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Using genetic data to characterize dispersal, relatedness and parentage in the collared peccary (Pecari tajacu)

ProQuest Dissertations and Theses, 2009
Dissertation
Author: Jennifer Diane Cooper
Abstract:
Heretofore, little was known of the population genetic structure, dispersal, genetic mating system or relationships of the collared peccary (Pecari tajacu ). I sampled 268 individuals from 31 herds in 3 Texas populations. I haplotyped peccaries at a 449bp control region locus within the mitochondrial genome. Analysis of mtDNA haplotype distribution patterns across Texas indicates that P. tajacu has recently expanded its range, a result congruent with historical accounts of the recent colonization by collared peccaries of the American southwest. I utilized mtDNA haploype data to estimate sex-specific natal dispersal rates through sex-specific comparisons of genetic variation among social groups. AMOVA analyses yielded fixation index values for females which were significantly larger than values for males. I also calculated a rate of male dispersal among social groups of 0.37. These results indicate that mtDNA can be used to infer instantaneous dispersal behavior for both sexes, despite a pattern of matrilineal inheritance. Collared peccaries exhibit several traits that differentiate them from suids, including a mixed-sex grouping pattern and sexual monomorphism. There has been debate concerning the importance of social dominance in maximizing male reproductive success. I used 11 polymorphic microsatellites (6 of which I developed for P. tajacu via cloning) to produce a multi-locus genotype for all individuals. I tested genetic relationships among adults and assigned parents to 75 offspring. My results indicate that herds comprised a mixture of relatives and non-relatives of both sexes. I used pairwise relatedness ( r ) estimates between adult males and adult females within herds to classify 38% of males as dispersers, a rate comparable to that inferred from the mtDNA analysis. Relationship analyses also revealed a low degree of female dispersal, a result that clarifies the source of the modest degree of female mtDNA haplotype admixture females within herds. Parentage data suggest that males either disperse multiply or successfully father offspring in neighboring herds. Multiple males sire offspring within a herd, and there was no evidence for reproductive skew in either sex. Clearly, neither males nor females monopolize reproductive success, thus competition may play a smaller role mating system than was previously suggested.

TABLE OF CONTENTS Page LIST OF TABLES ................................................................................................. vi LIST OF FIGURES .............................................................................................. vii

ABSTRACT ........................................................................................................ viii

CHAPTER 1. QUANTIFYING MALE-BIASED DISPERSAL AMONG SOCIAL GROUPS IN THE COLLARED PECCARY (PECARI TAJACU) USING ANALYSES BASED ON MTDNA VARIATION ..................................................... 1

1.1. Introduction ................................................................................................. 1

1.1.1. Measuring dispersal ............................................................................. 1

1.1.2. Using sex-specific fixation indices to estimate instantaneous dispersal rates…………………...…………………………………………………….2

1.2. Materials and Methods ............................................................................... 3

1.2.1. Study species ....................................................................................... 3

1.2.2. Sampling ............................................................................................... 4

1.2.3. Genetic analysis ................................................................................... 5

1.2.4. Statistical analyses ............................................................................... 7

1.3. Results ..................................................................................................... 10

1.3.1. mtDNA haplotype distribution patterns ............................................... 10

1.3.2. Patterns of genetic variation revealed by F-statistics as functions of identity probabilities .......................................................................... 13

1.3.3. Dispersal rate estimates ..................................................................... 17

1.4. Discussion ................................................................................................ 17

1.4.1. Dispersal in P. tajacu .......................................................................... 17

1.4.2. Measuring dispersal biases ................................................................ 18

1.4.3. Measuring sex-biased dispersal with uni-parentally inherited markers ............................................................................................. 19

CHAPTER 2. MEASURING DISPERSAL SEX BIAS IN SOCIAL MAMMALS: ANALYTICAL COMPARISONS OF MICROSATELLITE AND SEQUENCE DATA .................................................................................................................. 21

2.1. Introduction ............................................................................................... 21

2.1.1. Variation among populations .............................................................. 21

2.1.2. Variation within populations ................................................................ 22

v

Page

2.2. Materials and Methods ............................................................................. 26

2.2.1. Sampling ............................................................................................. 26

2.2.2. DNA isolation and amplification .......................................................... 27

2.2.3. Statistical analysis .............................................................................. 29

2.3. Results ..................................................................................................... 32

2.3.1. Genetic variation among populations ................................................. 32

2.3.2. Genetic variation within populations: analysis of molecular variance . 35

2.3.3. Isolation by distance ........................................................................... 37

2.4. Discussion ................................................................................................ 42

2.4.1. Biogeographic patterns of colonization ............................................... 42

2.4.2. Population patterns of dispersal ......................................................... 42

CHAPTER 3. GENETIC ESTIMATES OF NATAL DISPERSAL, KIN STRUCTURE AND PARENTAGE IN COLLARED PECCARY (PECARI TAJACU) ............................................................................................. 46

3.1. Introduction ............................................................................................... 46

3.2. Materials and Methods ............................................................................. 48

3.2.1. Sampling ............................................................................................. 48

3.2.2. Genetic analysis ................................................................................. 51

3.2.3. Genetic relatedness, family relationships and dispersal ..................... 52

3.2.4. Parentage ........................................................................................... 53

3.3. Results ..................................................................................................... 55

3.3.1. Genetic relatedness, family relationships and dispersal ..................... 56

3.3.2. Parentage ........................................................................................... 60

3.4. Discussion ................................................................................................ 67

3.4.1. Genetic relatedness, family relationships and dispersal ..................... 67

3.4.2. Parentage and mating system ............................................................ 68

3.4.3. Evolutionary implications .................................................................... 70

LIST OF REFERENCES .................................................................................... 73

APPENDIX ......................................................................................................... 82

VITA ................................................................................................................... 87

vi

LIST OF TABLES Table Page Table 1.1 Distribution of mtDNA haplotypes in three wild populations of P. tajacu in Texas, across sex and age classes………………………………12 Table 1.2 Pairwise genetic differentiation among three P. tajacu populations, based on mtDNA haplotype frequencies ...................................................... 12 Table 1.3 Intra-class correlations for pairs of genes among social groups within replicate populations estimated by means of identity probabilities. .............. 14 Table 2.1 Autosomal microsatellites amplified in collared peccaries………….....28 Table 2.2 Microsatellite allele frequencies in 3 Texas populations of collared peccaries………………………………………………………………………..…34 Table 2.3 Distribution of mtDNA haplotypes in 4 Texas populations of P. tajacu, across sex and age classes.………………………………….………………….35 Table 2.4 Mismatch distribution for spatial and demographic expansions in 3 Texas populations of Pecari tajacu …………………………………….………36 Table 2.5 Estimates of average among-herd relatedness, F ST , F IS mean and variance of the Assignment Index (mAIc and vAIc) in 2 Texas populations of collared peccaries (P. tajacu).…………………………….……36 , and the Table 2.6 Covariance estimates generated from analysis of molecular variance (AMOVA) of mtDNA haplotype and microsatellite genotype frequency data in 3 Texas populations of collared peccaries ………………………………….40 Table 3.1 Genetic diversity across microsatellite loci and frequency of inferred parentage assignments in three Texas populations of collared peccary (Pecari tajacu)………..…………………………………………………………...58 Table 3.2 Genetic relatedness and most likely family relationships among adults within herds in two populations of P. tajacu in Texas, inferred from multi- locus microsatellite genotype data.…………………………………………......58 Table 3.3 No evidence for reproductive skew in female or male P. tajacu in Big Bend Ranch State Park, Texas……………………………………….…….…..65

vii

LIST OF FIGURES Figure Page Figure 1.1 Re-sampled data null distributions for each class of individuals…….16 Figure 2.1 Pairwise F ST /(1-F ST in 2 Texas populations indicates no genetic isolation by distance over the scales sampled. ) among collared peccary (P. tajacu) herds a) Chaparral Wildlife Management Area ………………….…....38 b) Big Bend Ranch State Park…………………...………………38 Figure 2.2 Direct observation of collared peccary transfer among herds within the CWMA population as inferred from 3 years (1995-1998) of trapping data………………………………………………………………………………....41 Figure 3.1 Chaparral Wildlife Management Area, Texas .................................... 49 Figure 3.2 Welder Wildlife Refuge, Texas……………………………………….….49 Figure 3.3 Big Bend Ranch State Park, Texas……………………….…………….50 Figure 3.4 Reconstructed pedigree within a herd of collared peccaries (P. tajacu) in Big Bend Ranch State Park,Texas……………………………...63 Figure 3.5 Poisson regression indicates no significant relationship between the number of putative full siblings an individual has within the herd and the number of offspring assigned to it using Cervus parentage analysis. a) Females………………………………………………………....66 b) Males………………………………………………………….…67

viii

ABSTRACT Cooper, Jennifer Diane. Ph.D., Purdue University, May, 2009. Using genetic data to characterize dispersal patterns, relatedness and parentage in the collared peccary (Pecari tajacu). Major Professor: Peter M. Waser.

Heretofore, little was known of the population genetic structure, dispersal, genetic mating system or relationships of the collared peccary (Pecari tajacu). I sampled 268 individuals from 31 herds in 3 Texas populations. I haplotyped peccaries at a 449bp control region locus within the mitochondrial genome. Analysis of mtDNA haplotype distribution patterns across Texas indicates that P. tajacu has recently expanded its range, a result congruent with historical accounts of the recent colonization by collared peccaries of the American southwest.

I utilized mtDNA haploype data to estimate sex-specific natal dispersal rates through sex-specific comparisons of genetic variation among social groups. AMOVA analyses yielded fixation index values for females which were significantly larger than values for males. I also calculated a rate of male dispersal among social groups of 0.37. These results indicate that mtDNA can be used to infer instantaneous dispersal behavior for both sexes, despite a pattern of matrilineal inheritance

Collared peccaries exhibit several traits that differentiate them from suids, including a mixed-sex grouping pattern and sexual monomorphism. There has

ix

been debate concerning the importance of social dominance in maximizing male reproductive success. I used 11 polymorphic microsatellites (6 of which I developed for P. tajacu via cloning) to produce a multi-locus genotype for all individuals. I tested genetic relationships among adults and assigned parents to 75 offspring. My results indicate that herds comprised a mixture of relatives and non-relatives of both sexes. I used pairwise relatedness (r) estimates between adult males and adult females within herds to classify 38% of males as dispersers, a rate comparable to that inferred from the mtDNA analysis. Relationship analyses also revealed a low degree of female dispersal, a result that clarifies the source of the modest degree of female mtDNA haplotype admixture females within herds.

Parentage data suggest that males either disperse multiply or successfully father offspring in neighboring herds. Multiple males sire offspring within a herd, and there was no evidence for reproductive skew in either sex. Clearly, neither males nor females monopolize reproductive success, thus competition may play a smaller role mating system than was previously suggested.

1

CHAPTER 1. QUANTIFYING MALE-BIASED DISPERSAL AMONG SOCIAL GROUPS IN THE COLLARED PECCARY (PECARI TAJACU) USING ANALYSES BASED ON MTDNA VARIATION 1.1. Introduction

Sex bias in natal dispersal is common; in most mammalian species, males are dispersers while females are philopatric, and the opposite trend is exhibited in birds (Greenwood 1980). Exploring why the sexes differ in their dispersal patterns can shed light on the evolutionary causes of dispersal in general (Goudet et al. 2002), and accurate characterization of dispersal behavior is integral to our understanding of the social structure, mating system, and population genetic structure of a species. Yet detection of sex-biased dispersal can be tricky because a dispersal event may occur once in an animal’s lifetime, and such events can be difficult to observe directly. 1.1.1. Measuring dispersal

In the last few decades molecular genetics has provided a means of investigating sex-biased dispersal within and among populations (reviewed in Lawson-Handley and Perrin 2007). Several powerful approaches have been developed to detect individual dispersers through assignment tests or to characterize general patterns of dispersal through summary statistics of population genetic structure (F-statistics, relatedness). Most of these approaches utilize autosomal microsatellites as molecular markers, either alone

2

(Goudet et al. 2002; Mossman and Waser 1999; Petit et al. 2001; Waser et al. 2001) or in tandem with a uni-parentally inherited marker such as mtDNA or a Y chromosome locus (Escorza-Trevino and Dizon 2000; Girman et al. 1997). The expectation inherent to all these approaches is that greater genetic structure will be evident in the philopatric sex compared to the dispersing sex, thus comparisons of sex-specific F ST 1.1.2. Using sex-specific fixation indices to estimate instantaneous dispersal rates estimates should reveal the direction (and suggest the relative strength) of sex-bias in dispersal (Goudet et al. 2002).

Because mitochondrial DNA is matrilineally inherited, it is commonly used to infer female-biased dispersal rates (Prugnolle and de Meeus 2002). When mtDNA haplotype distribution patterns are examined in isolation, inferences can be made about female dispersal behavior without respect to males, but this approach is qualitative and not widely applied (Hoelzer et al. 1994). However, it is possible to use mtDNA alone to infer the relative dispersal of both sexes by extending methods developed for autosomal, bi-parentally inherited markers. For instance, the comparisons of sex-specific population differentiation from haplotype frequency data can indicate which sex disperses more (Escorza- Trevino and Dizon 2000; Yang et al. 2003).

Vitalis (2002) developed a method to quantitatively measure sex bias in instantaneous dispersal rates using data from bi-parentally inherited markers such as microsatellites. This approach allows the inference of sex-specific dispersal rates by comparing sex-specific estimates of genetic differentiation (F ST ) measured before and after dispersal. This intuitive method can be further extended to incorporate the hierarchical structure within social species (Fontanillas et al. 2004), as it has been recognized that social organization can

3

strongly influence correlations of gene frequencies (Chesser 1991; Chesser and Baker 1996; Slatkin and Voelm 1991; Sugg and Chesser 1994; Vigouroux and Couvet 2000). Herein we use an extension of the Vitalis (2002) method to estimate instantaneous dispersal rates through analyses of mtDNA haplotype distribution patterns in a social mammal, the collared peccary (Pecari tajacu, family Tayassuidae).

We sampled extensively within three populations separated by long distances, with the goal of quantifying local dispersal among breeding groups within populations. We then compared sex- and age-specific estimates of population differentiation based solely on mtDNA haplotype frequencies, using identity-probability based estimates of intra-class correlations of gene frequencies among social groups within populations. We used a resampling approach to test for the significance of the observed age-, sex- or class-bias in dispersal. Last, the fixation indices generated by these analyses were used to calculate single-generation sex-specific dispersal rates. Heretofore mtDNA has been used primarily to infer female dispersal patterns, but we demonstrate that this matrilineally-inherited genetic marker can be used to quantify male dispersal rates in the absence of nuclear population genetic data.

1.2. Materials and Methods

1.2.1. Study species

The collared peccary is a socially complex, pig-like ungulate that forms stable, mixed sex herds of 3 to 30 individuals (Sowls, 1978). These groups associate throughout the year and vigorously defend territories against other

4

social groups (Bissonette 1982; Hellgren et al. 1984; Ellisor and Harwell 1969). Herds are socially cohesive and attempts to immigrate may be met with aggression, although direct observational data on dispersal behavior are still scarce. Male exchange between groups and solitary wandering of both sexes has been observed but natal dispersal has not been adequately described (Day 1985; Ellisor and Harwell 1969; Gabor and Hellgren 2000). Heretofore little population genetic data existed for P. tajacu (but see Gongora et al. 2006). Theimer and Keim (1994) utilized mtDNA variation to measure sequence divergence and geographic partitioning in Arizona populations, but their samples were not associated with social groups. There was sufficient heterogeneity in mtDNA haplotype distribution to indicate limited female dispersal across regions (rather than among neighboring herds as is considered here), although it was not clear if the patterns observed were also a signature of founding events (Theimer and Keim 1994). 1.2.2. Sampling

Data were collected from three wild populations of P. tajacu in Texas. In the mid-1990s, 102 whole blood samples were collected from the Chaparral Wildlife Management Area (CWMA) in south Texas (Gabor and Hellgren 2000). These samples were taken from live-trapped animals from 13 social groups, but not all group members were sampled. In 2005, we collected 31 ear snip tissue samples from live-trapped animals from 4 groups in the Welder Wildlife Refuge (WWR) in south Texas. In 2006-2007 we similarly sampled 134 animals from 13 groups in Big Bend Ranch State Park (BB) in west Texas, along the Texas- Mexico border. The WWR and BB populations were sampled extensively; every social group at these locations was identified through direct and remote camera observation and trapped in large corrals over several sessions. Groups ranged in size from 2 to 18 animals, and mean group size was 8.9. Individuals were uniquely marked with numbered ear tags and the strongest possible effort was

5

made to trap and sample every unmarked individual. All samples include associated data on age class (adult, subadult, juvenile, infant), sex, territory location and social group affiliation. Age class was assigned according to behavior and morphological traits such as pelage, body size and testicular development (rather than tooth eruption). Individuals exhibiting immature characteristics such as ginger or spotted pelage, undescended or partially descended testicles, adult-oriented following behavior, or estimated body size of less than 9 kg were classed as infants or juveniles, while individuals which weighed 10-13 kg were classed as “subadults” (on the cusp of sexual maturity). Whole blood samples were frozen at -20°C, and tissue samples were stored in lysis buffer at room temperature until DNA was extracted for long-term storage at 4°C. 1.2.3. Genetic analysis

Blood clot samples (~ 0.5 g) were digested by rotating for 12 hours at 55°C in 750 µL of lysis buffer (100 mM Tris-Cl pH 8, 10 mM EDTA, 1% SDS, ddH 2 O), 40 µL of proteinase K (10 mg/mL) and 2 µL of streptokinase (10 U/µL). Tissue samples (~ 5 X 5 mm) were digested by rotating for 24 hours at 55°C in 750 µL of lysis buffer and 20 µL of proteinase K (10 mg/mL). Genomic DNA was extracted from blood using a standard phenol-chloroform method, and from tissue samples using either a phenol-chloroform-isopropanol method or ammonium acetate method (Sambrook and Russell 2001). All DNA precipitations were washed twice in 70% ethanol, and DNA pellets were re- suspended in 250 µL of TLE (10 mM Tris-Cl, 0.1 mM EDTA). A 449 bp region between sites 15,390 and 15,900 of the collared peccary mtDNA D-loop was amplified from genomic DNA using porcine primers (Alves et al. 2003). This sequence lies in the hypervariable 5’ end of the control region and does not code for any known protein product. PCR volumes were 25 µL and contained final

6

concentrations of the following reagents: 1.5 mM MgCl; 0.5 µM each primer; 0.21 mM dNTPs; 1.25 U Taq polymerase (NEB). PCRs were performed in an Eppendorf MasterCycler using the following temperature profile: denaturation for 3 min. at 94° C, followed by 30 cycles of 94° C for 4 s, 55° C for 4 s, and 72° C for 12 s; finishing with a 15 min. extension step at 72° C. PCR products were cleaned using a low sodium protocol; 28 µL of a mixture containing 500 ml of absolute ethanol and 20 µL of 3M NaOAc (pH 5.2) was added to each sample, shaken for 15 min, and centrifuged at 2051 g for 35 min. This step was followed by 70% ethanol precipitation under centrifugation (twice) and re-suspension in 20 µL ddH 2 0.

PCR products were then directly sequenced in both directions using Big Dye 3.1 chemistry. Sequencing products were purified using the low sodium protocol described above, and then electrophoresed using an AB Prism 3730XL sequencer (Applied Biosystems). Sequence data were aligned and edited with Sequencher 4.5 (Gene Codes), then converted into NEXUS format and imported into PAUP* 4.0 (Swofford 2003) for haplotype assignment. Haplotypes were determined through reconstruction of unrooted phylogenetic trees using a neighbor-joining algorithm. Direct sequencing of a sub-set of the CWMA population revealed that some of the mtDNA haplotypes could be discriminated by restriction digest with the MboI enzyme, but all individuals from WWR and BB were typed by direct sequencing.

7

1.2.4. Statistical analyses 1.2.4.1. Among population differentiation

MtDNA haplotype frequencies were calculated by hand for all three populations. Genetic differentiation among populations was inferred from F ST 1.2.4.2. Within population differentiation

estimates (Weir and Cockerham 1984) and exact tests of population differentiation (Raymond and Rousset 1995), both overall and between population pairs, using the software package Arlequin Version 3.1 (Excoffier et al. 2005). For the latter, p-values were estimated from a Markov chain set to 110,000 steps including 10,000 dememorization steps. All analyses were based on pure haplotype frequency data rather than nucleotide differences.

Because P. tajacu populations are further subdivided into breeding groups, we incorporated breeding group as a hierarchical level. We calculated identity probabilities by simple counting of identical pairs of genes at different hierarchical levels (Q 1 for pairs of genes within groups, Q 2 for pairs of genes sampled among groups within populations, and Q 3 for pairs of genes sampled in different populations). We then estimated the intra-class correlations by taking appropriate ratios of identity probabilities, weighted according to the number of pairs in each sample (see Rousset 2007), following the definitions of F-statistics as functions of identity probabilities between pairs of genes (see Appendix). Since the distances among populations are large in this study (range of 225 km to 945 km between the three sampling sites), we considered the three populations as independent replicates in the analysis, and we restricted our analyses to estimate within-population dispersal. We focused on the level of genetic differentiation among social groups within populations as measured by

8

the parameter F GP . The notation is adapted from Wright's (1965). This approach is different from that of Fontanillas et al. (2004) who considered dispersal both among populations and among breeding groups. Although the samples from each site were collected in different years, F GP estimates do not depend upon identity between pairs of genes from different populations and temporally discontinuous sampling is therefore unlikely to undermine the approach. We employed a bootstrapping procedure to calculate confidence limits around estimates of F GP for each class of individuals. Using the statistical software package R (R Development Core Team 2008), we generated 25,000 bootstrap samples, with each sample being produced by random resampling (with replacement) of the 255 polymorphic sites from the mtDNA haplotypes (254 sites + 1 indel). This allowed us to calculate F GP 1.2.4.3. Class-specific analyses

estimates for each sample and generate a distribution; confidence intervals were then calculated as falling within the 2.5% and the 97.5% percentiles of this distribution.

Dispersal is a trait that can always be partitioned into pre- and post- dispersal conditions, therefore our first analysis partitioned the data by age. We performed separate analyses independently on data partitioned into two age sets, respectively for adults and immatures (the latter including both juveniles and infants). Subadults were classed as immatures and then as adults in sequential analyses. Each age-specific data set was composed of individuals assigned to their respective populations and social groups, and intra-class correlations were calculated among populations, among social groups within populations, and within social groups (see above). Only those social groups containing a representative individual from each treatment were included in the analysis (e.g. in the independent analyses on adult and immature data sets, a social group must have contained at least 1 adult and 1 immature to be included). We then duplicated the analysis with the data partitioned by sex rather

9

than age. From these results, we were able to distinguish a putative class of dispersing individuals, from a putative class of non-dispersers. We therefore performed, a posteriori, independent analyses on data sets of putative dispersers and non-dispersers.

We used a resampling scheme after Goudet et al. (2002) to test whether the estimated fixation indices among social groups within replicate populations (F GP ) for specific classes (age, sex, or putative dispersal class) departed significantly from the null hypothesis that dispersal is independent from the class of individuals. Re-sampling tests were all performed with the statistical software package R (R Development Core Team 2008). For each class, we generated 25,000 randomized datasets, by re-assigning the age (or sex, or dispersal class) of each haplotype randomly within each breeding group. By doing so, we kept the number of individuals from each class constant within each breeding group. We calculated the probabilities of identities between pairs of genes for each resampled dataset, and obtained the distribution of class-specific F GP estimates under the null hypothesis that dispersal behavior or capability is independent from age, sex, or dispersal class. We then calculated p-values as the proportion of times where F GP from the randomized datasets was larger than or equal to the observed F GP 1.2.4.4. Estimating dispersal

on the original dataset.

To calculate a sex-specific dispersal rate within a single generation, we adapted Vitalis’ (2002) approach and extended it to mtDNA data. In Vitalis (2002), the ratio of the sex-specific differentiation evaluated after juvenile dispersal over the differentiation evaluated before dispersal gives the sex-specific dispersal rate. Appendix 1 shows that this relationship also applies to uni- parentally inherited markers, and:

10

ˆ m X ≈1− ˆ F G P X X ˆ F G P * for all X ∈ {♂,♀} (1)

gives the sex-specific dispersal rate. Here we use this simple model to compare fixation indices before and after dispersal at the within-population level, focusing on dispersal of individuals among breeding groups (F GP ). This equation assumes that the number of breeding groups, n, is large (infinite); by considering an infinitely large n, we slightly overestimate dispersal rate m x (e.g., 10% relative bias with n = 10). We estimated instantaneous sex-specific dispersal rates for P. tajacu by applying equation 1, using fixation indices estimates for adult males, adult females and all immatures of both sexes (Table 1.3). Confidence intervals for dispersal rates were obtained by means of a bootstrap procedure, similar to that used for F GP (see above), modified as follows. For each bootstrap sample, F GP 1.3. Results

estimates were calculated for adult males (resp. adult females) and all immatures, and male- (resp. female-) specific migration rates were calculated using equation (1). Confidence intervals for sex-specific dispersal rates were then derived from the 0.025 and 0.975 percentiles of the bootstrap distribution. 1.3.1. mtDNA haplotype distribution patterns

A total of 18 nucleotide sites were variable (17 substitutions and a single indel) over 449 bp. We recovered 6 mtDNA haplotypes from 267 individual collared peccaries among the 3 sites sampled (Table 1.1). Haplotype A was observed in all sampling sites, but haplotype B was unique to the CWMA, and haplotype C was found in both the WWR and the CWMA. The BB population

11

was almost fixed for haplotype E (96%). Haplotypes F and G were only found in the CWMA, and were represented by single individuals (both males).

We overlaid mtDNA haplotype distribution onto the social group territory distribution for all populations. At the local level, haplotype distribution did not exhibit geographic structuring in the CWMA or the WWR; all haplotypes present at each sampling site were found distributed throughout that site. In the BB population, haplotype A was found only in the eastern portion of the sampling site. At the regional level across Texas, we observed significant population differentiation. Pairwise F ST estimates ranged from 0.31 to 0.86 between populations and pairwise exact tests of population differentiation were highly significant, indicating that these populations are significantly divergent from one another (Table 1.2).

12

Table 1.1 Distribution of mtDNA haplotypes in three wild populations of P. tajacu in Texas, across sex and age classes.

Sex

Age class

Population

Haplotype

n

Freq.

F

M

I

J

A

WWR

C

24

0.77

10

14

1

6

17

A

7

0.23

3

4

0

3

4

CWMA

B

43

0.43

24

19

1

10

32

A

38

0.38

21

17

1

9

28

C

19

0.19

9

10

3

2

14

G

1

0.01

0

1

0

0

1

F

1

0.01

0

1

0

0

1

BB

E

129

0.96

61

68

13

35

81

A

5

0.04

3

2

0

0

5

n: sample size; F: females, M: males; I: infants; J: juveniles; A: adults (including subadults)

Table 1.2 Pairwise genetic differentiation among three P. tajacu populations, based on mtDNA haplotype frequencies. Inferred from F ST

estimates (below diagonal) and Fisher’s exact tests of differentiation (above diagonal), with p- values estimated from a Markov chain set to 100,000 steps and 10,000 dememorization steps. WWR CWMA BB WWR – 0.001 0.001 CWMA 0.31 – 0.001 BB 0.86 0.66 _

13

1.3.2. Patterns of genetic variation revealed by F-statistics as functions of identity probabilities

Because dispersal status is often dependent upon age, we tested for an age bias in dispersal. To that end, we pooled infants and juveniles (categorized hereafter as “immatures”) in one class, and adults in another class. It was not clear if individuals categorized as subadults were sufficiently developed to be considered as adults, therefore we performed a preliminary analysis on adult- only and immature-only data sets partitioned into social groups, which revealed a decrease in F GP when subadults were included in the adult class (not shown). This result indicates that individual genetic variation in the subadult class is apportioned among rather than within social groups, and therefore subadults were classed as adults in all subsequent analyses. We estimated fixation indices among social groups for each sex, with individuals partitioned into known breeding groups (Table 1.3). It is clear that F GP for adults (0.296 [0.032, 0.380]) is much smaller than that for immatures (0.602 [0.602, 1.000]), as would be expected if the adult class included dispersed individuals. To test for significance of these quantitative differences, we used a randomization approach, and generated randomized data sets by assigning an age randomly to each mtDNA haplotype. Under the null hypothesis that dispersal is not age-biased, we expect the observed F GP of adults and immatures not to depart significantly from the null distribution. For adults, there was a very large proportion of randomized data sets with a differentiation among groups within populations (F GP ) larger than the observed (p = 0.788; Fig. 1A). In contrast, for immatures of both sexes, there was only a small proportion of randomized data sets giving a F GP larger than the observed, although the test was not significant (p = 0.199; Fig. 1B). In general terms, these results clearly indicate a greater amount of dispersal among social groups for adults when compared to immatures.

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Abstract: Heretofore, little was known of the population genetic structure, dispersal, genetic mating system or relationships of the collared peccary (Pecari tajacu ). I sampled 268 individuals from 31 herds in 3 Texas populations. I haplotyped peccaries at a 449bp control region locus within the mitochondrial genome. Analysis of mtDNA haplotype distribution patterns across Texas indicates that P. tajacu has recently expanded its range, a result congruent with historical accounts of the recent colonization by collared peccaries of the American southwest. I utilized mtDNA haploype data to estimate sex-specific natal dispersal rates through sex-specific comparisons of genetic variation among social groups. AMOVA analyses yielded fixation index values for females which were significantly larger than values for males. I also calculated a rate of male dispersal among social groups of 0.37. These results indicate that mtDNA can be used to infer instantaneous dispersal behavior for both sexes, despite a pattern of matrilineal inheritance. Collared peccaries exhibit several traits that differentiate them from suids, including a mixed-sex grouping pattern and sexual monomorphism. There has been debate concerning the importance of social dominance in maximizing male reproductive success. I used 11 polymorphic microsatellites (6 of which I developed for P. tajacu via cloning) to produce a multi-locus genotype for all individuals. I tested genetic relationships among adults and assigned parents to 75 offspring. My results indicate that herds comprised a mixture of relatives and non-relatives of both sexes. I used pairwise relatedness ( r ) estimates between adult males and adult females within herds to classify 38% of males as dispersers, a rate comparable to that inferred from the mtDNA analysis. Relationship analyses also revealed a low degree of female dispersal, a result that clarifies the source of the modest degree of female mtDNA haplotype admixture females within herds. Parentage data suggest that males either disperse multiply or successfully father offspring in neighboring herds. Multiple males sire offspring within a herd, and there was no evidence for reproductive skew in either sex. Clearly, neither males nor females monopolize reproductive success, thus competition may play a smaller role mating system than was previously suggested.