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Supplementary information
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Genetic analyses
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Biopsy samples for genetic analyses were taken on an opportunistic basis, using a modified
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0.22 caliber rifle designed for biopsying small cetaceans [1]. Samples were stored in a freezer
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in saturated NaCl/20% dimethyl sulfoxide [2]. DNA was extracted using the Gentra Puregene
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Tissue Kit (Qiagen) and DNA concentrations adjusted to 20 ng/μl. Sex was determined
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genetically using sex chromosome-specific primers; loci ZFX and SRY [3] were coamplified
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in a single polymerase chain reaction (PCR). PCR products were run on a 1.5% agarose gel
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and sex was determined based on the different fragments amplified. Mitochondrial DNA
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(mtDNA) haplotypes were based on a 468 base pair (bp) sequence, amplified by the primers
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dlp1.5 and dlp5 [4]. The fragment contains part of the hypervariable region I and the proline
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transfer RNA gene. We followed the PCR conditions described in Bacher et al. [5]. The
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sequences were aligned in BioEdit [6] and haplotypes assigned by eye.
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We amplified 26 microsatellite loci in three multiplex PCRs. We amplified nineteen
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tetranucleotide and seven dinucleotide loci using the Qiagen Multiplex KitTM (Qiagen) in 10
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μl volumes. Multiplex 1 contained the following markers: E12, Tur4_66, Tur4_98, Tur4_105,
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Tur4_108, Tur4_111, Tur4_117, Tur4_128 [7], and MK6 [8]. The loci D8, F10, Tur4_87,
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Tur4_91, Tur4_138, Tur4_141 [7], and D22 [9] were amplified in multiplex 2. We
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multiplexed Tur4_80, Tur4_132, Tur4_142, Tur4_153, Tur4_162 [7], MK3, MK5, MK8,
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MK9 [8], and KWM12 [10] in multiplex 3. PCR conditions are described in Nater et al. [7].
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The single-stranded PCR products were run on an ABI 3730 DNA Sequencer (Applied
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Biosystems). Alleles were scored with Genemapper Software 4.0 (Applied Biosystems).
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Figure S1: Sponging kernel utilisation distribution. The black outline is the 95% kernel of all
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sponging sightings (indicated by stars) in the eastern (ESB) and western gulf (WSB) of Shark
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Bay. The red outline is the 95% kernel of all sponging sightings including a 4 km buffer. Dots
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represent DNA sampling locations of all dolphins sampled within the 95% sponging kernel
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plus the 4 km buffer zone and are colour coded by the mtDNA haplotype of sampled
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dolphins.
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Figure S2: STRUCTURE plots for k=2 (top) and k=3 (bottom) of WSB. E, F and H
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correspond to mtDNA haplotypes and “o” indicates other haplotypes. The analyses included
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108 individuals and 26 microsatellite loci.
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Individual-based model
Model description
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We used simulations to test the hypothesis that vertical social transmission of a habitat-
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dependent trait can lead to fine-scale genetic structure using an individual-based model based
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on empirical data [11]. In the model, an individual lived in one of two habitats (deep or
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shallow). Habitat preference was inherited from mother to offspring, as was the mtDNA
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haplotype. The three mtDNA haplotypes and two habitats of the 600 individuals of the start
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population were assigned with equal probability. We introduced two vertically socially
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transmitted habitat specialisations: sponging and another specialisation called strategy2. At
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the start of each simulation, five females with haplotype 1 were spongers and five females
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with haplotype 2 engaged in strategy2. Spongers only occurred in deep habitat whereas
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strategy2 only occured in shallow habitat. We ran the simulation with various learning
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fidelities (0.9, 0.95 and 1) and fitness benefits (-2.5, 0, 5, 7.5, 12.5 and 15%) for females with
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foraging specialisations in the respective habitats. However, most simulations were run with
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5% fitness benefits for specialists, although empirical data suggest that fitness advantages of
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spongers were close to 18% but non-significant [12]. After 1200 years (approximately 57
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generations [13]) and 100 iterations we noted whether we observed a segregation of mtDNA
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haplotypes and habitats. We ignored the segregation of the third haplotype (F) observed in
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WSB because its segregation is not as clear (although significant) as for mtDNA haplotype E
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and H.
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Simulations showed that fine-scale genetic structure based on mtDNA haplotypes can be
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driven by vertically socially transmitted, habitat-dependent traits (figure 3 in main text and S3
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below). We introduced two habitat-dependent specialisations into the simulation because
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there was a strong geographic segregation of haplotypes E and H in WSB. The specialisations
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were sponging in deep water and the alternative but unspecified behavioural “strategy2” in
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shallow water. Starting with equal mtDNA haplotype proportions in each habitat and five
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specialists per habitat sharing a specific mtDNA haplotype, mtDNA haplotype proportions of
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habitat specialists increased in the habitat to which they were specialised. The larger the
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fitness benefits for specialists in a given habitat, the faster the mtDNA haplotypes segregated
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between habitats (figure S3). The segregation of haplotypes occurred even if the learning
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fidelity was not 100% (figure S3). If only one habitat specialisation was present, the
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segregation of one mtDNA haplotype was observed (figure 3, second column). In explaining
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observed patterns of mtDNA haplotypes, it is important to note that in the absence of
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vertically, socially transmitted specialisations, no geographic segregation of mtDNA
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haplotypes was observed (figure 3, fourth column).
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Figure S3: Effect of learning fidelity and fitness benefits on geographic partitioning of
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matrilines: mtDNA haplotype segregation by habitat in an individual-based model. Three
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mtDNA haplotypes (Hap1, 2 and 3) and two habitat specialisations (sponging and strategy2)
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were present at the start of the simulation. All spongers had Hap1 and all strategy2 individuals
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Hap2. Top row: number of females per strategy (No IDs/strategy). Bottom row: proportion of
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individuals with a particular mtDNA haplotype in deep water relative to all individuals with
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this particular mtDNA haplotype. Proportions were calculated for every haplotype separately.
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Error bars represent one standard error. Dashed lines indicate the observed haplotype
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proportion in deep water for the three mtDNA haplotypes E, F and H in UL. Fitness benefits
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for specialists and learning fidelity of daughters born to specialists are shown below graphs.
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Because random cultural drift [14] is a strong force counteracting the establishment of new
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innovation we indicated the likelihood (%) of at least one specialist/strategy to persist for 100
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time periods; this is shown below the fitness benefits. Note that haplotypes also segregate
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when no fitness benefits are present for specialists (fourth column). However, this may be an
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artefact of the prerequisite of the simulation that at least one specialist is present in every time
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period, i.e. iterations with more specialists are selected.
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