- Research article
- Open Access
Tracing early stages of species differentiation: Ecological, morphological and genetic divergence of Galápagos sea lion populations
© Wolf et al; licensee BioMed Central Ltd. 2008
- Received: 22 November 2007
- Accepted: 16 May 2008
- Published: 16 May 2008
Oceans are high gene flow environments that are traditionally believed to hamper the build-up of genetic divergence. Despite this, divergence appears to occur occasionally at surprisingly small scales. The Galápagos archipelago provides an ideal opportunity to examine the evolutionary processes of local divergence in an isolated marine environment. Galápagos sea lions (Zalophus wollebaeki) are top predators in this unique setting and have an essentially unlimited dispersal capacity across the entire species range. In theory, this should oppose any genetic differentiation.
We find significant ecological, morphological and genetic divergence between the western colonies and colonies from the central region of the archipelago that are exposed to different ecological conditions. Stable isotope analyses indicate that western animals use different food sources than those from the central area. This is likely due to niche partitioning with the second Galápagos eared seal species, the Galápagos fur seal (Arctocephalus galapagoensis) that exclusively dwells in the west. Stable isotope patterns correlate with significant differences in foraging-related skull morphology. Analyses of mitochondrial sequences as well as microsatellites reveal signs of initial genetic differentiation.
Our results suggest a key role of intra- as well as inter-specific niche segregation in the evolution of genetic structure among populations of a highly mobile species under conditions of free movement. Given the monophyletic arrival of the sea lions on the archipelago, our study challenges the view that geographical barriers are strictly needed for the build-up of genetic divergence. The study further raises the interesting prospect that in social, colonially breeding mammals additional forces, such as social structure or feeding traditions, might bear on the genetic partitioning of populations.
- Discriminant Function Analysis
- Partial Mantel Test
- Step Stone Model
- Quadratic Discriminant Function
- Genetic Distance Measure
The relative role of ecologically mediated divergence in speciation processes is still under debate . Theory predicts that barriers to gene flow can evolve as a result of ecologically-based divergent selection and need not necessarily be associated with separation imposed by geographic barriers [2–5]. Recent empirical evidence makes it increasingly clear that ecological factors can indeed drive speciation processes [6–9]. Traditionally, top-down phylogenetic analyses, where the relevant divergence processes are inferred retrospectively long after the putative split has occurred have often been invoked to address this question. While this is clearly a powerful approach to reveal evolutionary trajectories, it is by its very nature restricted to retrospective inferences and can thereby only speculate about the ecological conditions under which the speciation process was initiated. It is hence necessary to identify cases where the first steps of divergence appear, even if one can not definitely know whether it will eventually end with a true species separation [10–13]. Studying ongoing differentiation processes in small-scale situations with unlimited dispersal opportunities is therefore crucial to investigate the mechanisms driving adaptive divergence.
Marine environments provide excellent study cases, as they typically allow broad dispersal in mobile taxa and, compared to terrestrial habitats, offer low travel costs . Still, within geographic ranges of several thousand kilometres genetic isolation by distance is expected and has been observed even for highly mobile marine predators . However, it is a challenge to track evolutionary divergence processes at a smaller spatial scale. The few that have ventured on this undertaking have produced interesting results ranging from a role of gamete recognition molecules  to a role of socially mediated information . We here present a system that allows examination of micro-evolutionary processes in an isolated, small-scale marine environment for a highly mobile top predator.
Sampling locations and sample sizes
Island (code on map)
Number of samples
Differentiation scenario: geological/ecological
≥ 625 bp mtDNA
Amplifying ≥ 21 microsatellite loci
Stable isotope analysis
(Galápagos sea lion)
Santa Fé (SF)
Española * (ECEG)
San Cristobal* (ILZN)
(Galápagos fur seal)
Isabela Banks Bay (Ag_IB)
Isabela Marshal Bay (Ag_IM)
(Californian sea lion)
Año Nuevo Island
Moss Landing Beach
Summary statistics of discriminant function analysis
a priori classification
Classification success [%]
A) Stable isotopes
We further tested for homogeneity of variance in the isotopic signal that can be indicative of niche width differences . For two pairs of directly adjacent populations of sea lions and fur seals (IBES/Ag_IB and FH/Ag_FH, see Fig. 1) variances in δ13C values are larger in sea lions (IBES/Ag_IB: F23,29 = 34.90, p < 0.001, FH/AgFH: F21,29 = 9.92, p < 0.001), while differences in δ15N values are statistically non-significant after correcting for multiple testing (IBES/Ag_IB: F23,29 = 2.30, p = 0.04; FH/AgFH: F21,29 = 2.57, p = 0.02).
Analysis of genetic differentiation at the level of microsatellites and the individual colonies using Goodman's standardized Rst as the pair-wise distance suggests the same habitat-related pattern (Fig. 4B). This split is corroborated by global estimates of traditional fixation indices (Rst = 0.020; Gst' = 0.012, θ = 0.012: bootstrapped CI99% = 0.005–0.021; G-statistic: p < 0.001).
Isolation by distance
Another noteworthy difference between the isolation by distance pattern of mtDNA and nDNA relates to the variance of the genetic distance measure. For comparable geographic distances the variance in Fst between populations within habitats (dotted brace in Fig. 6) and between habitats (solid brace in Fig. 6) is of similar size for nDNA (F19,45 = 1.14). For mtDNA the variance of Φst for inter-habitat comparisons is four times as large as the variance of intra-habitat comparisons (F19,45 = 4.12).
Using ecological, morphological and molecular indicators, we find a clear structure between western and central Galápagos sea lion colonies, even though these are extremely mobile predators and breeding dispersal is potentially unrestricted across the entire species range. The mobility potential is well exemplified by the Californian sister species of the Galápagos sea lion  that can easily travel several hundred kilometres during foraging routines . Similarly, for the Galápagos sea lion satellite telemetry data show that the scale of ecological and genetic divergence lies well within the geographic range of daily foraging trips . In other marine mammals of similar mobility  including species of seals  a comparable degree of genetic differentiation is usually found only at geographic scales that are about 10-fold larger. This is not surprising, as high mobility usually translates into strong gene flow. In elephant seals for example, a single male can successfully father 19 offspring 8000 km from its natal rookery . This calls for an explanation beyond mere distance effects in the Galápagos sea lion, where homogenizing effects of even rare dispersal events would equally be expected as in other polygynous animals. In the following, we discuss the possible factors that might play a role in this differentiation.
A role of ecology
Using the results of stable isotope analysis as a proxy for maternal trophic ecology we find that individuals of the Galápagos sea lion cluster according to their natal habitat. Colonies in the central habitat are characterized by pelagic shelf feeding, a foraging strategy that is also typical for the closely-related Californian sister species. Conversely, colonies found adjacent to the deep, nutrient rich habitat in the west show an atypical benthic signature. This difference in isotopic signatures between western and central populations could simply reflect differences in food-web-wide basal isotopes. It is however intriguing that the fur seal, which overlaps with the sea lion in this habitat, shows the typical pelagic δ13C values of eastern sea lions. This counters the idea that differences in basal isotopes of the foraging location alone account for the observed difference in the sea lions. It is rather indicative of resource partitioning, potentially via character displacement in this area where competition for a joint resource leads to specialization of at least one of the competing species. Grant and Grant  have shown in two species of Galápagos finch that such character displacement can occur rapidly. As stable isotope values integrate maternal foraging strategies over several months (see Methods), the measured effect could develop within even a single generation. On the other hand, the changes in skull features are likely to require longer periods of directional selection, suggesting that the differences in foraging strategies are established and stable in the respective populations.
It is clear that the data presented here can only be a first hint towards such character displacement and need to be substantiated by several independent lines of evidence that go beyond the scope of this study . Nonetheless, other sources of information on Galápagos fur seals and sea lions indirectly corroborate the interpretation of our data as being indicative of niche segregation. Fur seals forage at night, western sea lions exclusively during the day , whereas central sea lions show no apparent temporal pattern [unpublished data from long-term study on a central rookery ]. Scat analyses revealed that, in contrast with central sea lions that are using a broad prey spectrum , trophic niches of fur seals and western sea lions are highly specialised and show little overlap . Furthermore, sea lions from the different habitats seem to diverge in diving behaviour [28, 37]; hence, dissimilar ecological conditions within the archipelago and the competition with fur seals in one habitat appear to evoke habitat specialisation in the sea lion.
A role of natal habitat preference induction and social behaviour
To develop levels of genetic differentiation that reflect the ecological differentiation between different populations of Galápagos sea lions, some form of pre-zygotic isolation is required. Habitat choice would be one such mechanism and could constitute a non-genetic means of assortment. There is convincing theoretical and empirical evidence that habitat preferences can be based solely on learning [4, 38]. For instance, early learning can lead to a lifetime shift in feeding niche, even across species . Natal habitat preference induction is particularly likely to evolve in species with long lasting social bonds between adults and young. The discussion regarding the role of socially mediated feeding styles of killer whales as the primary source of genetic differentiation is a prominent example . Likewise, genetic divergence between transient and resident wolf populations links to different foraging strategies and suggests a similar explanation .
Galápagos sea lions are highly social animals, whose offspring are dependent on their mother for one to three years . They are likely to have the same long-term memory  and high cognitive abilities as their Californian sister species . The idea of socially mediated habitat learning thus seems not far fetched and is partly supported by telemetry data on female Galápagos sea lions. None of the surveyed females ever crossed the habitat border in any of the recorded foraging trips, although it lay well within their mobility capacity . In addition to the "ecological" habitat the social environment may contribute to reducing gene flow. In contrast to other species that only join for reproduction, Galápagos sea lions maintain haul-out sites year round. In such a situation, reproductive success is likely to be affected by long-term interactions with others  and predictability of the social environment is of prime importance [44–46]. Thus, learned habitat preference induction – be it ecological or social – may well contribute to pre-zygotic isolation.
The observed isolation by distance pattern strengthens this idea. The mitochondrial marker reflecting matrilineal inheritance shows no relationship between genetic and geographic distance after habitat identity is removed as a factor. Thus, within one habitat, gene flow seems relatively unrestricted and genetic variants can spread across the entire central region. This homogenizing effect of gene flow that is witnessed by the absence of isolation by distance and the low variance of intra-habitat comparisons suggests that site fidelity alone  is not strong enough in this species to create significant population structure as reported in other otariid seals . Hence, environmental differences seem to be key to the understanding of genetic divergence. This is corroborated by the fact that the variance of genetic distance between rookeries of different habitats is much larger than among rookeries of the same habitat indicating that drift across habitats is strong relative to gene flow.
For microsatellites the isolation by distance pattern is in line with a stepping stone model of a regional equilibrium with gene flow and drift [compare ]. This clear difference from the mitochondrial pattern is not easy to explain and may partly be due to the fact that differentiation of the two markers differs by an order of magnitude. It may further be due to the four times smaller effective population size of the mitochondrial marker or differences in mutational dynamics between the two marker systems. The most compelling explanation might lie in the large difference in information content of the two markers. While mitochondrial results are based on a short stretch of sequence data in one locus, the results of nuclear DNA stem from 22 independent highly variable microsatellite loci. The information for the mtDNA may thus simply not suffice to pick up the isolation by distance pattern between populations sharing the same habitat.
Another factor bearing on the isolation by distance patterns could also be sex specific migration behaviour. The nuclear pattern suggests that males are more likely to cross occasionally the habitat boundaries, but would on the other hand show high site fidelity even within the respective habitats, together with the females. While female site fidelity is characteristic for most mammalian species , short range dispersal in males is less common. Why then would males restrict their dispersal to an area that is even smaller than their daily putative foraging range? In contrast to other species that only join for reproduction, the sea lion adult males are known to reside for years [Pörschmann et al. in prep, ]. In such a situation reproductive success is likely to be affected by long-term interactions with others  and predictability of the social environment is of prime importance [44, 45]. For males, in particular, long-term social dominance hierarchies, social queuing and 'dear enemy relationships' are essential for territorial success [50–52]. The fact that males of the Antarctic fur seal (Arctocephalus gazella) return to locations at a scale less their own body length year after year  and males that are able to establish territories several years in a row increase reproductive success  can be interpreted along these lines.
A role of selection against immigrants
Apart from natal-induced habitat preference, an alternative mechanism that may contribute to pre-zygotic isolation was described by Hendry . In a modelling approach he proposed that selection against migrants themselves can contribute substantially to ecologically dependent reproductive isolation. Nosil et al.  even suggested that this mechanism plays a critical role in ecological modes of speciation. Given the difference in ecology and the apparent behavioural and morphological adaptations in the West, we might expect that immigrant sea lions from the central area would have problems to compete successfully with resident animals. Thus, once ecological differentiation has been initiated, this factor would stabilize any genetic divergence.
A role of geography and geology
The geology of the Galápagos can be described as a combination of concentrated volcanic activity at the archipelago's western rim (hotspot) and lithospheric motion that carries the emerging volcanoes off in a north-eastern direction. This results in a shallow submarine platform with steep abysses at its western and southern side that gently slopes to the north-east where it joins the intersection of two major tectonic plates . These geological processes lead to an almost linear island age structure across the archipelago: easternmost islands are oldest (San Cristobal, Española ~3 mya), westernmost islands are youngest (Fernandina: ca. 0.08 mya ). Assuming comparable oceanographic conditions to those of today, we would expect similar habitat differences across the archipelago over geological times. Without any geographic barriers, the cold upwelling western waters would mix with warmer waters in the east, and ecological differences would most likely resemble an environmental gradient. It has been shown that such environmental gradients can trigger genetic divergence into two discrete states in models of sympatric divergence . The emergence of Isabela in the west would have further accentuated this. The large northern and southern volcanoes of Isabela emerged about 0.2–0.4 mya ago  and probably joined only within the past few thousand years (D. Geist personal communication).
Our data show evidence for intra-specific divergence of the Galápagos sea lion at ecological, morphological and genetic levels, which may potentially lead to the emergence of a new species over time. Our analysis shows that a multitude of factors may play a role in ecological divergence, including some behavioural conditions that are specific to the system. In particular, the data constitute an example where substantial effects of a competitor species on intra-specific evolutionary processes appears likely [31, 32]. Geographic isolation, on the other hand, seems to play only a small role. Thus, our results are in line with an increasing number of studies that suggest that the current dominance of allopatric and parapatric speciation concepts in evolutionary theory may be in part an artefact of studying speciation patterns at levels where the processes have long been completed. The study highlights that divergence processes are likely to be based on a variety of factors, and that little will be gained by exclusively adhering to a controversial debate about geographic speciation scenarios .
Tissue sample collection and DNA extraction
A total of 376 tissue samples were collected from the inter-digital membrane of the hind flippers from newborn individuals of the Galápagos sea lion and the Galápagos fur seal at their natal colonies. Sampling locations were spread uniformly across the Galápagos archipelago excepting the northernmost islands of Darwin and Wolf (Fig. 1, Table 1). Adjacent colonies with low individual sample sizes were pooled, their geographic position averaged and subsequently treated as one entity (indicated by four letter codes in Fig. 1). Samples of the Californian sea lion were supplied from locations central to the taxon's range containing adults (n = 5) as well as sub-adults (n = 11) (Table 1).
Stable isotope analysis
Skin samples for stable isotope analysis were taken from a total of 140 the Galápagos sea lion pups and from 90 Galápagos fur seal pups (Table 1) that were about three months old. This is an age where pups are nutritionally fully dependent of their mothers . The stable isotope signature therefore exclusively represents maternal foraging strategies. Skin samples were oven dried at 65°C for 24 h. Samples were pulverised, weighed (ca. 0.55 mg) and loaded into tin cups prior to analysis of carbon (δ13C) and nitrogen (δ15N) stable isotope ratios [for analytical details see ]. Analytical precision was < 0.1‰ (δ13C) and < 0.3‰ (δ15N).
In order to examine whether isotopic and elemental variation in skin samples represented a viable means to differentiate the different genetic stocks and species, we ran a discriminant function analysis using δ13C, δ15N and C:N values as predictors of stock/species following Harrod et al. . We used a quadratic discriminant function as our sample size differed between groups and because of heterogeneity of variance in some variables.
A total of 43 skulls of the Galápagos sea lion held at several natural history museums and institutions (see Additional file 3) were measured for the following 13 variables using Mitotoyo digital calipers (accuracy ± 0.01 mm): condylobasal length, breadth of preorbital processes, interorbital constriction, palatal notch – incisors, length of upper postcanine row, rostral width, gnathion – posterior of maxilla (palatal), breadth of zygomatic root of maxilla, zygomatic breadth, basion – zygomatic root (anterior), auditory breadth, gnathion – posterior border of preorbital process, palatal breadth at postcanine five. All skulls were used for univariate statistics; thirty-six of these (those with no missing variables) were used for discriminant analyses. Only fully grown adult specimens with suture indices of > 23 for males and > 18 for females were included in the analyses . Raw data were initially standardized to z-scores so that each variable had equal weighting. Specimens were grouped according to the habitat where they were collected. Note that this leads to a conservative classification estimate, since skull samples may include occasional visitors that originate from other habitats. Discriminant function analysis using SYSTAT 11 was applied to examine relationships between individuals from the different habitats. Multivariate ANOVA (MANOVA) was followed by either two-group or multi-group discriminant function analysis. The MANOVA was applied initially to test whether group centroids for specimens were significantly different. Mahalanobis distances of individuals from the mean centroid were plotted for each habitat, against discriminant axes I and II. When sexes were analyzed separately, both males and females showed similar Mahalanobis distances. Due to low numbers of individuals from the western habitat (males = 5, females = 4) sexes were pooled to provide greater resolution of results.
Mitochondrial DNA: laboratory procedures and data analysis
After extraction of genomic DNA, the mitochondrial control region was amplified by use of PCR with taxon-specific modifications of highly conserved primers located in the tRNAthr/pro and the tRNAphe region, purified by ultrafiltration and sequenced on an ABI 3730 sequencer . Quality ascertainment and sequence alignment were conducted in SEQMAN™ version 6.1. (DNAStar Inc.). Individuals with less than 625 bp of reliably identified sequence were excluded from the analysis leaving a total of 336 individuals. From these, 29 haplotypes can be distinguished. If alignment gaps are included as a fifth character the number of haplotypes rises to 36. Sequences for all individuals and the haplotype alignment are deposited as alignment ALIGN_001234 in the EMBL-Align database that can be accessed by the EBI sequence retrieval system .
Φst was inferred by AMOVA as implemented in ARLEQUIN 3.10.  and used as an estimator of hierarchical population differentiation of the mitochondrial genome. We compared three scenarios (see Table 1): comparisons among colonies a) without any further hierarchical level, b) grouping colonies by island geology following Rassmann et al.  c) grouping colonies by habitat type. Genetic distances were based on the K80 nucleotide substitution model, which is closest to the substitution model suggested by Wolf et al. . Qualitatively, results were unaffected by whether alignment gaps were or were not included in the analysis.
Nuclear DNA: microsatellite genotyping and data analyses
Genomic DNA was genotyped for a total of 367 Galápagos sea lion and 16 Californian sea lions at 22 microsatellite loci [for further details see [18, 66, 67]]. Population structure was inferred using the program STRUCTURE  including the Californian sea lion in the analysis, as otherwise the MCMC would not converge. Evanno et al.  proposed an ad hoc statistic, Δk, to detect the number of clusters that best fit the dataset. We did not adhere to this procedure for two reasons: firstly, it is not suited to resolve less than three clusters and secondly, it may lead to unreliable results, as the calculation of Δk includes several chains that may have not converged. We therefore followed the original method by Pritchard , namely to run several chains (10) and for each value of k select the MCMC run with the smallest value of -log(Pr(x|k)). Conventional Fst  and Rst estimates  were used to estimate the degree of genetic differentiation between the inferred populations using FSTAT 188.8.131.52. . The G statistic proposed by Goudet et al.  was taken for statistical inference on global population differentiation. Bootstrapped pair-wise Rst(Goodman) distances were obtained from the software MICROSAT 1.5d  and used for cluster-based tree reconstruction in the PHYLIP module Neighbor .
Isolation by distance analysis
Stepping stone models on a two-dimensional space predict a linear relationship between Fst/(1-Fst) and the logarithm of geographic distance . Because pairwise elements of distance matrices are not independent, a Mantel test with 104 permutations was used to test for the statistical significance of this relationship ['ecodist package' in R ]. In migration – drift equilibrium the variance of the genetic distance measure is further expected to increase with geographic distance . We therefore assessed if the degree of scatter in the genetic distance measure increased with geographic distance. This was done by first obtaining the residuals from a standard linear regression of genetic distance (Fst/(1-Fst)) on the logarithm of geographic distance. These residuals and the log geographic distance matrix were then subjected to a partial Mantel test to test for statistical significance. As population structure can artificially produce statistically significant isolation by distance relationships, we also conducted partial Mantel tests correcting for the influence of habitat.
We gratefully acknowledge assistance in the field provided by Corinne Zurbrügg, Karina Acevedo-Whitehouse, Marilyn Cruz and Sandie Salazar. Samples of the Californian sea lion were kindly provided by Terry Williams. We thank David Aurioles-Gamboa, who contributed samples for the easternmost range of the Galápagos sea lion. Thanks to Elke Hippauf, Heinke Buhtz, Anita Möller and Elke Blohm-Sievers for help in the laboratory. Thanks to the following for allowing access to skull specimens: Jacques Cuisin and Erwan Vappreau (MNHN), Fiona Brady (AMNH), James Mead, Linda Gordon and Criis Geer (NMNH), Philip Unitt (SDNHM), Michi Solomon (FMNH) and Rainer Hutterer (ZFMK). We would also like to thank the Max-Planck Society via the Institute for Ornithology, Seewiesen, for use of their research table. Funding was provided by the National Geographic Society (grant: 7671-04), the German Research Foundation (WO 1426/1-1), VolkswagenStiftung (grant 78620) and the Max Planck Society. The study complied with the laws of Ecuador, and was carried out under permit and with support of the Servicio Parque Nacional Galápagos and the Charles Darwin Research Station, which also provided the basic GIS map. The highly constructive criticism of four anonymous referees significantly improved the manuscript.
- Mallet J: Speciation in the 21st century. Book review of "Speciation" by Jerry A. Coyne & H. Allen Orr. Heredity. 2005, 95: 105-109. 10.1038/sj.hdy.6800686.View ArticleGoogle Scholar
- Dieckmann U, Doebeli M: On the origin of species by sympatric speciation. Nature. 1999, 400 (6742): 354-357. 10.1038/22521.View ArticlePubMedGoogle Scholar
- Bürger R, Schneider KA, Willensdorfer M: The conditions for speciation through intraspecific competition. Evolution. 2006, 60: 2185-2206.View ArticlePubMedGoogle Scholar
- Beltman JB, Haccou P: Speciation through the learning of habitat features. Theor Popul Biol. 2005, 67 (3): 189-202. 10.1016/j.tpb.2005.01.001.View ArticlePubMedGoogle Scholar
- Doebeli M, Dieckmann U: Speciation along environmental gradients. Nature. 2003, 421: 259-264. 10.1038/nature01274.View ArticlePubMedGoogle Scholar
- Funk DJ, Nosil P, Etges WJ: Ecological divergence exhibits consistently positive associations with reproductive isolation across disparate taxa. Proc Natl Acad Sci USA. 2006, 103 (9): 3209-3213. 10.1073/pnas.0508653103.PubMed CentralView ArticlePubMedGoogle Scholar
- Dieckmann U, Doebeli M, Metz JAJ, Tautz D: Adaptive Speciation. 2004, Cambridge, UK: Cambridge University PressView ArticleGoogle Scholar
- Rundle HD, Nosil P: Ecological speciation. Ecol Lett. 2005, 8 (3): 336-352. 10.1111/j.1461-0248.2004.00715.x.View ArticleGoogle Scholar
- Schluter D: The Ecology of Adaptive Radiation. 2000, Oxford, U.K.: Oxford Universtiy PressGoogle Scholar
- Steinfartz S, Weitere M, Tautz D: Tracing the first steps to speciation: ecological and genetic differentiation of a salamader population in a small forest. Mol Ecol. 2007, 16 (21): 4550-4561. 10.1111/j.1365-294X.2007.03490.x.View ArticlePubMedGoogle Scholar
- Tautz D: Phylogeography and Patterns of Incipient Speciation. Adaptive Speciation. Edited by: Dieckmann U, Doebeli M, Metz JAJ, Tautz D. 2004, Cambridge: Cambridge University Press, 305-320.Google Scholar
- Bekkevold D, Andre C, Dahlgren TG, Clausen LAW, Torstensen E, Mosegaard H, Carvalho GR, Christensen TB, Norlinder E, Ruzzante DE: Environmental correlates of population differentiation in Atlantic herring. Evolution. 2005, 59 (12): 2656-2668.View ArticlePubMedGoogle Scholar
- Hendry AP, Wenburg JK, Bentzen P, Volk EC, Quinn TP: Rapid evolution of reproductive isolation in the wild: evidence from introduced salmon. Science. 2000, 290: 516-519. 10.1126/science.290.5491.516.View ArticlePubMedGoogle Scholar
- Tucker VA: The energetic cost of moving about. Am Scientist. 1975, 63: 413-419.PubMedGoogle Scholar
- Fontaine MC, Baird SJE, Piry S, Ray N, Tolley KA, Duke S, Birkun A, Ferreira M, Jauniaux T, Llavona A, et al: Rise of oceanographic barriers in continuous populations of a cetacean: the genetic structure of harbour porpoises in Old World waters. BMC Biology. 2007, 5:Google Scholar
- Geyer LB, Palumbi SR: Reproductive character displacement and the genetics of gamete recognition in tropical sea urchins. Evolution. 2003, 57 (5): 1049-1060.View ArticlePubMedGoogle Scholar
- Hoelzel AR, Hey J, Dahlheim ME, Nicholson C, Burkanov V, Black N: Evolution of population structure in a highly social top predator, the killer whale. Mol Biol Evol. 2007, 24 (6): 1407-1415. 10.1093/molbev/msm063.View ArticlePubMedGoogle Scholar
- Wolf JB, Tautz D, Trillmich F: Galápagos and Californian sea lions are separate species: genetic analysis of the genus Zalophus and its implications for conservation management. Front Zool. 2007, 4 (1): 20-10.1186/1742-9994-4-20.PubMed CentralView ArticlePubMedGoogle Scholar
- Banks S: Ambiente físico. Reserva Marina de Galápagos. Edited by: Danulat E, Edgar GJ. 2002, Puerto Ayora, Santa Cruz, Galápagos: Fundación Charles Darwin/Servicio Parque Nacional Galápagos, 22-35.Google Scholar
- Sakamoto CM, Millero FJ, Yao WS, Friederich GE, Chavez FP: Surface seawater distributions of inorganic carbon and nutrients around the Galápagos Islands: results from the PlumEx experiment using automated chemical mapping. Deep-Sea Res II. 1998, 45 (6): 1055-1071. 10.1016/S0967-0645(98)00013-7.View ArticleGoogle Scholar
- Vargas H, Logheed C, Snell H: Population size and trends of the Galápagos Penguin Spheniscus mendiculus. Ibis. 2005, 147: 367-374. 10.1111/j.1474-919x.2005.00412.x.View ArticleGoogle Scholar
- Danulat E, Edgar GJ: Reserva Marina de Galápagos. Puerto Ayora, Santa Cruz, Galápagos: Fundación Charles Darwin/Servicio Parque Nacional Galápagos;. 2002Google Scholar
- France RL: Carbon-13 enrichment in benthic compared to planktonic algae: foodweb implications. Mar Ecol – Prog Ser. 1995, 124: 307-312. 10.3354/meps124307.View ArticleGoogle Scholar
- Hückstädt LA, Rojas CP, Antezana T: Stable isotope analysis reveals pelagic foraging by the Southern sea lion in central Chile. J Exp Mar Biol Ecol. 2007.Google Scholar
- Bearhop S, Adams CE, Waldron S, Fuller RA, Macleod H: Determining trophic niche width: a novel approach using stable isotope analysis. J Anim Ecol. 2004, 73 (5): 1007-1012. 10.1111/j.0021-8790.2004.00861.x.View ArticleGoogle Scholar
- Hutchison DW, Templeton AR: Correlation of pairwise genetic and geographic distance measures: Inferring the relative influences of gene flow and drift on the distribution of genetic variability. Evolution. 1999, 53 (6): 1898-1914. 10.2307/2640449.View ArticleGoogle Scholar
- Weise MJ, Costa DP, Kudela RM: Movement and diving behavior of male California sea lion (Zalophus californianus) during anomalous oceanographic conditions of 2005 compared to those of 2004. Geophys Res Lett. 2006, 33 (22):Google Scholar
- Villegas-Amtmann S, Costa DP, Tremblay Y, Aurioles-Gamboa D, Salazar S: Multiple foraging strategies in a marine apex predator, the Galápagos Sea Lion. Mar Ecol – Prog Ser.Google Scholar
- Hoffman JI, Matson CW, Amos W, Loughlin TR, Bickham JW: Deep genetic subdivision within a continuously distributed and highly vagile marine mammal, the Steller's sea lion (Eumetopias jubatus). Mol Ecol. 2006, 15 (10): 2821-2832.View ArticlePubMedGoogle Scholar
- Fabiani A, Hoelzel AR, Galimberti F, Muelbert MMC: Long-range paternal gene flow in southern elephant seals. Science. 2003, 299: 676-10.1126/science.299.5607.676.View ArticlePubMedGoogle Scholar
- Grant PR, Grant BR: Evolution of Character Displacement in Darwin's Finches. Science. 2006, 313: 224-226. 10.1126/science.1128374.View ArticlePubMedGoogle Scholar
- Schluter D, McPhail JD: Ecological character displacement and speciation in sticklebacks. Am Nat. 1992, 140 (1): 85-108. 10.1086/285404.View ArticlePubMedGoogle Scholar
- Trillmich F, Ono KA: Ecological Studies – Pinnipeds and El Niño. 1991, Berlin: Springer Verlag, 88:View ArticleGoogle Scholar
- Wolf JBW, Kauermann G, Trillmich F: Males in the shade: habitat use and sexual segregation in the Galápagos sea lion (Zalophus californianus wollebaeki). Behav Ecol Sociobiol. 2005, 59 (2): 293-302. 10.1007/s00265-005-0042-7.View ArticleGoogle Scholar
- Salazar SK: Dieta, tamaño poblacional e interacción con desechos costeros del lobo marino Zalophus californianus wollebaeki en las islas Galápagos. Disertación previa al título de Licenciatura en Ciencias Biológicas. Pontificia Universidad Católica del Ecuador. 1999Google Scholar
- Dellinger T, Trillmich F: Fish prey of the sympatric Galápagos fur seal and sea lions: seasonal variation and niche seperation. Can J Zool. 1999, 77: 1204-1216. 10.1139/cjz-77-8-1204.View ArticleGoogle Scholar
- Kooyman GL, Trillmich F: Diving Behavior of Galápagos Sea Lions. Fur seals – Maternal Strategies on Land and at Sea. Edited by: Gentry RL, Kooyman GL. 1986, Princeton, New Jersey: Princeton University Press, 209-219.Google Scholar
- Stamps JA, Davis JM: Adaptive effects of natal experience on habitat selection by dispersers. Anim Behav. 2006, 72: 1279-1289. 10.1016/j.anbehav.2006.03.010.View ArticleGoogle Scholar
- Slagsvold T, Wiebe KL: Learning the ecological niche. Proc R Soc B. 2007, 274 (1606): 19-23. 10.1098/rspb.2006.3663.PubMed CentralView ArticlePubMedGoogle Scholar
- Musiani M, Leonard JA, Cluff HD, Gates CC, Mariani S, Paquet PC, Vilà C, Wayne RK: Differentiation of tundra/taiga and boreal coniferous forest wolves: genetics, coat colour and association with migratory caribou. Mol Ecol. 2007, 16: 4149-4170. 10.1111/j.1365-294X.2007.03458.x.View ArticlePubMedGoogle Scholar
- Trillmich F, Wolf JBW: Parent-offspring and sibling conflict in Galápagos fur seals and sea lions. Behav Ecol Sociobiol. 2008, 62 (3): 363-375. 10.1007/s00265-007-0423-1.View ArticleGoogle Scholar
- Kastak CR, Schusterman RJ: Long-term memory for concepts in a California sea lion (Zalophus californianus). Anim Cogn. 2002, 5 (4): 225-232. 10.1007/s10071-002-0153-8.View ArticleGoogle Scholar
- Schusterman RJ, Reichmuth CJ, Kastak D: How animals classify friends and foes. Curr Dir Psychol Sci. 2000, 9 (1): 1-6. 10.1111/1467-8721.00047.View ArticleGoogle Scholar
- Wolf JBW, Trillmich F: Beyond habitat requirements: individual fine-scale site fidelity in a colony of the Galapagos sea lion (Zalophus wollebaeki) creates conditions for social structuring. Oecologia. 2007, 152: 553-567. 10.1007/s00442-007-0665-7.View ArticlePubMedGoogle Scholar
- Wolf JBW, Mawdsley D, Trillmich F, James R: Social structure in a colonial mammal: Unravelling hidden structural layers and their foundations by network analysis. Anim Behav. 2007, 74 (5): 1293-1302. 10.1016/j.anbehav.2007.02.024.View ArticleGoogle Scholar
- Wolf JBW, Trillmich F: Kin in space. Social viscosity in a spatially and genetically sub-structured network. Proc R Soc Lond B. 2008, 10.1098/rspb.2008.0356.Google Scholar
- Campbell RA, Gales NJ, Lento GM, Baker CS: Islands in the sea: extreme female natal site fidelity in the Australian sea lion, Neophoca cinerea. Biol Lett. 2008, 4: 139-142. 10.1098/rsbl.2007.0487.PubMed CentralView ArticlePubMedGoogle Scholar
- Greenwood PJ: Mating systems, philopatry and dispersal in birds and mammals. Anim Behav. 1980, 28: 1140-1162. 10.1016/S0003-3472(80)80103-5.View ArticleGoogle Scholar
- Voigt BD: Social organization and territoral behavior of the Galápagos sea lion Zalophus californianus wollebaeki (Sivertsen, 1953). Thesis. Kopenhagen. 1979, 1-75.Google Scholar
- East ML, Burke T, Wilhelm K, Greig C, Hofer H: Sexual conflicts in spotted hyenas: male and female mating tactics and their reproductive outcome with respect to age, social status and tenure. Proc Biol Sci. 2003, 270 (1521): 1247-1254. 10.1098/rspb.2003.2363.PubMed CentralView ArticlePubMedGoogle Scholar
- Poston JP: Dominance, access to colonies, and queues for mating opportunities by male boat-tailed grackles. Behav Ecol Sociobiol. 1997, 41 (2): 89-98. 10.1007/s002650050368.View ArticleGoogle Scholar
- Kunc H, Wolf JBW: Seasonal changes of vocal rates and their relation to territorial status in male Galápagos sea lions (Zalophus wollebaeki). Ethology. 2008, 114: 381-388. 10.1111/j.1439-0310.2008.01484.x.View ArticleGoogle Scholar
- Hoffman JI, Trathan PN, Amos W: Genetic tagging reveals extreme site fidelity in territorial male Antarctic fur seals Arctocephalus gazella. Mol Ecol. 2006, 15 (12): 3841-3847. 10.1111/j.1365-294X.2006.03053.x.View ArticlePubMedGoogle Scholar
- Hoffman JI, Boyd IL, Amos W: Male reproductive strategy and the importance of maternal status in the antarctic fur seal Arctocephalus gazella. Evolution. 2003, 57 (8): 1917-1930.View ArticlePubMedGoogle Scholar
- Hendry AP: Selection against migrants contributes to the rapid evolution of ecologically dependent reproductive isolation. Evol Ecol Res. 2004, 6: 1219-1236.Google Scholar
- Nosil P, Vines TH, Funk DJ: Reproductive isolation caused by natural selection against immigrants from divergent habitats. Evolution. 2005, 59: 705-719.PubMedGoogle Scholar
- Simkin T: Geology of Galápagos Islands. Key environments – Galápagos. Edited by: Perry R. 1984, Oxford: Pergamon Press, 15-43.Google Scholar
- Kurz MD, Rowland S, Curtice J, Saal A, Naumann T: Eruption rates at Fernandina volcano, Galápagos archipelago, from cosmogenic helium surficial laval flows. Eos Trans AGU. 2005, 86 (52): Fall Meet. Suppl., Abstract U33A-0016Google Scholar
- Naumann T, Geist D: Physical volcanology and structural development of Cerro Azul volcano, Isabela island, Galápagos: implications for the development of Galápagos-type shield volcanoes. Bull Volcanol. 2000, 61: 497-514.Google Scholar
- Harrod C, Grey J: Isotopic variation complicates analysis of trophic relations within the fish community of Plußsee: a small, deep, stratifying lake. Archiv für Hydrobiologie. 2006, 167: 281-299. 10.1127/0003-9136/2006/0167-0281.View ArticleGoogle Scholar
- Harrod C, Grey J, McCarthy TK, Morrissey M: Stable isotope analyses provide new insights into ecological plasticity in a mixohaline population of European eel. Oecologia. 2005, 144: 673-683. 10.1007/s00442-005-0161-x.View ArticlePubMedGoogle Scholar
- Brunner S, Bryden MM, Shaughnessy PD: Cranial ontogeny of otariid seals. Syst Biodivers. 2004, 2 (1): 83-110. 10.1017/S1477200004001367.View ArticleGoogle Scholar
- EMBL Align database. http://www.ebi.ac.uk/embl/Submission/alignment.html OR http://srs.ebi.ac.uk OR ftp://ftp.ebi.ac.uk/pub/databases/embl/align/
- Excoffier L, Laval G, Schneider S: Arlequin ver. 3.0: An integrated software package for population genetics data analysis. Evol Bioinformatics Online. 2005, 1: 47-50.Google Scholar
- Rassmann K, Tautz D, Trillmich F, Gliddon C: The microevolution of the Galápagos marine iguana Amblyrhynchus cristatus assessed by nuclear and mitochondrial genetic analyses. Mol Ecol. 1997, 6 (5): 437-452. 10.1046/j.1365-294X.1997.00209.x.View ArticleGoogle Scholar
- Wolf JBW, Tautz D, Caccone A, Steinfartz S: Development of new microsatellite loci and evaluation of loci from other pinniped species for the Galápagos sea lion (Zalophus californianus wollebaeki). Conserv Genet. 2006, 7 (3): 461-465. 10.1007/s10592-005-9045-1.View ArticleGoogle Scholar
- Hoffman JI, Steinfartz S, Wolf JBW: Ten novel dinucleotide microsatellite loci cloned from the Galápagos sea lion (Zalophus californianus wollebaeki) are polymorphic in other pinniped species. Mol Ecol Notes. 2007, 7 (1): 103-105. 10.1111/j.1471-8286.2006.01544.x.View ArticleGoogle Scholar
- Falush D, Stephens M, Pritchard JK: Inference of population structure using multilocus genotype data: Linked loci and correlated allele frequencies. Genetics. 2003, 164 (4): 1567-1587.PubMed CentralPubMedGoogle Scholar
- Evanno G, Regnaut S, Goudet J: Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study. Mol Ecol. 2005, 14: 2611-2620. 10.1111/j.1365-294X.2005.02553.x.View ArticlePubMedGoogle Scholar
- Pritchard JK, Stephens M, Donnelly P: Inference of population structure using multilocus genotype data. Genetics. 2000, 155 (2): 945-959.PubMed CentralPubMedGoogle Scholar
- Weir BS, Cockerham CC: Estimating F-statistics for the analysis of population structure. Evolution. 1984, 38: 1358-1370. 10.2307/2408641.View ArticleGoogle Scholar
- Goodman SJ: R-ST Calc: a collection of computer programs for calculating estimates of genetic differentiation from microsatellite data and determining their significance. Mol Ecol. 1997, 6 (9): 881-885. 10.1111/j.1365-294X.1997.tb00143.x.View ArticleGoogle Scholar
- Goudet J: FSTAT: a program to estimate and test gene diversities and fixation indices (version 2.9.3). 2001, [http://www.unil.ch/izea/softwares/fstat.html]Google Scholar
- Goudet J, Raymond M, De Meeüs T, Rousset F: Testing differentiation in diploid populations. Genetics. 1996, 144: 1933-1949.PubMed CentralPubMedGoogle Scholar
- Minch E, Ruiz-Linares A, Goldstein DB, Feldman M, Cavalli-Sforza LL: Microsat (version 1.5d): a program for calculating various statistics on microsatellite allele data. 1997, Stanford, CA: Stanford UniversityGoogle Scholar
- Felsenstein J: PHYLIP (Phylogeny Inference Package) version 3.6. Distributed by the author Department of Genome Sciences, University of Washington, Seattle. 2004Google Scholar
- Rousset F: Genetic differentiation between individuals. J Evol Biol. 2000, 13 (1): 58-62. 10.1046/j.1420-9101.2000.00137.x.View ArticleGoogle Scholar
- Ihaka R, Gentleman R: R: a language for data analysis and graphics. J Comput Graph Stat. 1996, 5: 299-314. 10.2307/1390807.Google Scholar
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