.86 75.80 97.96 SA1 78.00 100.20 76.00 100.20 SA1 SA1 SA! SA1 SA1 SAI SAI SAl Appendix 1 Contd. Sample Assigned Pop OM50-08 OMS 1- 16 OMS 1- 19 MX-1 KC-02 122 122 KL-O3 122 122 KL-04 122 122 KL-O5 122 122 KC-07 122 122 KL-10 122 122 KL-11 122 122 KL-12 122 122 KL-14 122 122 KL* 1fi 122 122 KL-16 122 122 KI.-17 122 122 tu-19 122 922 KL-21 122 122 KL-22 122 122 KL-24 122 122 KL-26 122 122 KL-27 122 122 KL28 122 122 Ki-30 122 122 SH-Ol 122 122 SH-02 122 122 SH-03 122 122 SH-O4 122 122 SH-05 122 122 SH-06 122 122 SH-07 122 122 SH-08 122 122 SH60 122 122 - SH-10 122 122 00 Appendix 1 Contd. Sample Assign Pop Original Unique Lat. Long Lat: Long KL-O2 71.30 117.40 71.21 117.31 KL-O3 77.30 117.40 71.22 117.32 KL-04 71.30 117.40 71.23 1 l7.W KL-O5 71.30 117.40 71.24 117.34 KL-07 71,30 117.40 71.25 11735 KL-1O 71.30 117.40 71-26 117.36 KL-$1 71.30 117.40 71.27 117.37 KL-12 71.30 il7.40 71.28 117.30 Kt- 14 71.30 117.40 71.29 117.39 Kb15 71.30 117.40 71.30 117.40 KL-16 71.30 117.40 71.31 117.41 KL-17 71.30 117.40 71.32 117.42 KL-19 71.30 117.40 71.33 117.43 Kt021 71.30 117.40 71.34 117.44 Kt42 71.30 117.40 71.35 117.45 KL-24 71.30 117.40 71.36 117.46 KL-26 71.30 117.40 71.37 117.47 KLc27 71.30 117.40 71.38 117.48 KL-29 71.30 1V.40 71.30 117.49 KL-30 71.30 117.40 71.40 117.50 SH61 72.00 125.20 71.91 125.11 SH42 72.00 125.20 71.02 125.12 SH-03 72.00 125.20 71.93 125.13 SH-04 72.00 125.20 71.94 125.14 SH-O5 72.00 125.20 71.95 125.15 SH-06 72.00 125.20 71.96 125.16 SH-07 72.00 125.20 71.07 125.17 SH68 72.00 125.20 71.98 125.18 SH6Q 72.00 125-20 71.09 125.19 S SH-10 72.00 125.20 72.00 125.20 00 Appendix 1 Contd. Sample Assigned Pop OM5O-08 OMS 1 - 16 MX-1 SH-11 122 122 SH- 12 122 122 SH-13 122 122 SH*S4 122 122 SH-15 122 122 SH-16 122 122 SH-17 122 122 SH-18 122 122 SH-10 122 122 w.04 122 122 W8-01 122 122 WB02 122 122 WB03 122 t22 WB44 122 122 WB-05 122 122 WB06 122 122 WB47 122 122 WB08 122 122 WB49 122 122 WB10 122 122 WB11 122 122 Wb12 122 122 WB13 122 122 WB44 122 122 WB-15 122 122 WB-1 6 122 122 WB17 122 122 WB4 8 122 122 WB49 122 122 WB020 122 122 IO Appendix 1 Contd. Sample Assign Pop Original Unique Lat. Long Lat. Long SA1 72.00 125.20 72.01 125.21 SA1 72.00 125.20 72.02 125.22 SA1 72,OO 125.20 72,03 125.23 SA1 72.00 125.20 72.04 125.24 SA1 72.00 125.20 72,05 125.26 SA1 72,OO 125.20 72.06 125.26 SA1 72.00 125.20 72.07 125.27 SAI 72.00 125.20 72.08 125.28 SAI 72.00 125.20 72.09 125.29 SA! 73.50 99.87 73.50 90.87 SA! 69.20 106.20 69.12 106.11 SA1 69.20 106,20 69.13 106.12 SA1 60.20 106.20 69.14 106.13 SA1 69.20 106.20 69.15 106.14 SA1 69.20 106,20 69.16 106.15 SA1 69,20 106.20 69.17 106.16 SA1 69.20 106.20 69.18 106.17 SA1 69.20 106.20 69.19 106.18 SA1 69.20 106.20 69.20 106.19 SA1 69.20 106.20 69.21 106.20 SA1 69.20 tO6.20 69.22 106.21 SA1 60.20 106.20 69,23 106.22 SA1 69.20 106.20 69.24 106.23 SA1 60.20 106.20 69.25 106.24 SA1 69.20 106.20 69,26 106.25 SA1 69.20 106.20 69,27 106.26 SA1 69.20 106.20 69.28 106.27 SA1 69.20 106.20 69.29 106.28 SAI 69.20 $06.20 69.30 106.29 SA1 69.20 106.20 69.31 106.30 APPENDIX 2 Two pairwise distance motrices - DLR(Paetkau et al. 1997) and Ds(Nei 1972) - for the eleven sample locations used in this study. The letter codes refer to sample locations detailed in Figure 3- 1. Sarnples FR-2 . PW-4and TH-27where not included. They were each relatively distant from the closest sample location and were thus not assigned to locations. They were nssigned to one to the three muskox lineages. DLRis the bottom half matrix and Ds is the top half matrix. Individual Assigament probabilities for each of the 172 muskox used in this study. Original = the lineage of origin based on sampling location; Assigned = the most probable assigned lineage; Prob = the assignment probability of the most probable assigned lineage based on the 14 locus genotype; Main = the probability of the individual king assigned to the MAINLAND lineage; NA1 = the probability of the individual king assigned to the Northern Arctic Island WAI) heage; SA1 = the probability of the individual king assigned to the Southem Arctic Island lineage. The fust two letters in an individual's name correspond to locations found in Figure 3-1 and Table 3-1. Individual Original Assigned Prb SA1 Main NA1 BL-02 Main Main BL-03 Main Main BL-04 Main Main BL-05 Main Main BL-06 Main Main BL-07 Main Main BL-09 Main Main BL-IO Main Main BL-11 Main Main BL-12 Main Main BL-13 Main Main BL-15 Main Main BL-16 Main Main BL-17 Main Main BL-18 Main Main BL-20 Main Main BL-2 1 Main Main BL-22 Main Main CH41 Main Main CH-OS Main Main Cfi-O6 Main Main CH47 Main Main CH-08 Main Main GH-01 Main Main GH-02 Main Main GH-03 Main Main GH-04 Main Main GH-OS Main Main Appendix 3 contd. GH-û6 Main Main GH-07 Main Main GH-08 Main Main GH-09 Main Main GH-IO Main Main KU42 Main Main KU44 Main Main KU46 Main Main KU49 Main Main KU-1 1 Main Main Ku-12 Main Main KU-13 Main Main KU- 14 Main Main KU-16 Main Main KU-1 8 Main Main KU-19 Main Main KU-20 Main Main KU-3 1 Main Main KU-32 Main Main KU-33 Main Main KU-34 Main Main KU-35 Main Main LIS-O 1 Main Main LIS-02 Main Main LK-03 Main Main LK-04 Main Main LK-05 Main Main LK-06 Main Main LK-07 Main Main LK-08 Main Main LK-09 Main Main LK-1 O Main Main TH-27 Main Main AM1 NA1 NAI AH-04 NAI NA1 DI43 NA1 NAI 0164 NA1 NAI DE05 NAI NA1 DL07 NAI NAI DI- 16 NA1 NAI EL1 3 NAI NAI EI-27 NAI NAI EI-28 NAI NA1 Appendix 3 contd. EU47 NAI NA1 EU- 1 5 NA1 NAl EU-19 NAI NA1 GF-01 NM NAI GF-02 NA1 NAI GF-04 NAI NAI GF-O5 NAI NA1 GF-O6 NA1 NAl GF-O7 NAI NAI GF-09 NA1 NAI GF-14 NAI NAI GF-19 NA1 NA1 GF-21 NA1 NAI JA-01 NAI NAI JA-02 NAI NAI JA-04 NAI NAI SF-O3 NAI NAI ZA-07 NAI NAI 24-08 NAI NAI ZA-12 NAI NAI ZA- 16 NAI NAI ZA-2 1 NAI NA1 ZA-26 NA1 NA1 AI-O 1 SAI SN BI-O 1 SM SA1 BI-26 SAI SA1 BI-30 SM SA1 B 1-3 1 SA1 SAI BI-3 2 SAI SA1 BI-33 SA1 SA1 BI-36 SA1 SA1 BI-38 SA1 SA1 CI-O 1 SA1 NA1 CI-04 SAI SAI CI-05 SAI SM CI47 SAI SA1 CI48 SAI NAI CM41 SA1 SN CM42 SA1 SA1 FR-02 SA1 NAI KIAI SM SA1 Kt-02 SAI SA1 KL-03 SAI SA1 Appendix 3 contd. KL-04 SAI SAI KM5 SM SAI KL-07 SM SA1 KL-10 SAI SM KL-Il SAI SA1 KL-12 SAI SAI KL- 14 SAI SA1 KL-15 SM SM KL-16 SAI SM KL-17 SAI SAI KL-19 SAI SM KL-21 SAI SN KL-22 SAI SA1 KL-24 SM SA1 KL-26 SM SA1 KL-27 SM SAI KL-29 SAI SAI KL-30 SA1 SAI PW-04 SAI SA1 SH-OI SM SAI SH-02 SAI SN SH-03 SA1 SA1 SH-04 SAI SA1 SH-05 SAI SA1 SN46 SA1 SA1 SH-07 SA1 SA1 SH-08 SA1 SN SH-09 SAI SA1 SH-IO SM SAI SH-11 SAI SM SH-12 SAI SAI SH-13 SAI SAI SH-14 SAI SAI SH-15 SAI SM SH-16 SM SA1 SH- 17 SN SA1 SH-18 SAI SA1 SH-19 SM SA1 WB41 SA1 SA1 m-02 SA1 SA1 m-03 SA1 SA1 wB-04 SN SN WB45 SM SN Appendix 3 contd. - --- WB-06 SAI SA1 2.60E-05 WB47 SA1 SA1 6.23E-05 WB-08 SAI SM 4.9 1E-06 wB-09 SN SA1 1.26E-04 WB40 SA1 SA1 8.75E-04 WB-1 1 SAI SAI 7.29E-05 WB-12 SAI SAI 6.42E-04 WB- 13 SN SA1 1.26E-04 WB-14 SAI SAI 3.5 1 E-OS WB-15 SAI SM 2.WE-04 WB-16 SAI SA1 1.12E-05 WB-17 SAI SAI 3.75E-04 WB-18 SAI SA1 0.002094 WB-19 SN SAI 3.97E-06 WB-20 SA1 SA1 3.44E-07 APPENDIX 4 The Assignment Matrix of 172 Muskox to the three major muskox lineages identified in this study based on the likliehoods of a 14 locus genotype. Main = MAINLAND lineage. NA1 = The northem Arctic Island lineage and SM = the Southern Arctic Island lineage. Original Assigned Lineage Lineage SM Main NA1 SAI 75 O 3 Main O 61 O NAI O O 33 APPENDIX 5 Pairwise Iikelihood distance Dm estimates between three muskox lineages in this study SA1 0.0 Main 21.132 0.0 NA1 8.676 23.780 0.0