Journal of Heredity 2004:95(2):144-153
© 2004 The American Genetic Association
Genetic Consequences of a Severe Population Bottleneck in the Guadalupe Fur Seal (Arctocephalus townsendi)
From the Department of Biological Sciences, University at Albany, State University of New York, Albany, NY 12222 (Weber and Lehman) and Hubbs-SeaWorld Research Institute, San Diego, CA 92109 (Stewart). N. Lehman is currently at the Department of Chemistry, Portland State University, P.O. Box 751, Portland, OR 97207. D. S. Weber is currently at the Molecular Systematics Lab, American Museum of Natural History, Central Park West at 79th Street, New York, NY 10024. We thank J. Heyning and D. Janiger for access to archaeological bone samples from the collection at the Los Angeles County Museum of Natural History, G. Bernardi for providing DNA sequences from modern Guadalupe fur seals, A. Jacklet, R. Osuna, and D. McKeon for providing facilities for analysis of ancient DNA, and D. Decker, J. Fahy (Qiagen), J. deKoning, T. Pratt, D. Pryor, J. Schienman, C.-B. Stewart, K. A. Walker, K. L. Walker, J. VanderKelen (Qiagen), H. Weber, and P. Yochem for technical assistance and suggestions. This work was supported by grants from Sigma Xi, the University at Albany Benevolent Society, the University at Albany Graduate Student Organization, and the Hubbs-SeaWorld Research Institute.
Address correspondence to Niles Lehman, Department of Chemistry, Portland State University, P.O. Box 751, Portland, OR 97207, or e-mail: niles{at}pdx.edu.
 |
Abstract |
|---|
 Top Abstract Materials and MethodsResults and DiscussionReferences |
|---|
Population bottlenecks may lead to diminished genetic variability and correlative effects on fitness. The Guadalupe fur seal was nearly exterminated by commercial sealers during the late 18th and early 19th centuries. To determine the genetic consequences of this population bottleneck, we compared the variation at a 181 bp section of the mitochondrial DNA (mtDNA) control region from the bones of 26 prebottleneck fur seals versus variation in the extant population. We found 25 different mtDNA genotypes in the prebottleneck fur seals and only 7 genotypes among 32 extant fur seals, including only one of the ancient genotypes. These data demonstrate a substantial loss of genetic variability correlating with the recent population bottleneck. We also found from several genetic measures that the prehistoric population of Guadalupe fur seals was robust and that it had been increasing at some time during the late prehistoric period. Continued recovery of this species may, however, owe more to more immediate nongenetic factors, such as poaching and local availability of food resources during the breeding season and consequent effects on pup survival, than on the reduced genetic variability.
Anthropogenic disturbances to wildlife populations by direct harvesting or habitat destruction often result in substantial reductions in population size (population bottlenecks) and loss of genetic variability (genetic bottlenecks). Lowered allelic diversity, greater frequency of linkage disequilibrium, and reduced heterozygosity are some of the observed or inferred consequences of those bottlenecks (Hartl and Clark 1997; Hedrick 2000). The consequences of genetic bottlenecks vary from species to species and are often strongly reflective of demographic factors, though it has been generally held that substantial genetic variation is essential for population vitality and persistence (Amos 1996; Caro and Laurenson 1994; Hedrick 1996; O'Brien 1994; O'Brien et al. 1987). The frequency of rare, deleterious recessive alleles—the genetic load—can increase after a population decline, resulting in reduced fitness through inbreeding depression (cf. Amos 1996). However, both theory (Nei et al. 1975) and experiment (Miller and Hedrick 2001) have suggested that the impacts of severe bottlenecks may be minimized if subsequent recovery is rapid, and that fitness may actually increase in some instances. Fitness may often decline, however, in populations that recover more slowly, owing to greater reductions in heterozygosity (e.g., Bouzat et al. 1998; Westemeier et al. 1998).
The populations of most species of seals (family Phocidae) and sea lions (family Otariidae) were reduced substantially by commercial sealers and whalers in the 18th and 19th centuries, and some may have been reduced centuries earlier by coastal aborigines (Lyons 1937; Reeves and Stewart 2003; Reeves et al. 1992, 2002; Stewart et al. 1993; Wynen et al. 2000). In fact, most species of fur seals were presumed to be extinct by the late 19th century. The prehistoric and even presealing distribution and abundance of Guadalupe fur seals (Arctocephalus townsendi) are poorly known (cf. Etnier 2002; Gustafson 1968; Stewart et al. 1993). At least 52,000 Guadalupe fur seals had evidently been killed at several islands off the Pacific coasts of Mexico and the United States from the late 1700s to 1848, and the last few were harvested in Mexican waters in the late 1800s (Townsend 1931). This species was then presumed extinct (Townsend 1916) until a small breeding group was discovered at Isla de Guadalupe (Figure 1) in 1928 (Townsend 1928, 1931). Collections for zoos and museums and poaching evidently eliminated that colony soon after discovery, and the species was again thought to be extinct until a single male was seen at San Nicolas Island in 1949 (Bartholomew 1950). A small breeding group of 14 seals was then discovered at Isla de Guadalupe in 1954 (Hubbs 1956). The colony has grown exponentially (r = 13.7%) since then (Fleischer 1978; Gallo-Reynoso 1994), and numbered between 7400 and 12,000 in the late 1990s (Gallo-Reynoso 1994; Stewart 1997). Another small breeding colony became established on Isla Benito del Este in 1997 (Maravilla-Chavez and Lowry 1999).
|
Despite repeated, substantial reductions in population size during the past few centuries, genetic diversity of the Guadalupe fur seal is relatively high in the extant population. Seven genotypes, with 18 polymorphic nucleotide sites, were found in a 313 bp segment of the mitochondrial DNA (mtDNA) control region in 25 extant Guadalupe fur seals (Bernardi et al. 1998). Nonetheless, we hypothesized that some loss of genetic variability should have occurred during the population bottleneck in the 19th century, owing to its severity and duration before recovery began in the mid-20th century. Our goals in this study were (1) to document prebottleneck patterns of genetic variability in Guadalupe fur seal and (2) to evaluate the effects of the recent population bottleneck on various measures of genetic variability. To achieve those goals, we extracted DNA from the bones of 26 Guadalupe fur seals recovered from archaeological sites in southern California and assayed a 181 bp segment of the mtDNA control region containing most of the variation recently detected in seals from the extant population (Bernardi et al. 1998).
|
Materials and Methods |
|---|
|
TopAbstractMaterials and MethodsResults and DiscussionReferences |
|---|
Sample Collection
We obtained bones of 57 Guadalupe fur seals collected from prebottleneck (i.e., estimated age predating commercial exploitation) archaeological kitchen sites (middens) from Point Mugu, California, or from the nearby southern California Channel Islands (Figure 1). These bones were archived at the Natural History Museum of Los Angeles County. We attempted DNA extraction from 50 right femur samples to ensure uniqueness of individual genotypes, as well as from 7 humerus samples. The successfully analyzed humeri bones (FS-51, FS-54, and FS-55) were from different collections than all other bones, eliminating the possibility that any of the femurs and humeri were from the same individual (Table 1). We determined genetic variation in the extant population from (1) mtDNA sequences of 313 bp from 25 seals reported by Bernardi et al. (1998), and (2) tissue samples that we obtained from seven additional seals found injured or deceased along the southern California coast during the 1980s and 1990s.
|
DNA Extraction, Amplification, and Sequence Analysis
First, we extensively sanded the outer surface of each bone. Then we removed a small sample (4–5 g) from each bone, ground it into a powder with liquid nitrogen, and decalcified it in 0.5 M ethylenediaminetetraacetic acid (EDTA) for 5–14 days. Decalcification was confirmed by the absence of a precipitate in the supernatant when a solution of saturated ammonium oxalate was added. We obtained DNA from the bone powder using the DNeasy tissue kit (Qiagen) and the protocol for isolation of genomic DNA from compact bone (Qiagen User Developed Protocol DY01; Yang et al. 1998). We modified this procedure in two ways to maximize the overall DNA yield: first, we lysed the bone pellet overnight (instead of a few hours), and second, we eluted with only 50 µl (rather than 200 µl) of water to increase the final DNA concentration.
Ancient DNA is normally severely degraded and in small fragments, but our samples were potentially even more so, having originated from southern California beaches, not from cold or low-ultraviolet (UV) environments (higher latitudes, caves, etc.). Therefore, prior to polymerase chain reaction (PCR), we accomplished template reconstruction via a PCR-like method without primers ("primerless template reconstruction"; Stemmer 1994). We found here, as elsewhere (Weber et al. 2000), that our success at amplifying ancient DNA (aDNA) from sources such as these is greatly enhanced with this technique. In each case, we performed primerless template reconstruction on 8 µl of bone extract in a 50 µl reaction volume with 1.25 U AmpliTaq DNA polymerase (Perkin-Elmer), the manufacturer's supplied standard buffer with 1.5 mM MgCl2, and 0.2 mM deoxynucleotide triphosphates (dNTPs). An initial denaturation for 3 min at 94°C was followed by 25 cycles of 92°C (1 min), 50°C (1 min), 72°C (1 min), and a final extension step of 72°C for 10 min. We then achieved amplification of the resulting template reconstruction via a two-step ("nested") procedure of the 5' segment of the mtDNA control region. Ten microliters of the primerless product served as the template for the external (first step) PCR in a 50 µl reaction volume with 10 pmol of each primer and a standard PCR mix as outlined above. The cycles were adjusted for a profile of 3 min at 95°C, followed by 40 cycles of 92°C (30 s), 48°C (30 s), 72°C (30 s), and a final extension at 72°C for 10 min. Typically 1 µl of the resulting solution served as the template for the internal (second step) 50 µl PCR with parameters of 4 min at 94°C followed by 25 cycles of 92°C (1 min), 53°C (1 min), 72°C (1 min), and a final extension at 72°C for 10 min. The use of external primers (ONL-4a: 5'-GTTGCTGGTTTCTCGAGGC-3' and GFS-15a: 5'-CTGTGCCACCATAGTATC-3') followed by internal primers (fully nested: ONL-16: 5'-TCGCGGGCTAGGTGAATTGC-3' and ONL-17: 5'-CCCTATGTACGTCGTGC-3' or seminested using one of the external primers) provided a stepping-stone process to obtain intact DNA fragments from bones.
We obtained nucleotide sequences of the purified PCR products (QIAquick PCR purification kit, Qiagen) by one or both of the following methods. First, we performed bidirectional manual sequencing using [
-35S]dATP and Sequenase 2.0 (US Biochemical) with resolution on 6% polyacrylamide/8 M urea gels and visualization by autoradiography. Second, we performed bidirectional automated sequencing using the BigDye Terminator technology (Applied Biosystems) with resolution on a 373A DNA genetic analyzer (Applied Biosystems). Modern seals provided a 212 bp segment that included all of the mtDNA segment provided by the bone samples. We obtained genomic DNA from the tissue and blood samples with the DNeasy tissue kit (QIAGEN) and performed a single PCR procedure using the external primers and procedure listed above. After purification we obtained nucleotide sequences bidirectionally by the automated method described above.
Contamination Controls
Patterns of historical population genetics can be examined with samples of aDNA (e.g., Cooper and Wayne 1998), but adequate samples are often difficult to obtain from weathered specimens and may be contaminated in the process by modern DNA (e.g., Austin et al. 1997). Prevention of contamination during the amplification process is the key concern in studies of aDNA (cf. Hagelberg 1994; Hagelberg and Clegg 1991; Hummel and Herrmann 1994). Consequently rigorous controls have been established to minimize and prevent the risk of contamination, and to ensure the integrity and purity of aDNA samples, we took the following precautions. We processed all bones for aDNA in laboratory facilities at the University at Albany (State University of New York) that are dedicated to studies of aDNA and that are spatially isolated by two floors from facilities used for DNA amplification. We then transported bone DNA extracts to a dedicated PCR setup room with a UV light–containing hood (CBS Scientific) separate from facilities where subsequent purification and sequence determination of the products occurred. For nested PCR, we manipulated amplified DNA in a separate hood in yet another room from the room with the hood used for the PCR setup. Because the samples were subjected to three different protocols using Taq DNA polymerase, we conducted numerous controls to ensure that we obtained accurate sequences.
We processed two aliquots per bone extract as separate samples from start to finish, that is, from DNA extraction through sequence analysis. We compared the two resulting sequences in order to ascertain that the aliquots did indeed give the exact same sequence for that individual. In addition, for each of the two bone extracts for each individual, we processed the two aliquots a second time in parallel beginning from the primerless template reconstruction stage and taken through nested PCR and sequence analysis to ensure that identical sequences were obtained both times in the two aliquots. Consequently, for each successful bone extract, four separate sequences were obtained and compared. We also obtained second, independent extracts from the bones of three of the seals (FS-12, FS-50, and FS-6) and amplified and compared the DNA sequences to those resulting from the original extracts (Table 1). We attempted amplifications of negative control tubes open during the extraction process in all cases, and negative controls were included in every PCR amplification performed, usually several. Lastly, we minimized contamination from modern fur seals by amplifying the bones prior to the amplification of any of the seven modern tissue samples.
Data Analysis
We inspected sequences obtained from the ABI 373A using the program SEQUENCHER (version 5.2; Gene Codes Corp.). We then aligned all sequences with CLUSTALX 1.81 (Thompson et al. 1997) and GeneDoc 2.6.002 (Nicholas et al. 1997). We endeavored to obtain general phylogenetic relationships between the ancient and modern genotypes, in comparison to other fur seal mtDNA sequences. The limited number of phylogenetically informative sites in our samples precluded an unambiguous phylogenetic reconstruction. However, using PAUP* (version 4.0b10; Swofford 2002), we were able to estimate the general relationships of ancient and modern mtDNA lineages. In PAUP*, we employed the distance matrix-based method using a maximum-likelihood variant of the HKY85 model with minimum evolution optimality criterion. The HKY85 model allows for different transversion and transition rates and different base frequencies, both of which are the two most significant sources of bias. In order to test if the modern samples are a subset of the ancient samples, we found the best tree under the constrained null hypothesis of monophyly for all modern samples relative to all ancient and outgroup taxa. We calculated likelihoods for both the constrained (null; modern samples constrained to form a monophyletic clade with respect to all other taxa) and unconstrained trees, using an equivalent substitution model (HKY85 variant). We performed the likelihood-based Shimodaira-Hasegawa test to determine whether the data significantly distinguish between the two tress. The P value was calculated using a simulated distribution of test statistics by 1000 RELL bootstrap resampling in PAUP* 4.0b10. Additional sequences for the phylogenetic analysis included the northern elephant seal (Weber et al. 2000), plus the following Arctocephalus species (Wynen et al. 2001): Juan Fernández fur seal (A. philippii; GenBank accession no. AF384405), Australian fur seal (A. pusillus doriferus; AF384395), sub-Antarctic fur seal (A. tropicalis; AF384384), South American fur seal (A. australis; AF384402), Antarctic fur seal (A. gazella; AF384377), and Galapagos fur seal (A. galapagoensis; AF384386).
We estimated several population genetic parameters for ancient and modern mtDNA: (1) number of distinct control region genotypes, (2) number of polymorphic sites, (3) haplotype (gene) diversity (h = probability that two mtDNA sequences chosen randomly from the sample are different), (4) nucleotide diversity (
= number of nucleotide differences between randomly chosen pairs of sequences), (5) proportion of variable nucleotide (segregating) sites (p), (6) Tajima's D test statistic, (7) Fu's FS test statistic, (8) average number of nucleotide differences (k = variance; Tajima 1993), (9) raggedness index (r = a statistical measure indicating distributions of stationary/expanding/contracting populations; Harpending et al. 1993), and (10) 
, both S (estimates of nucleotide polymorphism using = s/a) and . The population genetic program DnaSP (version 3.51; Rozas and Rozas 1999) provided h, , D, k, and the graphs for the mismatch distribution (also called distribution of pairwise differences), while ARLEQUIN (version 2.000; Schneider et al. 2000) provided FS, , and r, and determined the means of the mismatch distribution (pairs of genotypes analyzed for the distribution of observed number of differences; Schneider et al. 2000).
|
Results and Discussion |
|---|
|
TopAbstractMaterials and MethodsResults and DiscussionReferences |
|---|
We obtained mtDNA sequences from 26 prebottleneck Guadalupe fur seals. The sequences began approximately 86 bp from the terminus of the tRNA-Pro on the 5' end of the mtDNA control region and spanned 181 bp. We found 25 ancient genotypes among those 26 prebottleneck Guadalupe fur seals (indicated as FS1 through FS55; Figure 2). Twenty-four of the 25 genotypes have not yet been identified in extant Guadalupe fur seal populations, whereas one (FS25) matched one of the 7 genotypes reported by Bernardi et al. (1998) from 25 seals (Figures 2 and 3). In contrast, in our modern seal samples (N = 7) we found three genotypes, all of which match one of the previously published seven modern genotypes. These data indicate a substantial historical loss of mtDNA genotypes in the Guadalupe fur seal. Lineages from only two mtDNA clades appeared to have survived the bottleneck, one containing modern genotypes 1–4 and 7, and the other containing genotypes 5 and 6 (Figure 3). Because many bootstrap values in the reconstruction shown in Figure 3 are low, we performed tests of specific hypotheses to determine if the data significantly support this conclusion. The Shimodaira-Hasegawa test (using RELL bootstrap replicates) indicated that when the constrained tree has only the northern elephant seal as an outgroup and all other fur seal species are placed with the ancient samples, the data do in fact reject the null hypothesis that the modern samples are monophyletic (P =.034). We then tested a more conservative analysis in which the tree is further constrained, such that all non-Guadalupe fur seals are forced into the outgroup, and found that we again could not reject the monophyly of the modern samples (P =.003). Both tests support our contention that the modern seals are indeed a subset of the prebottleneck seals and that they possess two general surviving mtDNA lineages.
|
) has a genotype found in seals today. Question marks designate missing data; dashes indicate inferred gaps
|
The population bottleneck also resulted in a substantial loss in genotypic diversity. We found 51 variable nucleotide sites (26.5%) in the prebottleneck samples versus 18 (5.7%) in the extant population. However, 15 of the variable ancient sites were the result of only single nucleotide changes found in single genotypes. We confirmed that these were not artifacts caused by Taq polymerase error by comparing each of these genotypes against all other genotypes at other nucleotide sites and found no matches. Moreover, Taq has an introduced error rate of about 1.1 x 10–4 nucleotides polymerized (Tindall and Kunkel 1988), such that the likelihood that the same error would occur in our duplicate amplifications is less than 1 x 10–8.
Clearly the population bottleneck resulted in a substantial loss of genetic variability in the Guadalupe fur seal, similar to that reported for the sympatric northern elephant seal, which experienced a population bottleneck during the same time period (Weber et al. 2000). However, because many evolutionary factors may influence patterns of genetic variation in populations (Fu 1997), we also considered several other indices of polymorphism (Table 2). We found significantly fewer (P <.001, t' test) nucleotide differences between pairs of genotypes (k) of the prebottleneck versus modern seals (Table 2). Accordingly, nucleotide diversity () was significantly greater (P <.001, t test) for prebottleneck (0.055 ± 0.004) versus postbottleneck seals (0.025 ± 0.003). Nucleotide diversity in the presealing Guadalupe fur seal population is similar to that reported for extant populations of other species of fur seals (A. tropicalis, = 0.048; A. gazella, = 0.032; A. forsteri, = 0.051; A. philippii, = 0.030) (Goldsworthy et al. 2000; Wynen et al. 2000), all of which were reduced to near-extinction levels by commercial sealers in the 18th and 19th centuries. Other species impacted by humans (hunting or habitat reduction) show much lower values of nucleotide diversity today, such as the whooping crane (0.0045 for both pre- and postbottleneck) (Glenn et al. 1999) and the northern elephant seal (Table 3) (Weber et al. 2000). Because pairwise DNA sequence divergence estimates are influenced by the length of the sequence (Tajima 1993), we also measured haplotype (gene) diversity (h), which is the equivalent of heterozygosity for haploid loci (Nei 1987). Haplotype diversity was significantly greater (P <.001, t' test; Table 2) in the ancient (0.997 ± 0.012) versus the modern seals (0.80 ± 0.038). For comparison, the sea otter has apparently lost nuclear heterozygosity as a result of fur trapping (HE = 0.82 pretrapping versus 0.47 post-trapping), but this is not mirrored in a loss of mtDNA haplotype diversity (h = 0.37 pretrapping versus 0.41 post-trapping) (Larson et al. 2002).
|
|
The genetic consequences of founder events or population bottlenecks that result in a loss of genetic variability may be evaluated by comparing estimates of nucleotide diversity (
S) and heterozygosity () in populations before and after those events (Galtier et al. 2000; Hedrick 2000). Estimates of nucleotide diversity are strongly influenced by rare alleles, whereas estimates of heterozygosity are relatively insensitive to them. Consequently – S will be negative in large prebottleneck populations under an infinite-sites model of mutation drift equilibrium. In contrast, postbottleneck populations should be in disequilibrium as a result of a reduction in the number of sites segregating for different alleles, and – S should be positive. Assuming neutrality for the mtDNA control region, our data for the Guadalupe fur seal are consistent with an equilibrium state in the prebottleneck population ( – S = –1.544) and with a population in disequilibrium in the modern population ( – S = 1.815). We further evaluated the status of the ancient and modern fur seal populations by constructing mismatch distributions of pairwise differences among nucleotide sequences (Harpending 1994; Harpending et al. 1993; Hartl and Clark 1997). We found significant differences in population trends between the pre- and postbottleneck populations (P <.001, t' test), with a smooth distribution of sequence matches (raggedness statistic; r = 0.009) for the prebottleneck population, characteristic of an equilibrium status, but a substantial mismatch in the extant population (r = 0.101), characteristic of a recently bottlenecked, nonequilibrium population (Figure 4).
|
The inference that the prebottleneck Guadalupe fur seal population was at mutation drift equilibrium raises the issue of whether the Guadalupe fur seal population was stable or increasing prior to the 19th century bottleneck, which may have implications for continued recovery of the extant population. We used Tajima's D test to evaluate the presealing population status of Guadalupe fur seal, as negative D values are indicative of historical growth (Hartl and Clark 1997; Rogers et al. 1996). We found that the prebottleneck Guadalupe fur seal populations were in an expansion mode (D = –0.865), with the caveat that not all of our Guadalupe fur seal bones were likely to be from the same temporal population. The large positive value of D (1.35) for the extant population is consistent with a population that has been interrupted by a recent, substantial population bottleneck (Schneider and Excoffier 1999). Fu (1997) suggested the FS statistic as an alternative measure of detecting historical population growth. Large negative FS values are indicative of an excess of rare alleles, suggesting an increase in recent mutations during population expansion. The prebottleneck FS of –16.576 (highly significantly different from zero; P <.0001) is again consistent with historical population growth. Conversely the postbottleneck FS value of 4.423 (P =.94) implies that the modern population has few rare alleles as a consequence of the bottleneck. The consensus of our computed metrics of genetic variability is that there was a substantial loss of genetic variability in the Guadalupe fur seal during the population bottleneck caused by commercial sealing in the 19th century, and that the population had been growing at some time prior to that bottleneck.
Amos (1996) suggested that substantial loss of genetic variation generally requires near extinction or a prolonged period of low population abundance. Yet purging of deleterious recessive alleles during such reductions may sometimes minimize reductions in fitness otherwise associated with low genetic variability. In contrast, delays in population recovery can cause substantial losses in fitness due to the buildup of a genetic load of mildly deleterious alleles and more lethal, but recessive alleles in the heterozygous condition. Consequently the patterns of genetic variability in postbottleneck populations may be determined more by the patterns of population recovery than by the magnitude of the bottleneck alone. Our empirical evidence with mtDNA suggests that the presealing population of Guadalupe fur seals was a robust and outbred one of high fitness, in contrast to the small, inbred extant population. Moreover, our results are consistent with theoretical models of the genomic effects of population bottlenecks (Kirkpatrick and Jarne 2000; Miller and Hedrick 2001) that predict more substantial loss of genetic variability in small populations that may begin to recover very soon after a population bottleneck versus similarly small populations where recovery is delayed. Theoretically, low levels of genetic variation may substantially increase the probability that a species may go extinct—the "central dogma of conservation genetics" (Lehman 1998). Yet several species, particularly marine mammals, are now robust and evidently doing very well despite substantial population and genetic bottlenecks and environmental change (including anthropogenic change and resource extraction). Consequently our data, and those from other recent studies, suggest caution in labeling any species as having "high" or "low" levels of variation, as this may give a misleading snapshot of the genetic health of the species and be of limited relevance in assessing its likelihood of persistence. Indeed, the continued viability of the Guadalupe fur seal may depend primarily on nongenetic factors, such as poaching or the local availability of food resources during the breeding season and its consequent effects on pup growth and survival.
|
Footnotes |
|---|
Corresponding Editor: Stephen J. O'Brien
Received November 23, 2002
Accepted September 15, 2003
|
References |
|---|
|
TopAbstractMaterials and MethodsResults and DiscussionReferences |
|---|
-
Amos B, 1996. Levels of genetic variability in cetacean populations have probably changed little as a result of human activities. Rep Int Whal Comm. 46:657-658.
Austin JJ, Smith AB, Thomas RH, 1997. Paleontology in a molecular world: the search for authentic ancient DNA. Trends Ecol Evol. 12:303-306.[CrossRef]
Bartholomew GA, 1950. A male GFS on San Nicolas Island, California. J Mamm. 31:175-180.[CrossRef]
Bernardi G, Fain SR, Gallo-Reynoso JP, Figueroa-Carranza AL, Le Boeuf BJ, 1998. Genetic variability in Guadalupe fur seals. J Hered. 89:301-305.
Bouzat JL, Cheng HH, Lewin HA, Westemeier RL, Brawn JD, Paige KN, 1998. Genetic evaluation of a demographic bottleneck in the greater prairie chicken. Conserv Biol. 12:836-843.[CrossRef]
Caro TM, Laurenson MK, 1994. Ecological and genetic factors in conservation: a cautionary tale. Science. 263:485-486.
Cooper A, Wayne R, 1998. New uses for old DNA. Curr Opin Biotechnol. 9:49-53.[CrossRef][Web of Science][Medline]
Etnier MA, 2002. Occurrences of Guadalupe fur seals (Arctocephalus townsendi) on the Washington coast over the past 500 years. Mar Mamm Sci. 18:551-557.[CrossRef]
Fleischer LA, 1978. The distribution, abundance, and population characteristics of the Guadalupe fur seal, Arctocephalus townsendi (Merriam 1897) (Master's thesis). Seattle, WA: University of Washington.
Fu Y-X, 1997. Statistical tests of neutrality of mutations against population growth, hitchhiking, and background selection. Genetics. 147:915-925.[Abstract]
Gallo-Reynoso JP, 1994. Factors affecting the population status of Guadalupe fur seal, Arctocephalus townsendi (Merriam, 1897), at Isla de Guadalupe, Baja California, Mexico (PhD dissertation). Santa Cruz, CA: University at California, Santa Cruz.
Galtier N, Depaulis F, Barton NH, 2000. Detecting bottlenecks and selective sweeps from DNA sequence polymorphism. Genetics. 155:981-987.
Glenn TC, Stephan W, Braun MJ, 1999. Effects of a population bottleneck on whooping crane mitochondrial DNA variation. Conserv Biol. 13:1097-1107.[CrossRef]
Goldsworthy S, Francis J, Boness D, Fleischer R, 2000. Variation in the mitochondrial control region in the Juan Fernandez fur seal (Arctocephalus philippii). J Hered. 91:371-377.
Gustafson CE, 1968. Prehistoric use of fur seals: evidence from the Olympic coast of Washington. Science. 161:49-51.
Hagelberg E, 1994. Mitochondrial DNA from ancient bones. In: Ancient DNA: recovery and analysis of genetic material from paleontological, archaeological, museum, medical, and forensic specimens (Herrmann B and Hummel S, eds). New York: Springer-Verlag; 195–204.
Hagelberg E, Clegg JB, 1991. Isolation and characterisation of DNA from archaeological bone. Proc R Soc Lond B. 244:45-50.[Medline]
Harpending HC, 1994. Signature of ancient population growth in a low-resolution mitochondrial DNA mismatch distribution. Hum Biol. 66:591-600.[Web of Science][Medline]
Harpending HC, Sherry ST, Rogers AR, Stoneking M, 1993. The genetic structure of ancient human populations. Curr Anthropol. 34:483-496.[CrossRef][Web of Science]
Hartl DL, Clark AG, 1997. Principles of population genetics, 3rd ed. Sunderland, MA: Sinauer Associates.
Hedrick PW, 1996. Bottleneck(s) or metapopulation in cheetahs. Conserv Biol. 10:897-899.[CrossRef]
Hedrick PW, 2000. Genetics of populations, 2nd ed. Sudbury, Ontario: Jones and Bartlett.
Hubbs CL, 1956. Back from oblivion. Guadalupe fur seal: still a living species. Pacific Disc. 9:14-51.
Hummel S, Herrmann B, 1994. General aspects of sample preparation. In: Ancient DNA: recovery and analysis of genetic material from paleontological, archaeological, museum, medical, and forensic specimens (Herrmann B and Hummel S, eds). New York: Springer; 59–68.
Kirkpatrick M, Jarne P, 2000. The effects of a bottleneck on inbreeding depression and the genetic load. Am Nat. 155:154-167.[CrossRef][Medline]
Larson S, Jameson R, Etnier M, Fleming M, Bentzen P, 2002. Loss of genetic diversity in sea otters (Enhydra lutris) associated with the fur trade of the 18th and 19th centuries. Mol Ecol. 11:1899-1903.[CrossRef][Medline]
Lehman N, 1998. Genes are not enough. Curr Biol. 8:1078-1081.
Lyons GM, 1937. Pinnipeds and a sea otter from the Point Mugu shell mound of California. Publications of the University of California at Los Angeles in Biological Sciences. 1:133-168.
Maravilla-Chavez MO, MS Lowry, 1999. Incipient breeding colony of Guadalupe fur seals at Isla Benito del Este, Baja California, Mexico. Mar Mamm Sci. 15:239-241.[CrossRef]
Miller PS, Hedrick PW, 2001. Purging of inbreeding depression and fitness decline in bottlenecked populations of Drosophila melanogaster. J Evol Biol. 14:595-601.[CrossRef]
Nei M, 1987. Molecular evolutionary genetics. New York: Columbia University Press.
Nei M, Maruyama T, Chakraborty R, 1975. The bottleneck effect and genetic variability in populations. Evolution. 29:1-10.
Nicholas KB, Nicholas HB, Jr Deerfield DW, II 1997. GeneDoc: analysis and visualization of genetic variation. EMBNEW.NEWS. 4:14.
O'Brien SJ, 1994. The cheetah's conservation controversy. Conserv Biol. 8:1153-1155.[CrossRef]
O'Brien SJ, Wildt DE, Bush M, Caro TM, FitzGibbon C, Aggundey I, Leakey RE, 1987. East African cheetahs: evidence for two population bottlenecks? Proc Natl Acad Sci USA. 84:508-511.
Reeves RR, Stewart BS, 2003. Marine mammals of the world: an introduction. In: Walker's marine mammals of the world (Nowak RM, ed). Baltimore: Johns Hopkins University Press; 1–64.
Reeves RR, Stewart BS, Clapham P, Powell J, 2002. Guide to marine mammals of the world. New York: Knopf.
Reeves RR, Stewart BS, Leatherwood S, 1992. The Sierra Club handbook of seals and sirenians. San Francisco: Sierra Club Books.
Rogers AR, Fraley AE, Bamshad MJ, Watkins WS, Jorde LB, 1996. Mitochondrial mismatch analysis is insensitive to the mutational process. Mol Biol Evol. 13:895-902.[Abstract]
Rozas J, Rozas R, 1999. DnaSP version 3: an integrated program for molecular population genetics and molecular evolution analysis. Bioinformatics. 15:174-175.
Schneider S, Excoffier L, 1999. Estimation of past demographic parameters from the distribution of pairwise differences when the mutation rates vary among sites: application to human mitochondrial DNA. Genetics. 152:1079-1089.
Schneider S, Roessli D, Excoffier L, 2000. Arlequin ver. 2000: a software for population genetics data analysis. Geneva, Switzerland: University of Geneva.
Stemmer WPC, 1994. DNA shuffling by random fragmentation and reassembly: in vitro recombination for molecular evolution. Proc Natl Acad Sci USA. 91:10747-10751.
Stewart BS, 1997. California pinnipeds: population trends, trans-jurisdictional migrations, and ecological function in large marine ecosystems of the eastern north Pacific Ocean. In: Pinniped populations, eastern north Pacific: status, trends, and issues (Stone G, Goebel J, and Webster S, eds). Monterey: American Fisheries Society; 13–21.
Stewart, BS, Yochem PK, DeLong RL, Antonelis GA, 1993. Trends in abundance and status of pinnipeds on the southern California Channel Islands. In: Third California Channel Islands symposium: recent advances in research on the California islands, Santa Barbara, CA, 2–6 March 1987 (Hochberg FG, ed). Santa Barbara, CA: Santa Barbara Museum of Natural History; 501–516.
Swofford DL, 2002. PAUP*: phylogenetic analysis using parsimony (*and other methods), version 4. Sunderland, MA: Sinauer Associates.
Tajima F, 1993. Measurement of DNA polymorphism. In: Mechanisms of molecular evolution: introduction to molecular paleopopulation biology (Takahata N and Clark AG, eds). Sunderland, MA: Sinauer Associates; 37–59.
Thompson JD, Gibson TJ, Plewniak F, Jeanmougin F, Higgins DG, 1997. The ClustalX windows interface: flexible strategies for multiple sequence alignment aided by quality analysis tools. Nucleic Acids Res. 24:4876-4882.
Tindall KR, Kunkel TA, 1988. Fidelity of DNA synthesis by the Thermus aquaticus DNA polymerase. Biochemistry. 27:6008-6013.[CrossRef][Medline]
Townsend CH, 1916. The Guadalupe fur seal. A contribution to its history. Bull N Y Zool Soc. 19:1330-1331.
Townsend CH, 1928. Reappearance of the lower California fur seal. Bull N Y Zool Soc. 31:173-174.
Townsend CH, 1931. The fur seal of the California islands with new descriptive and historical matter. Zoologica. 9:442-457.
Weber DS, Stewart BS, Garza JC, Lehman N, 2000. An empirical genetic assessment of the severity of the northern elephant seal population bottleneck. Curr Biol. 10:1287-1290.[CrossRef][Web of Science][Medline]
Westemeier RL, Brawn JD, Simpson SA, Esker TL, Jansen RW, Walk JW, Kershner EL, Bouzat JL, Paige KN, 1998. Tracking the long-term decline and recovery of an isolated population. Science. 282:1695-1698.
Wynen LP, Goldsworthy SD, Guinet C, Bester MN, Boyd IL, Gjertz I, Hofmeyr GJG, White RWG, Slade R, 2000. Postsealing genetic variation and population structure of two species of fur seal (Arctocephalus gazella and A. tropicalis). Mol Ecol. 9:299-314.[CrossRef][Medline]
Wynen LP, Goldsworthy SD, Insley SJ, Adams M, Bickham JW, Francis J, Gallo JP, Hoelzel AR, Majluf P, White RWG, Slade R, 2001. Phylogenetic relationships within the eared seals: implications for the historical biogeography of the family. Mol Phylogenet Evol. 21:270-284.[CrossRef][Web of Science][Medline]
Yang DY, Eng B, Waye JS, Dudar JC, Saunders SR, 1998. Improved DNA extractions from ancient bones using silica-based spin columns. Am J Phys Anthropol. 105:539-543.[CrossRef][Web of Science][Medline]
CiteULike 
Connotea 
Del.icio.us What's this?
This article has been cited by other articles:
|
|
 |
|
  S. D. Newsome, M. A. Etnier, D. Gifford-Gonzalez, D. L. Phillips, M. van Tuinen, E. A. Hadly, D. P. Costa, D. J. Kennett, T. P. Guilderson, and P. L. Koch The shifting baseline of northern fur seal ecology in the northeast Pacific Ocean PNAS, June 5, 2007; 104(23): 9709 - 9714. [Abstract] [Full Text] [PDF]
|
|
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||