ArticlePDF Available

Remarkably low genetic diversity and strong population structure in common bottlenose dolphins (Tursiops truncatus) from coastal waters of the Southwestern Atlantic Ocean


Abstract and Figures

Knowledge about the ecology of bottlenose dolphins in the Southwestern Atlantic Ocean is scarce. Increased by-catch rates over the last decade in coastal waters of southern Brazil have raised concerns about the decline in abundance of local dolphin communities. Lack of relevant data, including information on population structure and connectivity, have hampered an assessment of the conservation status of bottlenose dolphin communities in this region. Here we combined analyses of 16 microsatellite loci and mitochondrial DNA (mtDNA) control region sequences to investigate genetic diversity, structure and connectivity in 124 biopsy samples collected over six communities of photographically identified coastal bottlenose dolphins in southern Brazil, Uruguay and central Argentina. Levels of nuclear genetic diversity were remarkably low (mean values of allelic diversity and heterozygosity across all loci were 3.6 and 0.21, respectively), a result that possibly reflects the small size of local dolphin communities. On a broad geographical scale, strong and significant genetic differentiation was found between bottlenose dolphins from southern Brazil-Uruguay (SB-U) and Bahia San Antonio (BSA), Argentina (AMOVA mtDNA I broken vertical bar(ST) = 0.43; nuclear F-ST = 0.46), with negligible contemporary gene flow detected based on Bayesian estimates. On a finer scale, moderate but significant differentiation (AMOVA mtDNA I broken vertical bar(ST) = 0.29; nuclear F-ST = 0.13) and asymmetric gene flow was detected between five neighbouring communities in SB-U. Based on the results we propose that BSA and SB-U represent two distinct evolutionarily significant units, and that communities from SB-U comprise five distinct Management Units (MUs). Under this scenario, conservation efforts should prioritize the areas in southern Brazil where dolphins from three MUs overlap in their home ranges and where by-catch rates are reportedly higher.
Content may be subject to copyright.
Remarkably low genetic diversity and strong population structure
in common bottlenose dolphins (Tursiops truncatus) from coastal
waters of the Southwestern Atlantic Ocean
Pedro F. Fruet Eduardo R. Secchi Fa
´bio Daura-Jorge Els Vermeulen
Paulo A. C. Flores Paulo Ce
´sar Simo
˜es-Lopes Rodrigo Ce
´zar Genoves
Paula Laporta Juliana C. Di Tullio Thales Renato O. Freitas Luciano Dalla Rosa
Victor Hugo Valiati Luciano B. Beheregaray Luciana M. Mo
Received: 13 September 2013 / Accepted: 24 February 2014
ÓSpringer Science+Business Media Dordrecht 2014
Abstract Knowledge about the ecology of bottlenose
dolphins in the Southwestern Atlantic Ocean is scarce.
Increased by-catch rates over the last decade in coastal
waters of southern Brazil have raised concerns about the
decline in abundance of local dolphin communities. Lack of
relevant data, including information on population structure
and connectivity, have hampered an assessment of the
conservation status of bottlenose dolphin communities in
this region. Here we combined analyses of 16 microsatellite
loci and mitochondrial DNA (mtDNA) control region
sequences to investigate genetic diversity, structure and
connectivity in 124 biopsy samples collected over six
communities of photographically identified coastal bottle-
nose dolphins in southern Brazil, Uruguay and central
Argentina. Levels of nuclear genetic diversity were
remarkably low (mean values of allelic diversity and het-
erozygosity across all loci were 3.6 and 0.21, respectively), a
result that possibly reflects the small size of local dolphin
communities. On a broad geographical scale, strong and
significant genetic differentiation was found between bot-
tlenose dolphins from southern Brazil–Uruguay (SB–U) and
´a San Antonio (BSA), Argentina (AMOVA mtDNA
=0.43; nuclear F
=0.46), with negligible contem-
porary gene flow detected based on Bayesian estimates. On a
finer scale, moderate but significant differentiation (AM-
=0.29; nuclear F
=0.13) and
Electronic supplementary material The online version of this
article (doi:10.1007/s10592-014-0586-z) contains supplementary
material, which is available to authorized users.
P. F. Fruet (&)
Programa de Po
˜o em Oceanografia Biolo
´gica, FURG,
Rio Grande, Brazil
P. F. Fruet L. B. Beheregaray L. M. Mo
Molecular Ecology Laboratory, School of Biological Sciences,
Flinders University, Bedford Park, SA, Australia
P. F. Fruet E. R. Secchi R. C. Genoves
J. C. Di Tullio L. D. Rosa
Museu Oceanogra
´fico ‘‘Prof. Elie
´zer C. Rios’’, FURG,
Rio Grande, Brazil
P. F. Fruet E. R. Secchi R. C. Genoves
J. C. Di Tullio L. D. Rosa
´rio de Ecologia e Conservac¸a
˜o da Megafauna Marinha,
Instituto de Oceanografia, FURG, Rio Grande, Brazil
P. F. Fruet L. M. Mo
Cetacean Ecology, Behaviour and Evolution Lab, School of
Biological Sciences, Flinders University, Bedford Park, SA,
F. Daura-Jorge P. C. Simo
´rio de Mamı
´feros Aqua
´ticos (LAMAQ), UFSC,
´polis, Brazil
E. Vermeulen
Laboratory of Oceanology - MARE Research Centre, University
of Liege, Lie
`ge, Belgium
P. A. C. Flores
Centro Nacional de Pesquisa e Conservac¸a
˜o de Mamı
´ticos - CMA, ICMBio, MMA, Floriano
´polis, Brazil
P. Laporta
Yaqu-pacha Uruguay, Punta del Diablo, Rocha, Uruguay
T. R. O. Freitas
Departamento de Gene
´tica, Universidade Federal do Rio Grande
do Sul, Porto Alegre, Brazil
V. H. Valiati
´rio de Biologia Molecular, Unisinos, Sa
˜o Leopoldo,
Conserv Genet
DOI 10.1007/s10592-014-0586-z
asymmetric gene flow was detected between five neigh-
bouring communities in SB–U. Based on the results we
propose that BSA and SB–U represent two distinct evolu-
tionarily significant units, and that communities from SB–U
comprise five distinct Management Units (MUs). Under this
scenario, conservation efforts should prioritize the areas in
southern Brazil where dolphins from three MUs overlap in
their home ranges and where by-catch rates are reportedly
Keywords Cetacean Conservation Connectivity
Population genetics Microsatellite Mitochondrial DNA
Bottlenose dolphins (Tursiops spp.) are cetaceans able to
explore, occupy and adapt to different marine environ-
ments, with the exception of polar regions. Many genetic
studies of bottlenose dolphins around the globe have
reported moderate genetic differentiation among regional
populations, despite some reproductive exchange (Sellas
et al. 2005; Rosel et al. 2009; Tezanos-Pinto et al. 2009;
Urian et al. 2009; Mirimin et al. 2011). Over large spatial
scales, genetic discontinuities appear to coincide with
ecological and topographic breaks, such as distinct water
masses, currents and depth contours (Hoelzel et al. 1998a;
Natoli et al. 2004; Bilgmann et al. 2007). On the other
hand, habitat selection (e.g. open coast vs. estuarine eco-
systems) and local adaptation to prey resources are
believed to shape population structure over small spatial
scales (Mo
¨ller et al. 2007; Wiszniewski et al. 2010).
Therefore, a combination of environmental, geomorpho-
logical and evolutionary factors appears to influence the
genetic structure of bottlenose dolphin populations,
although some may represent cryptic species-level differ-
ences (e.g. Natoli et al. 2004; Rosel et al. 2009).
Despite being extensively studied in many regions of the
world, limited information is available for bottlenose dol-
phins of the Southwestern Atlantic Ocean (SWA); partic-
ularly scarce are details of their genetic diversity and
population structure. Understanding population sub-divi-
sions and connectivity provides information critical to the
identification of relevant biological units to be conserved.
These include evolutionary significant units (ESUs)—a
group of historically isolated populations with unique
genealogical and adaptive legacy—and Management Units
(MUs)—demographically distinct populations that should
be managed separately to ensure the viability of the larger
metapopulation (see Funk et al. 2012 for definitions and a
recent perspective on ESUs and MUs). This is especially
important in cases where populations are restricted in dis-
tribution, have small population sizes and are subject to
human induced mortality, which is the case for bottlenose
dolphins of the SWA. It has been reported that in the SWA
coastal bottlenose dolphins are mainly found between
Santa Catarina State, in southern Brazil, and Central
Argentina—and particularly along a narrow coastal corri-
dor between southern Brazil and Uruguay (SB–U) (Laporta
et al. in press). In this region, bottlenose dolphins occur in
bays and estuaries, and between the surf zone and 2 km
from the coastline when in the open-coast, with occasional
records between 2 and 4 km (Laporta 2009; Di Tullio
2009). The distribution of coastal and offshore bottlenose
dolphins apparently does not overlap and their feeding
ecology is distinct, at least in part of the SWA (e.g. Botta
et al. 2012). Concerns about the conservation of coastal
bottlenose dolphins in SWA has recently emerged due to
their relatively small population sizes (Laporta 2009; Fruet
et al. 2011; Daura-Jorge et al. 2013), vulnerability to by-
catch (Fruet et al. 2012) and substantial coastal develop-
ment, particularly in southern Brazil (Tagliani et al. 2007).
A long-term study of dolphin strandings has revealed high
levels of mortality along Brazil’s southernmost coastline,
mainly in areas adjacent to the Patos Lagoon estuary where
by-catch seems to be the main cause of death (Fruet et al.
Systematic photo-identification studies have shown that
coastal bottlenose dolphins of the SWA consist of small
communities with high site fidelity to estuaries and river
mouths (and each community not exceeding 90 individuals,
Fruet et al. in press a). These are often bordered by other
small bottlenose dolphin communities that show more
extensive movements along the coast, in contrast to estu-
arine communities (Laporta et al. in press). Photo-identi-
fication efforts in the two main estuaries of southern Brazil
suggest that bottlenose dolphins exhibit long-term resi-
dency in these areas (Fruet et al. 2011; Daura-Jorge et al.
2013). Although there is distribution overlap of dolphins
from these estuarine-associated and the adjacent coastal
communities, no information is available on the levels of
genetic connectivity among them. For example, social
network analyses has revealed the existence of at least
three distinct communities, which partially overlap in
range near the Patos Lagoon estuary, in southern Brazil
(Genoves 2013). This includes the year-round resident
community of the Patos Lagoon estuary and two coastal
communities: one that regularly moves from Uruguay to
southern Brazil during winter and spring (Laporta 2009)
and another which appears to inhabit the adjacent coastal
waters of the Patos Lagoon estuary year-round. Such range
overlap suggests potential for interbreeding among indi-
viduals of these communities, which would have implica-
tions for MUs classification and conservation management
efforts. Given the assumption of demographic indepen-
dence between different MUs, their delineation requires a
Conserv Genet
direct or indirect estimate of current dispersal rates (Pals-
bøll et al. 2007). However, dispersal rates can be difficult
to estimate, particularly in the marine environment, which
lacks marked physical barriers and where many organisms
are not easily accessible for long-term field studies of
identifiable or tagged individuals. In these cases, genetic
methods generally offer a suitable alternative to assess
dispersal rates and other indicators of demographic inde-
pendence, as well as for estimating genetic diversity.
In this study we investigate the genetic diversity and
population structure of bottlenose dolphins along the SWA
coast using data from nuclear microsatellite markers and
mtDNA control region sequences. We use this information
to assess the strength and directionality of genetic con-
nectivity over a range of spatial scales. Our sampling
design allows comparisons among neighbouring coastal
communities in southern Brazil-Uruguay (SB–U), and
between these and a community inhabiting Bahı
´a San
Antonio (BSA) in the Patagonian coast—the most southern
resident bottlenose dolphin community known for the
SWA and located in a different marine biogeographical
region to southern Brazil-Uruguay. We hypothesize that
specialization for, or association with particular habitat
types such as estuaries and open coasts may promote
genetic differentiation on small spatial scales, while the
biogeographical disjunction may influence differentiation
at broad scale. The adjacent dolphin communities sampled
in SB–U include two estuarine and three open coast com-
munities. If habitat type specialization or, association with,
drives genetic structure, we might expect to find lower
genetic differentiation between communities inhabiting the
contiguous open coast habitat than those living in sheltered
estuarine environments, irrespective of geographical dis-
tances. We also expect that greater differentiation would
characterize communities from different biogeographical
regions. By delineating conservation units for coastal bot-
tlenose dolphins in the SWA we expect to provide scien-
tific support to guide strategies for population monitoring
efforts, conservation status assessment and short-term
management goals.
Sampling scheme
The study area covers approximately 2,112 km of linear
distance along the coast. It extends from Floriano
´polis, in
southern Brazil, to Bahı
´a San Antonio, in the Patagonian
Argentina. Along this region we surveyed six locations
between 2004 and 2012 and collected 135 samples (Fig. 1).
Samples consisted primarily of skin tissueobtained from free-
ranging coastal bottlenose dolphins (common bottlenose
dolphins, Tursiops truncatus—see Wang et al. (1999)for
southern Brazil bottlenose dolphins molecular taxonomic
identification) belonging to communities inhabiting a variety
of habitat types: Floriano
´polis (FLN, coastal, n=9), Laguna
(LGN, estuarine, n=11), north of Patos Lagoon (NPL,
coastal, n=21), Patos Lagoon estuary (PLE, estuarine,
n=71), south of Patos Lagoon/Uruguay (SPL/URU, coastal,
n=14) and Bahı
´a San Antonio, Argentina (BSA, coastal
bay, n=12) (Table 1). Samples were collected using a
crossbow with 150 lb (68 kg) draw weight and darts and tips
especially designed for sampling small cetaceans (Ceta-Dart,
Copenhagen, Denmark). We attempted to individually iden-
tify sampled dolphins through simultaneous photo-identifi-
cation (see Fruet et al. in press b for details). Samples were
grouped according to the sampled location. For those col-
lected in the adjacent coastal areas of Patos Lagoon estuary,
where three distinct communities live in close proximity and
overlap in their range, identified individuals were grouped
according to the social unit to which they were previously
assigned based on social network analysis (Genoves 2013).
Our dataset also included four samples from freshly stranded
carcasses, two collected in La Coronilla, Uruguay, and two in
southern Brazil from animals known to belong to the NPL
community as photo-identified based on their natural marks
prior to their death. Samples were preserved in 20 % dimethyl
sulphoxide (DMSO) saturated with sodium chloride (Amos
and Hoelzel 1991) or 98 % ethanol.
Genetic methods
Genomic DNA was extracted from all samples following a
salting-out protocol (Sunnucks and Hales 1996). Sex of each
biopsy sample was determined by the amplification of
fragments of the SRY and ZFX genes through the polymerase
chain reaction (PCR) (Gilson et al. 1998), with PCR condi-
tions described in Mo
¨ller et al. (2001). Samples were geno-
typed at 16 microsatellite loci (Online Resource 1) and a
fragment of approximately 550 bp of the control region was
sequenced using primers Dlp-1.5 and Dlp-5 (Baker et al.
1993) on an ABI 3730 (Applied Biosystems) with GenScan
500 LIZ 3130 internal size standard. Procedures for micro-
satellite PCR and genotyping are found in Mo
¨ller and Be-
heregaray (2004), and for mtDNA PCR and sequencing in
¨ller and Beheregaray (2001). For microsatellites, bins for
each locus were determined and genotypes scored in GENE-
MAPPER 4.0 (Applied Biosystems). Rare alleles (i.e. fre-
quency \0.05) or alleles that fell in between two bins were
re-genotyped. Micro-Checker 2.2.3 (Van Oosterhout et al.
2004) was used to check for potential scoring errors, the
presence of null alleles, stuttering and large allelic drop out.
Genotyping error rates were estimated by re-genotyping 30
randomly selected samples, representing 22 % of the total
sample size used in this study. We used GENALEX6.5
Conserv Genet
(Peakall and Smouse 2012) to find potential matches
between genotypes and to estimate the probability of identity
as an indicator of the power of the 16 markers to distinguish
between two sampled individuals. Samples matching at all
genotypes or those mismatching at only a few alleles (1–2)
were double-checked for potential scoring errors. Sequences
of the mtDNA were edited using SEQUENCHER 3.0 (Gene
Codes Corporation, Ann Arbor, MI) and aligned using the
ClustalW algorithm in MEGA 5.05 (Tamura et al. 2011).
Haplotypes were defined using DNASP 5.0 (Librado and Rozas
2009). After careful examination, samples sharing identical
genotypes at all loci, same mtDNA haplotype and sex were
considered as re-sampled individuals and one of each pair
was removed. Re-sampled individuals identified by photo-
identification (n=7) were also confirmed through genetic
Data analysis
Population structure
We used 10,000 permutations in SPAGEDI to test for the rel-
ative importance of a stepwise mutation model as a
contributor to genetic diversity and structure (Hardy and
Vekemans 2002). This provides a way to assess whether F
or R
potentially provides a more appropriate statistic to
estimate genetic structure since R
accounts for divergence
times between microsatellite alleles and is thus expected to
better reflect older divergences (Hardy et al. 2003). Allele
size permutation test in SPAGEDI were non significant for all
loci. This suggests that F
is likely the most appropriate
estimator, and only F
values are therefore reported here-
after. ARLEQUIN was used for an analysis of molecular
variance (AMOVA) to evaluate differentiation between SB–
U and BSA dolphins, and among SB–U communities, for
both nuclear and mtDNA datasets. Degree of genetic dif-
ferentiation among locations was also assessed using
ARLEQUIN to calculate F
(Weir and Cockerham 1984) for
microsatellites, and both F
and U
measures for mtDNA.
For each of these measures we used the Tamura and Nei
(1993) model with a gamma correction of 0.5. Significance
was tested based on 10,000 permutations. We also estimated
the statistical power to detect nuclear differentiation using
POWSIM (Ryman and Palm 2006) by simulating six popula-
tions with samples sizes of each sampled community (8, 10,
19, 63, 12, 12) with F
of 0.05 (combining generation, time
Fig. 1 Study area in the Southwestern Atlantic Ocean showing the
proposed evolutionary significant units (ESUs) and management units
(MUs) (color counter lines) for coastal common bottlenose dolphins
(Tursiops truncatus), and the respective frequencies of mitochondrial
control region haplotypes (pie charts). Arrows indicate the main
sampling locations for each dolphin community. Approximate
geographic boundaries of management units were built combining
the results of this study with current knowledge on residency, social
structure and movement patterns of bottlenose dolphins along this
region. Specifically for NPL, the genetic assignment of some
individuals regularly sighted approximately 400 km north of Patos
Lagoon estuary (represented by stars) to NPL community were used
as a proxy to define the northern limit of the community range. The
dashed rectangle highlights the area of heightened conservation
concern proposed by this study (see ‘Conservation implications’’
section for details). FLN Floriano
´polis, LGN Laguna, NPL north of
Patos Lagoon, PLE Patos Lagoon estuary, SPL/URU south of Patos
Lagoon/Uruguay, BSA Bahı
´a San Antonio. (Color figure online)
Conserv Genet
t=25 with effective population size, N
=500), which
approximates the lowest empirical fixation index found
based on 15 loci (see ‘Results’ section). The a(Type I)
error was assessed running the same simulated scenario, but
sampling directly from the base population (i.e. setting drift
time t=0). A thousand replicates were run and the signif-
icance of the tests was assessed with Fisher’s exact tests and
Chi square tests.
The Bayesian clustering method implemented in
STRUCTURE 2.3.3 (Pritchard et al. 2000) was also used for
inferring population structure based on the microsatellite
data. We assumed correlated allele frequencies and an
admixture model using sampling location as prior infor-
mation (LOCPRIOR function) (Hubisz et al. 2009). Sim-
ulations were performed using a 200,000 step burn-in
period and 10
repetitions of the Markov Chain Monte
Carlo (MCMC) search, assuming number of clusters
(K) varying between 1 and 6. We performed 20 indepen-
dent runs to limit the influence of stochasticity, to increase
the precision of the parameter estimates, and to provide an
estimate of experimental reproducibility (Gilbert et al.
2012). The most likely K was explicitly determined by
examining DK (Evanno et al. 2005)inS
VESTER (Earl and vonHoldt 2012). Following the recom-
mendations of Evanno et al. (2005), we ran an iterative
process where, for each most likely K detected by STRUC-
TURE, we independently re-analyzed the data to test for
further sub-division. This process was repeated until the
most likely K was 1.
Isolation by distance (IBD) was assessed by conducting
Mantel tests (Mantel 1967) between matrices of F
genetic distances and geographical distances measured as
the shortest marine coastal distance between two locations.
Given the large geographical distance between the south-
ernmost sampling site (BSA) and others, we excluded BSA
from the IBD analysis. We also used partial Mantel tests to
test for an association between habitat type (estuarine
versus coastal) and genetic distance, while controlling for
the effect of geographical distance. Both tests were run
with 1,000 random permutations in GENODIVE 2.0.
Gene flow
Magnitude and direction of contemporary gene flow among
the six sampled communities was estimated using BAYE-
SASS 3.0 (Wilson and Rannala 2003). The software uses a
MCMC algorithm to estimate the posterior probability
distribution of the proportion of migrants from one popu-
lation to another. This was conducted with ten independent
MCMC runs of 10
steps, with the first 10
discarded as burn-in. To reach the recommended accep-
tance rates of total iterations between 20 and 40 % we
adjusted the values of continuous parameters such as
Table 1 Ecological information and summary of genetic diversity for the six communities and the two proposed evolutionary significant units (ESUs) of coastal common bottlenose dolphins
(Tursiops truncatus) based on mtDNA control region sequences and 15 microsatellite loci
N(f:m) Pop. size
(95 % CI)
mtDNA Microsatellites
Southern Brazil–
Uruguay ESU
FLN 8 (6:2) Unknown Coastal 0.7500 (0.0965) 0.0045 (0.0032) 0 1.6 1.6 0.19 0.23 -0.22 1.5 910
4.3 910
LGN 10 (2:8) 59 (49–72)
Estuarine 0.0000 (0.0000) 0.0000 (0.0000) 0 1.6 1.5 0.21 0.15 0.28* 1.3 910
3.6 910
NPL 19 (8:11) Unknown Coastal 0.5425 (0.1231) 0.0067 (0.0041) 2 2.3 1.9 0.20 0.19 0.06 7.5 910
3.5 910
PLE 63 (38:25) 86 (78–95)
Estuarine 0.4808 (0.0621) 0.0072 (0.0042) 9 3.0 2.0 0.26 0.26 -0.01 4.6 910
9.7 910
12 (5:7) Unknown Coastal 0.6484 (0.1163) 0.0067 (0.0041) 5 2.1 1.9 0.20 0.23 -0.02 3.5 910
2.4 910
Total 112 (59:53) 0.6457 (0.0404) 0.0096 (0.0053) 16 3.7 2.2 0.22 0.22 0.02
´a San Antonio ESU BSA 12 (2:10) 76 (70–97)
Coastal Bays 0.0000 (0.0000) 0.0000 (0.0000) 1 1.76 1.76 0.19 0.18 0.08 2.6 910
5.4 910
Total 124 (61:63) 0.7022 (0.0352) 0.0195 (0.0100) 3.6 0.28 0.23 0.194*
Ntotal number of individuals (separated by sex); PA number of private alleles; NA mean number of alleles per locus; AR mean allelic richness; H
mean expected heterozygosity; H
observed heterozygosity; F
inbreeding coefficient; PI
probabilities of identity for unbiased samples and samples of full-sibs, respectively
* Significant multi-locus Pvalue (P\0.001)
Daura-Jorge et al. (2013),
Fruet et al. (2011),
Vermeulen and Cammareri (2009)
Conserv Genet
migration rates (D
), allele frequencies (D
) and inbreed-
ing coefficient (D
) to 0.9, 0.6 and 0.8, respectively.
Samples were collected every 200 iterations to infer the
posterior probability distributions of parameters. Trace files
were monitored for convergence and runs with potential
problems were discarded. Additionally, convergence was
checked by comparing the migration rate profile between
the runs according to their average total likelihood and
associated credible confidence interval (CI).
Genetic diversity
For microsatellites, genetic diversity, expressed as number
of alleles (NA), expected (H
) and observed (H
) hetero-
zygosity, as well as the inbreeding coefficient (F
) were
estimated for each community in GENODIVE 2.0 (Meirmans
and Van Tienderen 2004). Departures from Hardy–Wein-
berg equilibrium and linkage disequilibrium were tested
using the Fisher’s exact test and a Markov chain method
with 1,000 iterations in GENEPOP 4.2 (Rousset 2008). Allelic
richness (AR) was estimated in FSTAT (Goudet
1995). All statistical tests followed sequential Bonferroni
correction to address type I errors associated with multiple
comparisons (Rice 1989). For the mtDNA sequences, we
used ARLEQUIN (Excoffier and Lischer 2010)to
estimate haplotypic and nucleotide diversities. A median-
joining network from the mtDNA haplotypes was con-
structed using NETWORK (Bandelt et al. 1999).
Summary statistics
A total of 134 biopsy samples and four samples from
stranded carcasses were used. All samples were success-
fully amplified at 16 microsatellite loci and sequenced for
approximately 550 bp of the mtDNA control region. Only
eight out of 450 repeated genotypes (1.7 %) did not match
but were resolved by re-genotyping. The probability of two
unrelated individuals or siblings sharing the same geno-
types was very low for all communities (Table 1). Multiple
lines of evidence (identical genotype, same mtDNA
sequence and sex) suggested that 14 biopsied individuals
were sampled twice, including seven individuals that were
suspected re-samples based on photo-identification. All re-
sampled animals were biopsied in the same location: eight
in PLE, two in SPL/URU, two in NPL, one in LGN, and
one in FLN. After removal of duplicates, 124 samples were
included in the final dataset analyzed. From these, 61
samples were males and 63 were females (Table 1).
The microsatellite locus Tur91 was monomorphic and
therefore excluded from further analysis. We found no
evidence for effects of large allelic dropout in any locus.
Null alleles were detected for two loci but these were not
consistent among sampled locations (locus TUR80 in PLE
and Ttr04 in BSA), and therefore the loci were kept for all
analyses. One locus pair (TUR105 and EV37) showed
evidence of linkage disequilibrium. However, because
similar results were obtained when analyses were run both
with and without TUR105 this locus was kept in the
dataset. Laguna was the only sample location that showed
significant deviation from Hardy–Weinberg equilibrium
when averaged across all loci, likely due to inbreeding
=0.28) in this small community. Inbreeding coeffi-
cient was low and non-significant for all other communities
(Table 1).
Genetic structure
The AMOVA results showed strong differentiation
between SB–U and BSA for both microsatellites
=0.46, P\0.001) and mtDNA (U
P\0.0001). On a smaller spatial scale, the AMOVA
indicated moderate differentiation among SB–U commu-
nities, for both microsatellites (F
=0.13, P\0.0001)
and mtDNA (U
=0.29, P\0.0001). Accordingly, sig-
nificant differentiation was observed for all pairwise
comparisons using microsatellites (Table 2), but over a
wide range of F
values (0.066–0.617). Excluding BSA,
which was by far the most differentiated (average F
0.51 for all comparisons with other communities), moder-
ate but significant differentiation was found between all
other pairwise comparisons, with the two geographically
closest communities (PLE and NPL) having the lowest
value of F
=0.06; P\0.001). POWSIM simulations
for 15 microsatellite loci and the sample sizes used in this
study suggested a 100 % probability of detecting differ-
entiation above the lowest empirical F
level of differ-
entiation, indicating satisfactory statistical power for our
analyses. The estimated type I error varied from 0.041 with
Fisher’s exact tests to 0.083 with v
tests, which approxi-
mates the conventional 5 % limit for significance testing.
Results of pairwise comparisons using mtDNA were
generally congruent with results from the microsatellite
analyses, albeit with higher levels of differentiation
between communities. The exceptions were NPL and PLE
(for both F
and U
), and NPL and FLN (for U
which showed no significant differentiation (Table 3). All
three of these communities are dominated by the most
common mtDNA haplotype (H08). Pairwise significant F
values ranged between 0.097 (NPL–FLN) to 1 (LGN–
BSA), with BSA the most differentiated community across
all comparisons.
Mantel tests revealed a positive and significant corre-
lation between microsatellites and mtDNA fixation indices
Conserv Genet
and geographical distances, suggesting a pattern of IBD
(Fig. 2). For the mtDNA data, the correlation was not as
strong (r
=0.428) as for the microsatellites (r
but still significant. Results of partial Mantel tests (details
not shown) suggested that differentiation was more likely
influenced by distance than by habitat type (estuarine
versus coastal). When controlling for geographical dis-
tances, non-significant relationships between locations and
clusters (cluster 1 and 2: estuarine and coastal communi-
ties, respectively) were found for both microsatellites
=-0.437; P=0.51) and mtDNA (r
Bayesian posterior probabilities indicated that the data-
set is best explained by the clustering of samples into two
genetic populations (K =2), with all individuals from
BSA placed in one cluster and remaining individuals
sampled in SB–U placed in a second cluster (Fig. 3a).
Negligible admixture appears to exist between these two
clusters, with assignment estimates of all individuals to
their respective clusters above 0.99 and 0.98, respectively.
Testing for further sub-division by running STRUCTURE
for the set of northern communities led to the identification
of additional partitioning within SB–U most consistent
with five populations (Fig. 3b–d). No sub-division was
detected within BSA (data not shown).
Gene flow
Estimates of contemporary gene flow inferred in BAYESASS
suggested very low gene flow from BSA to SB–U com-
munities (2.2 %) and negligible gene flow in the opposite
direction (0.3 %). Within the SB–U region, BAYESASS
revealed moderate and complex asymmetrical migration
rates (Table 4; Fig. 4) consistent with the inferred pattern
of IBD. Generally, higher migration occurred between
neighbouring communities than between those separated
by greater geographic distances, with the exception of
LGN, which seems to exchange more migrants with more
distant communities than with its closest neighbouring
community (FLN). Migration estimates between sampling
locations at the extremities of the sampling distribution was
low. Estimated migration rates from FLN to NPL and from
SPL/URU to PLE were at least twice the rates between all
other community pairs (Fig. 4). For the estuarine commu-
nities, PLE seems to act as a sink with a considerable rate
of migrants coming from LGN, NPL and SPL/URU, and
negligible migration in the opposite direction. In contrast,
LGN seems to be more closed to immigration while con-
tributing genetic migrants to PLE and NPL.
Genetic diversity
Levels of genetic variation were remarkably low for all
samples as measured by both allelic richness (AR) and
expected heterozygosity (H
) (Table 1; Appendix).
Observed heterozygosity (H
) ranged from 0.15 to 0.26,
with a mean across all loci of 0.21. AR ranged from 1.5 to
Table 2 Estimates of microsatellite differentiation among six coastal
communities of common bottlenose dolphins (Tursiops truncatus)
sampled along the Southwestern Atlantic Ocean
LGN 0.131** –
NPL 0.147** 0.169** –
PLE 0.144** 0.101** 0.066** –
0.289** 0.250** 0.156** 0.101** –
BSA 0.617** 0.502** 0.538** 0.423** 0.477**
Differentiation is expressed as F
based on 15 microsatellites loci
FLN Floriano
´polis, LGN Laguna, NPL north of Patos Lagoon, PLE
Patos Lagoon estuary, SPL/URU south of Patos Lagoon/Uruguay,
BSA Bahı
´a San Antonio
*P\0.05; ** P\0.01
Table 3 Estimates of mitochondrial differentiation among six coastal communities of common bottlenose dolphins (Tursiops truncatus)
sampled along the Southwestern Atlantic Ocean
FLN 0.659** 0.100* 0.209** 0.249** 0.687**
LGN 0.893** – 0.622** 0.572** 0.666** 1.000**
NPL 0.040 0.744** 0.009 0.297** 0.679**
PLE 0.198* 0.489** 0.06 0.329** 0.638**
SPL/URU 0.531** 0.466** 0.392** 0.230** – 0.689**
BSA 0.639** 1.000** 0.399** 0.340** 0.609**
Differentiation is expressed as U
(above diagonal) and F
(below diagonal) based on 457-bp of the mtDNA control region
FLN Floriano
´polis, LGN Laguna, NPL north of Patos Lagoon, PLE Patos Lagoon estuary, SPL/URU south of Patos Lagoon/Uruguay, BSA Bahı
San Antonio
*P\0.05; ** P\0.01
Conserv Genet
2.0, being higher in PLE, NPL and SPL/URU, and lower in
LGN and BSA. Number of alleles per locus ranged from
two to seven (Appendix) with a mean across all loci of 3.6,
while the mean number of alleles per community was two.
Out of 17 ‘‘private’’ (unique) alleles identified, nine were
found in PLE, five in SPL/URU, two in NPL and one in
BSA (Table 1). The only private allele in BSA was found
in high frequency in that community, while in all other
communities unique alleles had low frequencies.
After sequence alignment and editing, 457 bp of the
mtDNA control region could be analyzed for the same 124
individuals used for the microsatellite analysis. Thirteen
polymorphic sites (all transitional mutations) revealed nine
distinct haplotypes. The number of haplotypes detected in
each sampled location varied from one to five, and hap-
lotype diversity ranged from 0 to 0.75. Overall, nucleotide
diversity among all individuals was low (p=0.009), and
haplotype diversity moderate (h=0.712), although values
varied among communities. FLN community displayed the
highest level of haplotype diversity, while PLE had the
highest nucleotide diversity (Table 1). The most common
and widely dispersed haplotype (H8) was found in 49.6 %
of the individuals and across all locations, except in LGN
and BSA where all dolphins shared the same haplotypes
(H7 for LGN and H4 for BSA). Private haplotypes were
found in four of the six communities (FLN, n=1; NPL,
n=1; SPL/URU, n=2; BSA, n=1) (Fig. 1).
The median-joining network showed two main groups
of haplotypes separated by a minimum of five mutational
steps (Fig. 5). Individuals from PLE, NPL and SPL/URU
communities were present in both groups while individ-
uals from LGN, BSA and FLN were represented in only
one of the groups. Bahı
´a San Antonio retains a unique
haplotype (H05), which is fixed for this location and
differs from the most common haplotype (H08) by one
mutational step.
This study comprises the first comprehensive assessment of
population structure and genetic diversity of coastal
Fig. 2 Isolation by distance
plots using Euclidean distance
(km) and genetic distance (F
among five coastal communities
of common bottlenose dolphins
(Tursiops truncatus) inhabiting
southern Brazil–Uruguay based
on amtDNA control region and
b15 microsatellite loci (lower
Conserv Genet
bottlenose dolphins (Tursiops truncatus) along the SWA.
On a large spatial scale, we report on two genetic popu-
lations (SB–U and BSA) that are highly differentiated and
show very low level of gene flow. On a smaller spatial
scale, we detected low to moderate levels of asymmetric
gene flow between communities within the SB–U popula-
tion and an influence of geographic distance in shaping
patterns of connectivity, perhaps with the exception of
Laguna. Here we also show that coastal bottlenose dolphins
in the SWA have very low levels of genetic diversity. This
reduced gene flow and genetic diversity, combined with the
small size and probable demographic independence of
communities, limit the likelihood of replenishment if they
undergo a genetic or demographic decline, highlighting the
need to implement local-based monitoring and conserva-
tion plans.
Large-scale population structure in SWA bottlenose
On a broad geographical scale, our results indicate that
bottlenose dolphins in coastal Argentinean Patagonia (BSA
Fig. 3 STRUCTURE Bayesian assignment probabilities for common
bottlenose dolphins (Tursiops truncatus) based on 15 microsatellite
loci. Each vertical line represents one individual dolphin and vertical
black lines separate the sampled communities. We run an iterative
process where for each most likely K detected by STRUCTURE we
independently re-analyzed the data to test for further sub-division
(Evanno et al. 2005; Pritchard et al. 2007). This process was repeated
iteratively until the highest likelihood values resulted in K =1. When
all samples were analyzed together, STRUCTURE clearly separated
individuals sampled in BSA from all those sampled in southern
Brazil/Uruguay, resulting in K =2(a). The highest DK for the next
run within southern Brazil/Uruguay communities was for K =2,
clustering LGN, PLE and SPL/URU, and FLN and NPL (b). When we
run STRUCTURE independently for the above-mentioned clusters,
the highest DK resulted for K =3(c) and K =2(d), respectively.
FLN Floriano
´polis, LGN Laguna, NPL north of Patos Lagoon, PLE
Patos Lagoon estuary, SPL/URU south of Patos Lagoon/Uruguay,
BSA Bahı
´a San Antonio. (Color figure online)
Conserv Genet
community) are highly differentiated from those sampled
along the southern Brazil–Uruguay (SB–U) coast, likely
reflecting a combination of IBD and environmental dif-
ferentiation. Several studies have argued that bottlenose
dolphins are capable of specialization for a variety of
habitats and prey types, and that such specialization could
promote genetic divergence (Hoelzel et al. 1998a; Natoli
et al. 2004;Mo
¨ller et al. 2007; Tezanos-Pinto et al. 2009;
Wiszniewski et al. 2010;Mo
¨ller 2012). Bahı
´a San Antonio
is located in the San Matı
´as Gulf (Fig. 1), which is part of
the Northern Patagonian gulfs of Argentina. Geomorpho-
logical characteristics (bathymetry and coastal complex-
ity), oceanographic processes (upwelling, nutrient input,
sea surface temperature regimes and currents), and bio-
logical community structure biogeographically distin-
guishes the Patagonian region from the rest of the Atlantic
coast (Balech and Ehrlich 2008; Tonini 2010). For exam-
ple, archaeozoological evidence suggests that one of the
main prey species of bottlenose dolphins in SB–U, the
white croaker (Micropogonias furnieri) (Pinedo, 1982;
Mehsen et al. 2005), is currently absent from BSA (Scar-
tascini and Volpedo 2013), which is the northernmost limit
for many prey species confirmed to be part of the diet of
bottlenose dolphins in Patagonia (e.g. pouched lamprey
(Geotria australis), Patagonian octopus (Octopus tehuel-
chus), Argentine Hake (Mercluccius hubbsi) (Crespo et al.
2008), as it is located at the boundary between two bio-
geographic regions (Galva
´n et al. 2009). Regional differ-
ences in prey distribution and abundance are thought to
play a role on the genetic structuring of bottlenose dolphins
elsewhere (e.g. Bilgmann et al. 2007). Therefore, BSA
bottlenose dolphins may have different foraging adapta-
tions compared to SB–U bottlenose dolphins. The high
degree of differentiation at neutral markers and the results
from the Bayesian analysis of migration rates imply neg-
ligible gene flow between bottlenose dolphin communities
of these two regions. Future studies combining morpho-
logical, genetic, environmental, and ecological data are
needed to better clarify the taxonomic status between BSA
and SB–U coastal bottlenose dolphins.
Fine-scale population structure in SWA bottlenose
In spite of their high dispersal potential, several empirical
studies have shown that coastal bottlenose dolphins often
form discrete population units, even at very small geo-
graphical scales (e.g. Sellas et al. 2005;Mo
¨ller et al. 2007;
Rosel et al. 2009; Ansmann et al. 2012). Our results from
both fixation indices and the Bayesian clustering analysis
confirmed that the five studied communities within the SB–
U population are genetically distinct, indicating higher
genetic differentiation than expected over small
Table 4 Estimates of recent migration rates among six coastal communities of common bottlenose dolphins (Tursiops truncatus) sampled along the Southwestern Atlantic Ocean
From To
FLN 0.6915 (0.646–0.736) 0.0232 (0.019–0.066) 0.2152 (0.133–0.296) 0.0237 (0.019–0.067) 0.0232 (0.019–0.065) 0.0232 (0.019–0.063)
LGN 0.0209 (0.017–0.058) 0.6887 (0.648–0.728) 0.1289 (0.016–0.241) 0.1197 (0.007–0.232) 0.0209 (0.017–0.058) 0.0210 (0.017–0.059)
NPL 0.0126 (0.011–0.036) 0.0127 (0.011–0.036) 0.8454 (0.738–0.952) 0.1036 (0.001–0.208) 0.0127 (0.012–0.037) 0.0129 (0.010–0.036)
PLE 0.0050 (0.004–0.015) 0.0054 (0.004–0.015) 0.0455 (0.003–0.094) 0.9343 (0.883–0.985) 0.0049 (0.010–0.019) 0.0049 (0.004–0.014)
SPL/URU 0.0181 (0.015–0.051) 0.0179 (0.016–0.052) 0.0237 (0.029–0.076) 0.2367 (0.141–0.331) 0.6855 (0.621–0.749) 0.0180 (0.015–0.051)
BSA 0.0182 (0.015–0.051) 0.0183 (0.015–0.051) 0.0182 (0.015–0.052) 0.0185 (0.015–0.052) 0.0183 (0.015–0.052) 0.9084 (0.841–0.975)
Bold denotes the proportion of non-migrants in each dolphin community. 95 % CI values are given in brackets
FLN Floriano
´polis, LGN Laguna, NPL north of Patos Lagoon, PLE Patos Lagoon estuary, SPL/URU south of Patos Lagoon/Uruguay; BSA Bahı
´a San Antonio
Conserv Genet
geographical scales. Relatively lower degrees of nuclear
genetic differentiation are commonly reported for bottle-
nose dolphins over comparable spatial scales with the
exception of the high differentiation found among the
neighbouring communities of T. truncatus in Irish coastal
waters (Shannon estuary and Connemara–Mayo commu-
nities F
=0.179; Mirimin et al. 2011). For instance,
lower differentiation was found between neighbouring
communities of T. truncatus along the coast of the western
North Atlantic (minimum and maximum reported F
values of 0.002 and 0.015, respectively; Rosel et al. 2009)
and Bahamas (F
=0.048; total distance between two
sampling sites was 116 km; Parsons et al. 2006).
For highly mobile, long-lived animals with low repro-
ductive rates such as cetaceans, it is well accepted that a
combination of mechanisms including habitat selection,
specialized foraging behaviours, social structure and natal
philopatry can drive population differentiation across small
spatial scales (Hoelzel 2009;Mo
¨ller 2012). For a closely
related species, the Indo-Pacific bottlenose dolphins,
restricted gene flow between some coastal and estuarine
communities appears to have occurred after coastal dol-
phins colonized the embayment, as a consequence of high
site fidelity and resource and behavioural specializations
¨ller et al. 2007). In our study, however, we actually
found similar levels of genetic differentiation when com-
paring coastal and estuarine communities or among coastal
communities of the common bottlenose dolphin in SWA.
This pattern is contrary to what would be expected if
habitat type was a main driver of bottlenose dolphin pop-
ulation structure in the region. Instead, for most commu-
nities, structure appeared to follow an isolation-by-distance
model, where exchange of individuals seems to more likely
occur between adjacent communities, irrespective of hab-
itat type. The only exception was Laguna, which appeared
as an outlier to the IBD model. In Laguna, a unique for-
aging tactic involving cooperative interactions between
dolphins and beach-casting fishermen has evolved. It has
been suggested that the propagation of such behaviour
through social learning has a matrilineal origin, where the
mother–calf relationship might create conditions suitable
for behavioural information exchange (Daura-Jorge et al.
2012). In such special conditions, the costs to individuals
of leaving a suitable habitat is likely greater than the risk of
searching for more profitable locations. In contrast, some
Fig. 4 Schematic diagram showing the recent asymmetric migration
rates estimated between five coastal communities of common
bottlenose dolphins (Tursiops truncatus) sampled along southern
Brazil and Uruguay. The width of the arrows corresponds to the rates
of gene flow between putative populations
Fig. 5 Median-joining network of mtDNA control region haplotypes
in coastal common bottlenose dolphins (Tursiops truncatus). The size
of the circles is proportional to the total number of individuals bearing
that haplotype. Dashed lines separate the two main groups of
haplotypes. Different colors denote the different sampled communi-
ties: FLN Floriano
´polis, LGN Laguna, NPL north of Patos Lagoon,
PLE Patos Lagoon estuary, SPE/URU south of Patos Lagoon/
Uruguay, BSA Bahı
´a San Antonio. Dashes represent extinct or
unsampled haplotypes. (Color figure online)
Conserv Genet
PLE dolphins frequently interact with animals from other
communities in the coastal zone, and there is no evidence
of particular feeding specializations compared to LGN.
Thus, it appears that feeding specializations (LGN) and
sociality (PLE), instead of habitat type per se, may play a
role in shaping genetic structure of bottlenose dolphins in
these regions.
The contemporary asymmetric gene flow found in our
study system suggests moderate levels of connectivity
among communities in SB–U ESU, which are consistent
with a metapopulation. Gene flow is particularly mediated
by coastal communities, especially FLN and SPL/URU,
although estuarine communities exchange genes as well. It
seems that PLE potentially acts as a sink, receiving low to
moderate number of migrants while not contributing sub-
stantially to other communities. In contrast, LGN showed
much lower gene flow with adjacent communities, appar-
ently constituting a more closed genetic unit. This pattern
is also supported by mitochondrial data, which suggested
high connectivity between PLE and the adjacent coastal
community (NPL), but high maternal philopatry and
restricted dispersal of LGN dolphins.
Remarkably low levels of genetic diversity in SWA
bottlenose dolphins
Low genetic variation was detected with both mitochon-
drial and nuclear DNA markers across all communities.
Levels of variation at the mtDNA control region were
similar to those reported for T. truncatus in other parts of
the world. In contrast, nuclear DNA variation for all
communities was much lower than that reported for other
local coastal communities elsewhere (see Online Resource
2 for comparisons with studies of Parsons et al. 2006; Rosel
et al. 2009; Tezanos-Pinto et al. 2009; Mirimin et al. 2011;
Caballero et al. 2012). This is supported by the low num-
bers of alleles, reduced allelic richness and reduced het-
erozygosity. For LGN and BSA communities in particular,
the remarkably low variation at both marker types fall
within the range observed for cetaceans with extremely
small populations sizes (i.e. \100 individuals), such as the
subspecies of Hector’s dolphins, Cephalorhyncus hectori
mauii (Hamner et al. 2012), and the Black Sea subspecies
of the harbour porpoise, Phocoena phocoena relicta (Rosel
et al. 1995). These findings are consistent with the current
abundance estimates of less than 90 individuals for the
BSA, PLE, and LGN communities (Vermeulen and Cam-
mareri 2009; Fruet et al. 2011; Daura-Jorge et al. 2013) and
may also reflect the potential small size of the other
communities (such as FLN, NPL and SPL/URU) for which
estimates of abundance are not currently available. Several
authors have suggested that coastal populations of bottle-
nose dolphin elsewhere might have originated via inde-
pendent founder events from offshore populations,
followed by local adaptation and natal philopatry (Hoelzel
et al. 1998a; Natoli et al. 2004; Sellas et al. 2005;Mo
et al. 2007; Tezanos-Pinto et al. 2009), leading to a
reduction in genetic diversity.
Conservation implications
On a large geographical scale our results strongly support
that SB–U and BSA dolphins constitute at least two distinct
ESUs, and these warrant separate conservation and man-
agement strategies. The SB–U ESU comprises a set of
communities (or sub-populations) distributed along a nar-
row strip of the coast between Florianopolis (27°210S) in
southern Brazil, and the southern limit of the Uruguayan
coast (34°550S). The BSA ESU geographical range goes
possibly from the northern border of Rio Negro Province,
at the Rio Negro estuary (41°010S), to southern Golfo
Nuevo (43°050S), as suggested by sightings of bottlenose
dolphins in northern Patagonia (Vermeulen and Cammareri
2009; Coscarella et al. 2012). Our results indicate that these
two ESUs are genetically isolated which has important
implications for future conservation plans. It is funda-
mental that managers design appropriate conservation
strategies for each ESU, taking into account their respec-
tive threats, genetic and ecological processes shaping
structure, and geographical distribution in space and time,
as their responses to future environmental changes may
possibly differ. This is of particular relevance for BSA
dolphins since they apparently constitute the only popula-
tion within that ESU with reduced abundance and signs of
historical decline (Bastida and Rodrı
´guez 2003; Coscarella
et al. 2012).
The most serious and continuous threats for bottlenose
dolphins along the SWA coast are found within the SB–U
ESU, where they have experienced increased rates of
human-related mortalities during the past decade (Fruet
et al. 2012). These animals also face considerable coastal
habitat degradation as a consequence of ongoing industrial
and port development activities (Tagliani et al. 2007).
Based on this study we suggest that these dolphin com-
munities within SB–U are functionally independent, and
therefore should be treated as separate MUs for conserva-
tion purposes. We advocate for managers to adopt the
proposed MUs reported here (see Fig. 1), while
Conserv Genet
recognizing that their boundaries may change as more
information on dolphin home ranges and population
genetic structure becomes available. Under this proposed
management scenario, conservation programs should be
directed towards the Patos Lagoon estuary and adjacent
coastal waters where dolphins from distinct communities
(PLE, NPL and SPL/URU) show overlapping home ranges,
and where by-catch rates are reportedly higher (Fig. 1).
Protecting dolphins in this region would reduce the risk of
disrupting connectivity between MUs and increase the
chances of long-term viability. Strategies should reduce the
impact of by-catch and maximize the protection of ‘‘cor-
ridors’’ in coastal areas for maintaining connectivity
between adjacent dolphin communities.
The very low levels of genetic diversity in coastal bot-
tlenose dolphins from SWA could be a source for concern.
The importance of genetic variation relates to multiple
aspects of population resilience and persistence, and is
usually assumed to be critical for long-term fitness and
adaptation (Franklin 1980; Charlesworth and Willis 2009),
although some studies have shown that minimal genetic
variation is not always a reliable predictor of extinction risk
in wild populations (e.g. Schultz et al. 2009). We propose,
however, the adoption of a precautionary approach for
coastal bottlenose dolphins in SWA. Although there is no
evidence of inbreeding depression for bottlenose dolphins
in this region, the possibility of inbreeding in the small
LGN community (Table 1) may, in the long-term, be det-
rimental to its viability since inbreeding can increase vul-
nerability to environmental stressors (O’Brien et al. 1985;
Frankham 1995; Spielman et al. 2004; Hale and Briskie
2007). Bottlenose dolphins from Laguna and their neigh-
bouring community (FLN) are being affected by a chronic
dermal infection, the fungal Lobomycosis, and Lobomy-
cosis-like disease (LLD) (Van Bressen et al. 2007, Daura-
Jorge and Simo
˜es-Lopes 2011), with evidence of an
increase in the number of affected animals in recent years
(Daura-Jorge and Simo
˜es-Lopes 2011). While our results
suggest restricted dispersal of LGN dolphins, which may
limit the spread of the disease, the isolated nature of this
community can potentially accelerate fungal transmission
among resident dolphins.
Common bottlenose dolphins from coastal waters of the
SWA are characterized by unprecedentedly low mito-
chondrial and nuclear DNA diversity. Moderate to strong
levels of population differentiation at both marker types
were also disclosed and are likely associated with a com-
bination of geographical, environmental and social factors.
The pattern of genetic differentiation and the negligible
migration rates detected suggest two distinct lineages, or
evolutionarily significant units, one in Argentina and the
other in southern Brazil-Uruguay. In addition, five distinct
communities, or Management Units, characterized by low
to moderate asymmetrical gene flow were identified in
southern Brazil–Uruguay—a region where human activi-
ties negatively impact upon common bottlenose dolphins.
We propose that policies and practices relevant to conser-
vation management of common bottlenose dolphins in
coastal waters of the SWA should recognize the existence
of two lineages, as well as promote connectivity between
the estuarine and open-coast populations in southern Brazil
and Uruguay to ensure their long-term persistence.
Acknowledgments We thank many people who have helped during
our field surveys along South America and provided logistical sup-
port, including Alejandro Cammarieri, Dan Jacob Pretto, Paulo
Mattos, Paulo Henrique Ott, Mauricio Cantor, Ana Costa, Jonatas
Henrique Prado, Mariana Rosa Fetter, Rafael V. Camargo, Ma
Bozzeti, Juliana Wolmann Gonc¸alves, Caio Eichenberger and Ricardo
Castelli. Special thanks to Lauro Barcellos (Director of the Museu
´fico-FURG) for providing logistical support to this project.
Jonatan Sandovall-Castillo, Chris Brauer, Fabrı
´cius Domingos and
Kerstin Bilgmann provided helpful advice on molecular methods and
analysis. This study was made possible by the financial support of
Yaqu Pacha Foundation (Germany), the Brazilian Long Term Eco-
logical Program (PELD—National Council for Research and Tech-
nological Development/CNPq), Porto do Rio Grande (Brazil), and
grants-in-aid-research provided by the Society for Marine Mammal-
ogy in 2001 (USA). The Coordination for Enhancement of Higher
Education Personnel (CAPES—Brazil) provided a PhD scholarship to
P.F. Fruet (Programa de Po
˜o em Oceanografia Biolo
Instituto de Oceanografia, Universidade Federal do Rio Grande-
FURG). National Council for Research and Technological Develop-
ment (Brazil) provided a fellowship to E.R.Secchi (PQ 307843/2011-
4) and an international fellowship to P.F Fruet (SWE 201567/2011-3).
Flinders University of South Australia provided a fee waiver as part
of P.F. Fruet’s PhD cotutelle program between this university and
Universidade Federal do Rio Grande. Samples were collected under
regional permits (Brasil: SISBIO 24429-1 issued to PAC Flores,
SISBIO 24407-2 issued to PF Fruet) and transferred to Australia
under CITES permits 11BR007432/DF and 2011-AU-647980. This is
a contribution of the Research Group ‘‘Ecologia e Conservac¸a
Megafauna Marinha—EcoMega/CNPq’’ and is also publication #52
from MEGMAR (the Molecular Ecology Group for Marine Research
at Flinders University).
See Table 5.
Conserv Genet
Table 5 Genetic diversity screened at 16 microsatellite loci in six coastal communities of common bottlenose dolphin sampled along the Southwestern Atlantic
FLN (n=8) LGN (n=10) NPL (n=19) PLE (n=63) SPL/URU (n=12) BSA (n=12)
1 0.00 0.00 NA 1 0.00 0.00 NA 1 0.00 0.00 NA 2 0.01 0.01 1.00 1 0.00 0.00 NA 1 0.00 0.00 NA
1 0.00 0.00 NA 1 0.00 0.00 NA 1 0.00 0.00 NA 1 0.00 0.00 NA 1 0.00 0.00 NA 1 0.00 0.00 NA
2 0.25 0.23 1.00 1 0.00 0.00 NA 1 0.00 0.00 NA 2 0.06 0.06 1.00 2 0.08 0.08 1.00 2 0.08 0.08 1.00
1 0.00 0.00 NA 1 0.00 0.00 NA 1 0.00 0.00 NA 3 0.06 0.09 0.05 2 0.08 0.08 1.00 2 0.25 0.23 1.00
3 0.75 0.66 0.77 3 0.30 0.59 0.02* 3 0.45 0.53 0.15 4 0.68 0.65 0.85 3 0.67 0.68 0.21 2 0.33 0.39 1.00
1 0.00 0.00 NA 1 0.00 0.00 NA 1 0.00 0.00 NA 4 0.04 0.04 1.00 1 0.00 0.00 NA 2 0.25 0.23 1.00
1 0.00 0.00 NA 2 0.10 0.10 1.00 2 0.05 0.05 1.00 5 0.03 0.08 0* 2 0.08 0.23 0.13 1 0.00 0.00 NA
1 0.00 0.00 NA 1 0.00 0.00 NA 1 0.00 0.00 NA 3 0.03 0.03 1.00 1 0.00 0.00 NA 1 0.00 0.00 NA
1 0.00 0.00 NA 1 0.00 0.00 NA 1 0.00 0.00 NA 1 0.00 0.00 NA 1 0.00 0.00 NA 2 0.58 0.52 1.00
3 0.62 0.62 0.73 2 0.60 0.53 1.00 5 0.50 0.45 0.13 4 0.43 0.46 0.03* 4 0.75 0.69 0.45 2 0.42 0.43 1.00
2 0.75 0.50 0.43 2 0.20 0.50 0.08 5 0.60 0.62 0.92 5 0.55 0.67 0.15 3 0.08 0.70 0.55 1 0.00 0.00 NA
1 0.00 0.00 NA 2 0.30 0.39 0.48 2 0.15 0.14 1.00 2 0.46 0.39 0.20 1 0.00 0.00 NA 2 0.08 0.08 1.00
2 0.62 0.46 0.48 2 0.20 0.50 0.08 3 0.25 0.23 1.00 3 0.44 0.43 1.00 4 0.17 0.30 0.09 1 0.00 0.00 NA
2 0.12 0.12 1.00 1 0.00 0.00 NA 2 0.05 0.05 1.00 1 0.00 0.00 NA 2 0.08 0.08 1.00 2 0.25 0.23 1.00
2 0.12 0.12 1.00 1 0.00 0.00 NA 3 0.35 0.50 0.23 3 0.63 0.51 0.06 2 0.33 0.29 1.00 1 0.00 0.00 NA
2 0.50 0.40 1.00 3 0.70 0.65 0.37 4 0.65 0.66 0.37 5 0.78 0.75 0.69 4 0.58 0.47 1.00 3 0.42 0.68 0.28
NA number of alleles, H
observed heterozygosity, H
expected heterozygosity, PP-value of exact test using Markov chain, NA not available
* Significant deviation from Hardy–Weinberg equilibrium (P\0.05)
Nater et al. (2009),
¨tzen et al. (2001),
Hoelzel et al. (1998b),
Valsecchi and Amos (1996),
Rooney et al. (1999),
Rosel et al. (2005)
Conserv Genet
Amos W, Hoelzel AR (1991) Long-term preservation of whale skin
for DNA analysis. Rep Int Whaling Comm Spec Issue 13:99–104
Ansmann IC, Parra GJ, Lanyon JM, Seddon JM (2012) Fine-scale
genetic population structure in a mobile marine mammal:
inshore bottlenose dolphins in Moreton Bay, Australia. Mol
Ecol 21:4472–4485
Baker CS, Perry A, Bannister JL, Weinrich MT, Abernethy RB,
Calambokidis J, Lien J, Lambertensen RH, Urba
´rez J,
Vasquez O, Clapham PJ, Alling A, O’Brien SJ, Palumbi SR
(1993) Abundant mitochondrial DNA variation and world-wide
population structure in humpback whales. Proc Natl Acad Sci
USA 90:8239–8243
Balech E, Ehrlich MD (2008) Esquema biogeogra
´fico del mar
Argentino. Rev Invest Desarr Pesq 19:45–75
Bandelt HJ, Forster P, Ro
¨hl A (1999) Median-joining networks for
inferring intraspecific phylogenies. Mol Biol Evol 16:37–48
Bastida R, Rodrı
´guez D (2003) Mamı
´feros Marinos de Patagonia y
´rtida Vazquez Maziini (ed), 1st edn. Buenos Aires
Bilgmann K, Mo
¨ller LM, Harcourt RG, Gibbs SE, Beheregaray LB
(2007) Genetic differentiation in bottlenose dolphins from South
Australia: association with local oceanography and coastal
geography. Mar Ecol Prog Ser 341:265–276
Botta S, Hohn AA, Macko SA, Secchi ER (2012) Isotopic variation in
delphinids from the subtropical western South Atlantic. J Mar
Biol Assoc UK 92(8):1689–1698
Caballero S, Islas-Villanueva V, Tezanos-Pinto G, Duchene S,
Delgado-Estrella A, Sanchez-Okrucky R, Mignucci-Giannoni
AA (2012) Phylogeography, genetic diversity and population
structure of common bottlenose dolphins in the Wider Caribbean
inferred from analyses of mitochondrial DNA control region
sequences and microsatellite loci: conservation and management
implications. Anim Conserv 15:95–112
Charlesworth D, Willis JH (2009) The genetics of inbreeding
depression. Nat Rev Genet 10:783–796
Coscarella MA, Dans SL, Degrati M, Garaffo G, Crespo EA (2012)
Bottlenose dolphins at the southern extreme of the south-western
Atlantic: local population decline? J Mar Biol Assoc UK
Crespo EA, Garcı
´a NA, Dans SL, Pedraza SN (2008) Mamı
marinos. In: Boltovskoy D (ed) Atlas de Sensibilidad Ambiental
de la Costa y el Mar Argentino. Secretarı
´a de Ambiente y
Desarrollo Sustentable de la Nacio
´n, Buenos Aires
Daura-Jorge F, Simo
˜es-Lopes PC (2011) Lobomycosis-like disease in
wild bottlenose dolphins Tursiops truncatus of Laguna, southern
Brazil: monitoring of a progressive case. DisAquat Org 93:163–170
Daura-Jorge FG, Cantor M, Ingram SN, Lusseau D, Simo
˜es-Lopes PC
(2012) The structure of a bottlenose dolphin society is coupled to
a unique foraging cooperation with artisanal fishermen. Biol Lett
Daura-Jorge F, Ingram SN, Simo
˜es-Lopes PC (2013) Seasonal
abundance and adult survival of bottlenose dolphins (Tursiops
truncatus) in a community that cooperatively forages with
fishermen in southern Brazil. Mar Mamm Sci 29:293–311
Di Tullio JC (2009) Uso do habitat do boto, Tursiops truncatus,no
´rio da Lagoa dos Patos e a
´guas costeiras adjacentes, RS,
Brasil. Dissertation, Universidade Federal do Rio Grande
Earl DA, vonHoldt BM (2012) STRUCTURE HARVESTER: a
website and program for visualizing STRUCTURE output and
implementing the Evanno method. Conserv Genet Resour
Evanno G, Regnaut S, Goudet J (2005) Detecting the number of
clusters of individuals using the software STRUCTURE: a
simulation study. Mol Ecol 14:2611–2620
Excoffier L, Lischer HEL (2010) Arlequin suite ver 3.5: a new series
of programs to perform population genetics analyses under
Linux and Windows. Mol Ecol Res 10:564–567
Frankham R (1995) Inbreeding and extinction: a threshold effect.
Conserv Biol 9:792–799
Franklin I (1980) Evolutionary changes in small populations. In: Soule
M, Wilcox B (eds) Conservation biology: an evolutionary-ecolog-
ical perspective. Sinauer Associates, Suderland, pp 135–140
Fruet PF, Secchi ER, Di Tullio JC, Kinas PG (2011) Abundance of
bottlenose dolphins, Tursiops truncatus (Cetacea: Delphinidae),
inhabiting the Patos Lagoon estuary, southern Brazil: implica-
tions for conservation. Zoologia 28:23–30
Fruet PF, Kinas PG, Silva KG, Di Tullio JC, Monteiro DS, Dalla Rosa
L, Estima SC, Secchi ER (2012) Temporal trends in mortality
and effects of by-catch on common bottlenose dolphins,
Tursiops truncatus, in southern Brazil. J Mar Biol Assoc UK
Fruet PF, Flores PAC, Laporta P (in press a) Report of the working
group on population parameters and demography of Tursiops
truncatus in the Southwestern Atlantic Ocean. Lat Am J Aquat
Fruet PF, Dalla Rosa L, Genoves RC, Valiati VH, Freitas TRO,
¨ller LM (in press b). Biopsy darting of common bottlenose
dolphins (Tursiops truncatus) in southern Brazil: evaluating
effectiveness, short-term responses and wound healing. Lat Am J
Aquat Mamm
Funk WC, McKay JK, Hohenlohe PA, Allendorf FW (2012)
Harnessing genomics for delineating conservation units. Trends
Ecol Evol 27(9):489–496
´n DE, Venerus LA, Irigoyen AJ (2009) The reef-fish fauna of
the northern Patagonian gulfs, Argentina, southwestern Atlantic.
Open Fish Sci J 2:90–98
Genoves RC (2013) Estrutura social do boto, Tursiops truncatus
(Cetacea: Delphinidae) no estua
´rio da Lagoa dos Patos e a
costeiras adjacentes, sul do Brasil. Universidade Federal do Rio
Grande, Rio Grande
Gilbert KJ, Andrew RL, Bock DG et al (2012) Recommendations for
utilizing and reporting population genetic analyses: the repro-
ducibility of genetic clustering using the program structure. Mol
Ecol 21:4925–4930
Gilson A, Syvanen M, Levine KF, Banks JD (1998) Deer gender
determination by polymerase chain reaction: validation study
and application to tissues, bloodstains, and hair forensic samples
from California. Calif Fish Game 84:159–169
Goudet J (1995) FSTAT (Version 1.2): a computer program to
calculate F-statistics. J Hered 86:485–486
Hale KA, Briskie JV (2007) Decreased immunocompetence in a
severely bottlenecked population of an endemic New Zealand
bird. Anim Conserv 10:2–10
Hamner RM, Pichler FB, Heimeier D, Constantine R, Baker CS
(2012) Genetic differentiation and limited gene flow among
fragmented populations of New Zealand endemic Hector’s and
Maui’s dolphins. Conserv Genet 13:987–1002
Hardy O, Vekemans X (2002) Spagedi: a versatile computer program
to analyse spatial genetic structure at the individual or population
levels. Mol Ecol Notes 2:618–620
Hardy JO, Charbonnel N, Fre
´ville H, Heuertz M (2003) Microsatellite
allele sizes: a simple test to assess their significance on genetic
differentiation. Genetics 163:1467–1482
Hoelzel AR (2009) Evolution of population genetic structure in
marine mammal species. In: Bertorelle G, Bruford M, Hauffe H
(eds) Population genetics for animal conservation. Cambridge
University Press, Cambridge, pp 294–318
Hoelzel AR, Potter CW, Best PB (1998a) Genetic differentiation
between parapatric ‘‘nearshore’’ and ‘‘offshore’’ populations of
Conserv Genet
the bottlenose dolphin. Proc R Soc Lond B Biol Sci
Hoelzel AR, Dahlheim M, Stern SJ (1998b) Low genetic variation
among killer whales (Orcinus orca) in the eastern north Pacific
and genetic differentiation between foraging specialists. J Hered
Hubisz MJ, Falush D, Stephens M, Pritchard JK (2009) Inferring
weak population structure with the assistance of sample group
information. Mol Ecol Res 9:1322–1332
¨tzen M, Valsecchi E, Connor RC, Sherwin WB (2001) Charac-
terization of microsatellite loci in Tursiops aduncus. Mol Ecol
Notes 1:170–172
Laporta P (2009) Abunda
ˆncia, distribuic¸a
˜o e uso do habitat do boto
(Tursiops truncatus) em Cabo Polonio e La Coronilla (Rocha,
Uruguai). Dissertation, Universidade Federal do Rio Grande
Laporta P, Di Tullio JC, Vermeulen E, Domit C, Albuquerque C, Lodi
L (in press) Report of the working group on habitat use of
Tursiops truncatus in the Southwestern Atlantic Ocean. Lat Am
J Aquat Mamm
Librado P, Rozas J (2009) DnaSP v5: a software for comprehensive
analysis of DNA polymorphism data. Bioinformatics 25:
Mantel N (1967) The detection of disease clustering and a generalized
regression approach. Cancer Res 27:209–220
Mehsen M, Secchi ER, Fruet P, Di Tullio J (2005) Feeding habits of
bottlenose dolphins, Tursiops truncatus, in southern Brazil.
Paper SC/58/SM8 presented during the International Whaling
Commission Meeting. Ulsan, South Korea. Available online at
Meirmans PG, Van Tienderen PH (2004) Genotype and Genodive:
two programs for the analysis of genetic diversity of asexual
organisms. Mol Ecol Notes 4:792–794
Mirimin L, Miller R, Dillane E, Berrow SD, Ingram S, Cross TF,
Rogan E (2011) Fine-scale population genetic structuring of
bottlenose dolphins in Irish coastal waters. Anim Conserv
¨ller LM (2012) Sociogenetic structure, kin associations and
bonding in delphinids. Mol Ecol 21:745–764
¨ller LM, Beheregaray LB (2001) Coastal bottlenose dolphins from
southeastern Australia are Tursiops aduncus according to
sequences of the mitochondrial DNA control region. Mar Mamm
Sci 17:249–263
¨ller LM, Beheregaray LB (2004) Genetic evidence for sex-biased
dispersal in resident bottlenose dolphins (Tursiops aduncus).
Mol Ecol 13:1607–1612
¨ller LM, Beheregaray LB, Harcourt RG, Kru
¨tzen M (2001)
Alliance membership and kinship in wild male bottlenose
dolphins (Tursiops aduncus) of southeastern Australia. Proc R
Soc Lond B Biol Sci 268:1941–1947
¨ller LM, Wiszniewski J, Allen SJ, Beheregaray LB (2007) Habitat
type promotes rapid and extremely localised genetic differenti-
ation in dolphins. Mar Freshw Res 58:640–648
Nater A, Kopps AM, Kru
¨tzen M (2009) New polymorphic tetranu-
cleotide microsatellites improve scoring accuracy in the bottle-
nose dolphin Tursiops aduncus. Mol Ecol Res 9:531–534
Natoli A, Peddemors VM, Hoelzel AR (2004) Population structure
and speciation in the genus Tursiops based on microsatellite and
mitochondrial DNA analyses. J Evol Biol 17:363–375
O’Brien SJ, Roelke ME, Marker L, Newman A, Winkler CA, Meltzer
D, Colly L, Evermann JF, Bush M, Wildt DE (1985) Genetic basis
for species vulnerability in the cheetah. Science 227:1428–1434
Palsbøll PJ, Be
´M, Allendorf FW (2007) Identification of
management units using population genetic data. Trends Ecol
Evol 22:11–16
Parsons KM, Durban JW, Claridge DE, Herzing DL, Balcomb KC,
Noble LR (2006) Population genetic structure of coastal
bottlenose dolphins (Tursiops truncatus) in the northern Baha-
mas. Mar Mamm Sci 22:276–298
Peakall R, Smouse PE (2012) GenAlEx 6.5: genetic analysis in Excel.
Population genetic software for teaching and research: an update.
Bioinformatics 28:2537–2539
Pinedo MC (1982) Ana
´lise dos conteu
´dos estomacais de Pontoporia
blanvillei (Gervais e D’Orbigny, 1844) e Tursiops gephyreus
(Lahille, 1908) (Ceta
´cea, Platanistidae e Delphinidae) na zona
estuarial e costeira de Rio Grande, RS, Brasil. Master Thesis,
Universidade Federal do Rio Grande, Rio Grande
Pritchard J, Stephens M, Donnelly P (2000) Inference of population
structure using multilocus genotype data. Genetics 155:945–959
Pritchard JK, Wen X, Falush D (2007) Documentation for structure
software: version 2.2. Available from http://pritch.bsd.uchicago.
Rice W (1989) Analyzing tables of statistical tests. Evolution
Rooney AP, Merritt DB, Derr JN (1999) Microsatellite diversity in
captive bottlenose dolphins (Tursiops truncatus). J Hered
Rosel PE, Dizon AE, Haygood MG (1995) Variability of the
mitochondrial control region in populations of the harbour
porpoise, Phocoena, on interoceanic and regional scales. Can J
Fish Aquat Sci 52:1210–1219
Rosel PE, Forgetta V, Dewar K (2005) Isolation and characterization
of twelve polymorphic microsatellite markers in bottlenose
dolphins (Tursiops truncatus). Mol Ecol Notes 5:830–833
Rosel P, Hansen L, Hohn AA (2009) Restricted dispersal in a
continuously distributed marine species: common bottlenose
dolphins Tursiops truncatus in coastal waters of the western
North Atlantic. Mol Ecol 18:5030–5045
Rousset F (2008) Genepop’007: a complete re-implementation of the
genepop software for Windows and Linux. Mol Ecol Res
Ryman N, Palm S (2006) POWSIM: a computer program for
assessing statistical power when testing for genetic differentia-
tion. Mol Ecol 6:600–602
Scartascini FL, Volpedo AV (2013) White croaker (Micropogonias
furnieri) paleodistribution in the southwestern Atlantic ocean: an
archaeological perspective. J Archaeol Sci 40:1059–1066
Schultz J, Baker JD, Toonen RJ, Bowen B (2009) Extremely low
genetic diversity in the endangered Hawaiian Monk Seal
(Monachus schauinslandi). J Hered 100:25–33
Sellas AB, Wells RS, Rosel PE (2005) Mitochondrial and nuclear
DNA analyses reveal fine scale geographic structure in bottle-
nose dolphins (Tursiops truncatus) in the Gulf of Mexico.
Conserv Genet 6:715–728
Spielman D, Brook BW, Briscoe DA, Frankham R (2004) Does
inbreeding and loss of genetic diversity decrease disease
resistance? Conserv Genet 5:439–448
Sunnucks P, Hales DF (1996) Numerous transposed sequences of
mitochondrial cytochrome oxidase I–II in aphids of the genus
Sitobion (Hemiptera: Aphididae). Mol Biol Evol 13:510–524
Tagliani PRA, Asmus ML, Tagliani CRA, Polette M, Costa CSB,
Salas E (2007) Integrated coastal zone management in the Patos
Lagoon estuary (South Brazil): state of art. WIT Trans Ecol
Environ 103:679–686
Tamura K, Nei M (1993) Estimation of the number of nucleotide
substitutions in the control region of mitochondrial DNA in
humans and chimpanzees. Mol Biol Evol 10:512–526
Tamura K, Peterson D, Peterson N, Stecher G, Masatoshi N, Kumar S
(2011) MEGA5: molecular evolutionary genetics analysis using
maximum likelihood, evolutionary distance, and maximum
parsimony methods. Mol Biol Evol 28:2731–2739
Tezanos-Pinto G, Baker CS, Russell K, Martien K, Baird RW, Hutt A,
Stone G, Mignucci-Giannoni AA, Caballero S, Endo T, Lavery
Conserv Genet
S, Oremus M, Olavarrı
´a C, Garrigue C (2009) A worldwide
perspective on the population structure and genetic diversity of
bottlenose dolphins (Tursiops truncatus) in New Zealand.
J Hered 100:11–24
Tonini M (2010) Modelado nume
´rico del ecosistema de los golfos
´nicos. 2010. Phd thesis, Universidad Nacional del Sur,
´a Blanca
Urian KW, Hofmann S, Wells RS, Read AJ (2009) Fine-scale
population structure of bottlenose dolphins (Tursiops truncatus)
in Tampa Bay, Florida. Mar Mamm Sci 25:619–638
Valsecchi E, Amos W (1996) Microsatellite markers for the study of
cetacean populations. Mol Ecol 5:151–156
Van Bressen MF, Van Waerebeek K, Reyes JC et al (2007) A
preliminary overview of skin and skeletal diseases and traumata
in small cetaceans from South American waters. Lat Am J Aquat
Mamm 6:7–42
Van Oosterhout C, Hutchinson WF, Wills DPM, Shipley P (2004)
Micro-Checker: software for identifying and correcting geno-
typing errors in microsatellite data. Mol Ecol Notes 4:535–538
Vermeulen E, Cammareri A (2009) Residency patterns, abundance,
and social composition of bottlenose dolphins (Tursiops trunc-
atus) in Bahı
´a San Antonio, Patagonia, Argentina. Aquat Mamm
Wang JY, Chou L-S, White BN (1999) Mitochondrial DNA analysis
of sympatric morphotypes of bottlenose dolphins (genus:
Tursiops) in Chinese waters. Mol Ecol 8:1603–1612
Weir BS, Cockerham CC (1984) Estimating F-statistics for the
analysis of population structure. Evolution 38:1358–1370
Wilson GA, Rannala B (2003) Bayesian inference of recent migration
rates using multilocus genotypes. Genetics 163:1177–1191
Wiszniewski J, Beheregaray LB, Allen SJ, Mo
¨ller LM (2010)
Environmental and social influences on the genetic structure of
bottlenose dolphins (Tursiops aduncus) in Southeastern Austra-
lia. Conserv Genet 11:1405–1419
Wiszniewski J, Corrigan S, Beheregaray LB, Mo
¨ller LM (2012) Male
reproductive success increases with alliance size in Indo-Pacific
bottlenose dolphins (Tursiops aduncus). J Anim Ecol 81:423–431
Conserv Genet
... In recent years, several studies have looked at the genetic diversity and population structure of bottlenose dolphins in the SWAO. Fruet et al. (2014), using information from both the mtDNA CR and microsatellites, found extremely low genetic diversity in a population found in southern Brazil, Uruguay, and northern Argentina. The authors also found significant genetic differentiation between bottlenose dolphins from southern Brazil-Uruguay and those from Bahía San Antonio in Argentina, suggesting that these groups represent distinct ESUs. ...
... This study was very relevant, since this population has been showing decline in abundance over the last two decades (Coscarella et al., 2012;Vermeulen & Brager, 2015). Moreover, a significant genetic population structure was found within Brazil-Uruguay, encompassing five coastal populations recognized as distinct MUs (Fruet et al., 2014). A fine-scale population structure among distinct groups of coastal bottlenose dolphins in southern Brazil was also revealed by Costa et al. (2015) and Genoves et al. (2020). ...
Full-text available
Ecological information useful for conservation purposes have benefitted from recent and rapid advancements in genetic techniques, revealing unknown aspects of behavior, natural history, population structure and demography of several aquatic mammal species, many of them with conservation concerns. Molecular markers have been used to define management units, to settle taxonomic uncertainties, to control illegal wildlife trade, among others, providing valuable information to decision-making to conserve and manage aquatic mammals. We review genetic studies applied to conservation-related issues involving natural populations of more than 40 species of aquatic mammals in Latin America, covering four taxonomic groups. The main goal was to assess which genetic approaches have been used and to identify gaps in genetic research relating to geographic areas and species. We reviewed studies published in peer-reviewed journals between 2011 and 2022, and found that most were focused on population structure, phylogeography, gene flow and dispersal movements. The review revealed that researchers need to increase and improve the knowledge in those species which face major conservation concern. Scarce findings were related to forensics and its application to wildlife trade. In the era of next-generation-sequencing techniques, just a few studies used genomics as a tool for monitoring gene diversity, an important goal to help us predict how species will cope with climate change events. Looking to the future we suggest which species, geographic areas and genetic studies should be prioritized in a scenario of climate change and increased human threats (e.g., fishery bycatch, habitat degradation, etc.) and the urgent need for conservation actions. Finally, we highlight the benefits of the collaborative works and the necessity of generating a conservation genetic network, with an open agenda to discuss the local and regional problematics. All in all, we strongly emphasize the generation of critical information towards the effective conservation and management of aquatic mammals in Latin America.
... These dolphins have been studied since the end of the 1980s (Simões-Lopes, 1991;Simões-Lopes et al., 1998). It is a small population, approximately 54-60 individuals, with high site fidelity Daura-Jorge et al., 2013;Simões-Lopes & Fabian, 1999) and almost genetically isolated from other populations (Costa et al., 2015;Fruet et al., 2014). This population belongs to a recently recognized subspecies Tursiops truncatus gephyreus, endemic to the southwestern Atlantic Ocean Vermeulen et al. 2019). ...
Some dolphin species produce signature whistles, which may allow the identification of individual dolphins using passive acoustic monitoring (PAM). Identifying individuals by their sounds may enhance the opportunities for monitoring and addressing biological and ecological questions about these species. Here, we explored the potential of signature whistles to investigate ecological aspects of a resident bottlenose dolphin population. Using a limited data set, with few individuals recognized by signature whistles, combined with spatial capture‐recapture (SCR) methods, we investigated how effective such approach is describing spatial use patterns and estimating density for this population. The data were collected using 4–6 stationary bottom‐moored recorders. Since only eight signature whistles were identified, our density estimate may represent a subset of the entire population. However, even with only a few signature whistles identified, our results confirmed the center of the core area used by these dolphins as the area with the highest encounter probability. In addition, our results provided evidence that these dolphins have the same spatial use pattern at night as during the day. This study shows that SCR analysis of signature whistle data can improve our ecological knowledge and understanding of dolphin populations.
... This area represents the southernmost distribution limit for a Guiana dolphin population (Simões-Lopes, 1988), which resides in the area (Flores, 1999) exhibiting an unusual group cohesion for the species, as they remain in a single and large social group (Flores and Bazzalo, 2004;Flores and Fountoura, 2006). Additionally, one of the five management units (populations) of Lahille's bottlenose dolphin frequently utilizes this area (Fruet et al., 2014). Despite the sympatric occurrence of these two delphinid species on a regional scale, there is a clear spatial segregation between them at a fine scale within the Baía Norte (Flores and Fountoura, 2006). ...
... cultural and policing the detrimental fisheries-could prevent the extinction of this small, genetically distinct dolphin population (30). Safeguarding cultural behaviors that benefit both humans and wildlife not only encourages their coexistence (31) but is also emblematic of how the conservation of "culturally significant units" advances the conservation of biodiversity (6,32). ...
Interactions between humans and nature have profound consequences, which rarely are mutually beneficial. Further, behavioral and environmental changes can turn human-wildlife cooperative interactions into conflicts, threatening their continued existence. By tracking fine-scale behavioral interactions between artisanal fishers and wild dolphins targeting migratory mullets, we reveal that foraging synchrony is key to benefiting both predators. Dolphins herd mullet schools toward the coast, increasing prey availability within the reach of the net-casting fishers, who gain higher foraging success-but only when matching the casting behavior with the dolphins' foraging cues. In turn, when dolphins approach the fishers' nets closely and cue fishers in, they dive for longer and modify their active foraging echolocation to match the time it takes for nets to sink and close over mullets-but only when fishers respond to their foraging cues appropriately. Using long-term demographic surveys, we show that cooperative foraging generates socioeconomic benefits for net-casting fishers and ca. 13% survival benefits for cooperative dolphins by minimizing spatial overlap with bycatch-prone fisheries. However, recent declines in mullet availability are threatening these short- and long-term benefits by reducing the foraging success of net-casting fishers and increasing the exposure of dolphins to bycatch in the alternative fisheries. Using a numerical model parametrized with our empirical data, we predict that environmental and behavioral changes are pushing this traditional human-dolphin cooperation toward extinction. We propose two possible conservation actions targeting fishers' behavior that could prevent the erosion of this century-old fishery, thereby safeguarding one of the last remaining cases of human-wildlife cooperation.
... The Brazil-Malvinas Confluence has been proposed as an historical physical barrier to gene flow (Cortinhas et al., 2016;Vasconcellos, de Vasconcellos et al., 2015). The northern limit of the Brazil-Malvinas Confluence moves seasonally from 30 to 35°S during the winter to 40-46°S during the summer (Clauzet et al., 2007;Peterson & Stramma, 1991 Fruet et al., 2014;Secchi et al., 1998) and crustaceans (Weber & Levy, 2000). Geographically close estuaries can be very different from each other in terms of salinity, temperature, water quality and food stocks. ...
In the last 30 years a plethora of phylogeography studies were published targeting Brazilian marine species. To date several historical and extant physical and ecological processes have been identified as drivers of allopatric, sympatric and parapatric population genetic differentiation detected along the Brazilian coast. Examples of extant physical barriers include the split of the South Equatorial Current into the Brazil and North Brazil boundary currents, the mouth of major rivers (e.g. Amazon, São Francisco, and Doce river), and coastal upwellings. Examples of historical barriers include the Vitória‐Trindade seamount chain (VT) promoting genetic differentiation during periods of glacial maxima and lower sea levels. Examples of ecological speciation include adaptations to different substrata, resource use, and reproductive biology. We used published data to build datasets and generalized additive models to identify patterns of spatial phylogeographic concordance across multiple taxa and markers. Our results identify Cape São Roque as the most dominant extant barrier to gene flow along the Brazilian coast, followed by and the Vitória‐Trindade seamount chain and Cape Santa Marta. Cape Santa Marta in the winter is northern limit of the Rio da Plata plume and receives the intermittent influence of the Malvinas Current. This study provides a novel explicit quantitative approach to comparative phylogeography that recognizes four Brazilian phylogeographic regions delimited by processes associated with barriers to gene flow.
... Spatial segregation often occurs in socially or genetically structured groups of bottlenose dolphins [91]. Spatial segregation in common and Indo-Pacific bottlenose dolphins has been identified within estuarine systems, embayments, or lagoons [e.g., 7,11,12,82,87,91,93,[97][98][99][100], between or among estuarine and coastal groups [e.g., 8,14,84,[99][100][101][102][103][104], as well as in coastal open-water areas [9,94,104]. The spatial segregation often reflects site fidelity and occurs despite the lack of physical barriers to movements [e.g., 7,88,94,100,105]. ...
Full-text available
The social structure of estuarine-resident bottlenose dolphins is complex and varied. Residing in habitats often utilized for resource exploitation, dolphins are at risk due to anthropogenic pressures while still federally protected. Effective conservation is predicated upon accurate abundance estimates. In North Carolina, two estuarine-resident stocks (demographically independent groups) of common bottlenose dolphin have been designated using spatiotemporal criteria. Both stocks are subjected to bycatch in fishing gear. The southern North Carolina estuarine stock was estimated at
... Thus, it is likely that some ecotype was shaping the genetic architecture of the samples, with the offshore one being the most probable given its high frequency [55,56]. Our data are discrepant from prior studies in other regions where low genetic diversity has been reported [57]. Such differences reinforce the necessity of genetic studies and a validated set of markers to expand the knowledge about diversity within Tursiops. ...
... Thus, it is likely that some ecotype was shaping the genetic architecture of the samples, with the offshore one being the most probable given its high frequency [55,56]. Our data are discrepant from prior studies in other regions where low genetic diversity has been reported [57]. Such differences reinforce the necessity of genetic studies and a validated set of markers to expand the knowledge about diversity within Tursiops. ...
Full-text available
Genetic analysis is a conventional way of identifying and monitoring captive and wildlife species. Knowledge of statistical parameters reinforcing their usefulness and effectiveness as powerful tools for preserving diversity is crucial. Although several studies have reported the diversity of cetaceans such as Tursiops truncatus using microsatellites, its informative degree has been poorly reported. Furthermore, the genetic structure of this cetacean has not been fully studied. In the present study, we selected 15 microsatellites with which 210 dolphins were genetically characterized using capillary electrophoresis. The genetic assertiveness of this set of hypervariable markers identified one individual in the range of 6.927e13 to 1.806e16, demonstrating its substantial capability in kinship relationships. The genetic structure of these 210 dolphins was also determined regarding the putative capture origin; a genetic stratification (k = 2) was found. An additional dolphin group of undetermined origin was also characterized to challenge the proficiency of our chosen markers. The set of markers proposed herein could be a helpful tool to guarantee the maintenance of the genetic diversity rates in conservation programs both in Tursiops truncatus and across other odontocetes, Mysticeti and several genera of endangered and vulnerable species.
Full-text available
The mutation process at microsatellite loci typically occurs at high rates and with stepwise changes in allele sizes, features that may introduce bias when using classical measures of population differentiation based on allele identity (e.g., F(ST), Nei's Ds genetic distance). Allele size-based measures of differentiation, assuming a stepwise mutation process [e.g., Slatkin's R(ST), Goldstein et al.'s (deltamu)(2)], may better reflect differentiation at microsatellite loci, but they suffer high sampling variance. The relative efficiency of allele size- vs. allele identity-based statistics depends on the relative contributions of mutations vs. drift to population differentiation. We present a simple test based on a randomization procedure of allele sizes to determine whether stepwise-like mutations contributed to genetic differentiation. This test can be applied to any microsatellite data set designed to assess population differentiation and can be interpreted as testing whether F(ST) = R(ST). Computer simulations show that the test efficiently identifies which of F(ST) or R(ST) estimates has the lowest mean square error. A significant test, implying that R(ST) performs better than F(ST), is obtained when the mutation rate, mu, for a stepwise mutation process is (a) >/= m in an island model (m being the migration rate among populations) or (b) >/= 1/t in the case of isolated populations (t being the number of generations since population divergence). The test also informs on the efficiency of other statistics used in phylogenetical reconstruction [e.g., Ds and (deltamu)(2)], a nonsignificant test meaning that allele identity-based statistics perform better than allele size-based ones. This test can also provide insights into the evolutionary history of populations, revealing, for example, phylogeographic patterns, as illustrated by applying it on three published data sets.
Full-text available
Cetacean biopsy sampling is a widely used technique with undisputable scientific value. Although it is generally considered as a harmless technique with no apparent long-lasting effects, studies have recommended examining behavioral responses to evaluate potential impacts on individuals, groups and sampled populations. In this study, we evaluated individual behavioral reactions and wound-healing in common bottlenose dolphins (Tursiops truncatus) during a biopsy sampling program carried out in southern Brazil from 2003 to 2012, and compared sampling effectiveness between dedicated and opportunistic sampling surveys. Two hundred and fiftytwo biopsy attempts were made, resulting in 118 hits (48% of attempts) and 134 samples (52% of attempts) collected successfully. Responses to biopsy sampling were low-level, of short-term duration, and elicited similar reactions on the dolphins, irrespective of shot distance, sex of individuals, dolphins’ group size and pre-behavioral state. Dolphins subjected to multiple biopsy attempts reacted in a similar manner as in previous attempt(s), with no evidence of increasing the intensity of the reaction. Wounds could be monitored in 18 animals and healed over 18 to 35 days. Generally, wounds appeared to be covered by epidermis in about three weeks with no observed signs of skin infection. Our results agree with previous studies suggesting that biopsy sampling does not cause significant disturbance to the behavior of dolphins. At a local level, this study demonstrates that biopsy sampling of bottlenose dolphins in the Patos Lagoon Estuary is more effective, less costly and less intrusive when conducted opportunistically, but that long-term sampling is required to achieve a relatively good sample size from photoidentified individuals in the population.
Full-text available
The information herein presented were compiled from six scientific articles, one undergraduate monographs, four master and three doctoral thesis and six working papers presented during the “I South American Meeting of Research and Conservation of Tursiops truncatus”, which was held in Rio Grande, Rio Grande do Sul, Brazil between May 21-23, 2010. Some personal communications complement the information. Each topic discussed in the present report followed the geographical sub-divisions established in the Report of the Working Group on Distribution (this volume): a) Northern Brazil; b) North-eastern Brazil; c) South-eastern Brazil; d) Southern Brazil and Uruguay and e) Argentina.
We describe a model-based clustering method for using multilocus genotype data to infer population structure and assign individuals to populations. We assume a model in which there are K populations (where K may be unknown), each of which is characterized by a set of allele frequencies at each locus. Individuals in the sample are assigned (probabilistically) to populations, or jointly to two or more populations if their genotypes indicate that they are admixed. Our model does not assume a particular mutation process, and it can be applied to most of the commonly used genetic markers, provided that they are not closely linked. Applications of our method include demonstrating the presence of population structure, assigning individuals to populations, studying hybrid zones, and identifying migrants and admixed individuals. We show that the method can produce highly accurate assignments using modest numbers of loci—e.g., seven microsatellite loci in an example using genotype data from an endangered bird species. The software used for this article is available from
INTRODUCTION Marine mammals are a taxonomically diverse group of species with evolutionary roots right back to the earliest mammalian radiations. The smallest species is a mustelid, the sea otter (Enhydra lutris), and the largest the blue whale (Balaenoptera musculus). The only things marine mammals have in common are the facts that they are all mammals (and therefore dependent on breathing air and constrained by the necessities of live birth and maternal care), and they are all dependent on an aquatic, typically marine environment. These two common attributes have meant that they are constrained in similar ways, though the different groups have met these challenges in different ways. The mustelid, the carnivore (polar bear, Ursus maritimus) and the pinnipeds (seals, sea lions and walrus) all meet thermoregulatory challenges with dense pelage. Most of these also still give birth on land, and are to varying extents amphibious. The cetaceans (whales, dolphins and porpoises) and sirenians (manatees and dugongs) are fully aquatic, and have little or no pelage. Instead they have adjusted to the high thermal conductivity of water and the generally cold temperatures by developing thick layers of subcutaneous fat, and in many cases, by becoming large (which provides a high volume to surface area ratio and conserves heat). All of these species, with the exception of the polar bear, have adapted to more efficient locomotion in water by acquiring a relatively fusiform shape – most extensively developed in the delphinid cetaceans (the dolphins). In this chapter my focus will be on those features among the marine mammals that help to explain common patterns of population structure, or differences in these patterns among taxa. One feature shared by many is their high trophic position in the ecosystems they occupy. One exception is the sirenians, which are herbivorous. However, most marine mammals are predators, though their trophic position can vary dramatically (from baleen whales feeding on krill to killer whales feeding on other marine mammals). Another typical feature is large size.