Limited fine-scale larval dispersal of the threatened brooding corals Heliopora spp. as evidenced by population genetics and numerical simulation

Taninaka, Hiroki; Bernardo, Lawrence Patrick C.; Saito, Yuta; Nagai, Satoshi; Ueno, Mitsuhiro; Kitano, Yuko F.; Nakamura, Takashi; Yasuda, Nina

doi:10.1007/s10592-019-01228-7

Cited by 10 publications

(15 citation statements)

References 67 publications

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“…These migration rates are comparable to those found in brooding coral Helipora spp. in Sekisei Lagoon, which ranged from 0.4 to 20.2% (Taninaka et al 2019).…”

Section: Discussionmentioning

confidence: 99%

Genetic structure and diversity of the mustard hill coral Porites astreoides along the Florida Keys reef tract

et al. 2021

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Increases in local and global stressors have led to major declines in coral populations throughout the western Atlantic. While abundances of other species have declined, however, the relative abundance of the mustard hill coral, Porites astreoides, has increased. Porites astreoides is relatively resilient to some stressors, and because of its mixed reproductive strategies, its populations often recover quickly following disturbances. The ability for P. astreoides to continue as a potential “winner” in western Atlantic reefs relies on maintaining sufficient genetic variation within populations to support acclimatization and adaptation to current and future environmental change. Without high genetic diversity and gene flow within the population, it would have limited capacity for adaptation and the species’ competitive advantages could be short-lived. In this study, we determined the genetic relatedness of 37 P. astreoides colonies at four shallow reefs along the offshore Florida Keys Reef Tract (FKRT), a region particularly hard-hit by recent disturbances. Using previously designed microsatellite markers, we determined the genetic diversity and connectivity of individuals among and between sites. Our results suggest that the FKRT likely contains a single, well-mixed genetic population of P. astreoides, with high levels of gene flow and evidence for larval migration throughout the region. This suggests that regional populations of P. astreoides likely have a higher chance of maintaining resilience than many other western Atlantic species as they face current and future disturbances.

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“…These migration rates are comparable to those found in brooding coral Helipora spp. in Sekisei Lagoon, which ranged from 0.4 to 20.2% (Taninaka et al 2019).…”

Section: Discussionmentioning

confidence: 99%

Genetic structure and diversity of the mustard hill coral Porites astreoides along the Florida Keys reef tract

et al. 2021

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“…Heliopora coerulea is a brooding species whose internal fertilization occurs inside female polyps, and almost-competent larvae are released once a year during the summer (Babcock, 1990;Harii et al, 2002;. Consistent with the short dispersal duration (Harii et al, 2002), Harii and Kayanne (2003) used settlement tiles in Shiraho reef and directly demonstrated that H. coerulea larvae settle within a range of 350 m. Previous population genetic studies performed using microsatellite markers and numerical simulation analyses indicated that larval dispersal among different reef habitats is quite limited (Taninaka et al, 2019); however, one population genetic analysis study reported infrequent long-distance larval dispersal in multiple generations (Yasuda et al, 2014). Strong population genetic differentiation has been observed within a 20 m × 40 km area (Taninaka et al, 2019), indicating that H. coerulea may have a finer SGS even within a continuous large population.…”

Section: Introductionmentioning

confidence: 84%

Spatial Autocorrelation Analysis Using MIG-seq Data Indirectly Estimated the Gamete and Larval Dispersal Range of the Blue Coral, Heliopora coerulea, Within Reefs

Mokodongan¹,

Taninaka²,

Sara³

et al. 2021

Front. Mar. Sci.

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Spatial autocorrelation analysis is a well-established technique for detecting spatial structures and patterns in ecology. However, compared to inter-population genetic structure, much less studies examined spatial genetic structure (SGS) within a population by means of spatial autocorrelation analysis. More SGS analysis that compares the robustness of genome-wide single nucleotide polymorphisms (SNPs) and traditional population genetic markers in detecting SGS, and direct comparison between the estimated dispersal range based on SGS and the larval dispersal range of corals directly surveyed in the field would be important. In this study, we examined the SGS of a reef-building coral species, Heliopora coerulea, in two different reefs (Shiraho and Akaishi) using genome-wide SNPs derived from Multiplexed inter-simple sequence repeat (ISSR) genotyping by sequencing (MIG-seq) analysis and nine microsatellite loci for comparison. Microsatellite data failed to reveal significant spatial patterns when using the same number of samples as MIG-seq, whereas MIG-seq analysis revealed significant spatial autocorrelation patterns up to 750 m in both Shiraho and Akaishi reefs based on the maximum significant distance method. However, detailed spatial genetic analysis using fine-scale distance classes (25–200 m) found an x-intercept of 255–392 m in Shiraho and that of 258–330 m in Akaishi reef. The latter results agreed well with a previously reported direct field observation of larval dispersal, indicating that the larvae of H. coerulea settled within a 350 m range in Shiraho reef within one generation. Overall, our results empirically demonstrate that the x-intercept of the spatial correlogram agrees well with the larval dispersal distance that is most frequently found in field observations, and they would be useful for deciding effective conservation management units for maintenance and/or recovery within an ecological time scale.

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“…While several previous studies have reported good agreement between oceanographic models and genetic analysis and have provided robust and straightforward interpretations of larval dispersal occurring on an ecological timescale (e.g. Galindo et al 2006; White et al 2010; Sunday et al 2014; Taninaka et al 2019), only a few have discussed the usefulness of oceanographic modeling for identifying alternative hypotheses or provided additional insights into the causes of observed population genetic structure (Galindo et al 2010; Crandall et al 2014). By applying Markov chain simulation in the numerical simulation, we could also include the effect of migration over multiple generations, which is easier to compare with genetic results than a single generation simulation result in terms of time-scale.…”

Section: Discussionmentioning

confidence: 99%

“…Oceanographic simulation, on the other hand, can capture snapshots of larval dispersal, while even a sophisticated biophysical model cannot accurately simulate larval behavior, recruitment, and survival in the ocean (White et al, 2019). It is therefore important to integrate different methods to estimate larval dispersal (Marko and Hart, 2017), although few studies have attempted to do so (but see Schunter et al, 2011; Alberto et al, 2011; Nakabayashi et al, 2019; Taninaka et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

Integrated population genomic analysis and numerical simulation to estimate larval dispersal of Acanthaster cf. solaris between Ogasawara and other Japanese regions

Horoiwa

Nakamura

Yuasa

et al. 2021

Preprint

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The estimation of larval dispersal of marine species occurring on an ecological timescale is significant for conservation. In 2018, a semi-population outbreak of Acanthaster cf. solaris was observed on a relatively isolated oceanic island, Ogasawara. The aim of this study was to assess whether this population outbreak was caused by large-scale larval recruitment (termed secondary outbreak) from the Kuroshio region. We estimated larval dispersal of the coral predator A. cf. solaris between the Kuroshio and Ogasawara regions using both population genomic analysis and oceanographic dispersal simulation. Population genomic analysis revealed overall genetically homogenized patterns among Ogasawara and other Japanese populations, suggesting that the origin of the populations in the two regions is the same. In contrast, a simulation of 26-year oceanographic dispersal indicated that larvae are mostly self-seeded in Ogasawara populations and have difficulty reaching Ogasawara from the Kuroshio region within one generation. However, a connectivity matrix produced by the larval dispersal simulation assuming a Markov chain indicated gradual larval dispersal migration from the Kuroshio region to Ogasawara in a stepping-stone manner over multiple years. These results suggest that, while large-scale larval dispersal from an outbreak of the Kuroshio population spreading to the Ogasawara population within one generation is unlikely. This study also highlighted the importance of using both genomic and oceanographic methods to estimate larval dispersal, which provides significant insight into larval dispersal that occurs on ecological and evolutionary timescales.

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Limited fine-scale larval dispersal of the threatened brooding corals Heliopora spp. as evidenced by population genetics and numerical simulation

Cited by 10 publications

References 67 publications

Genetic structure and diversity of the mustard hill coral Porites astreoides along the Florida Keys reef tract

Genetic structure and diversity of the mustard hill coral Porites astreoides along the Florida Keys reef tract

Spatial Autocorrelation Analysis Using MIG-seq Data Indirectly Estimated the Gamete and Larval Dispersal Range of the Blue Coral, Heliopora coerulea, Within Reefs

Integrated population genomic analysis and numerical simulation to estimate larval dispersal of Acanthaster cf. solaris between Ogasawara and other Japanese regions

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