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Ocean currents help explain population genetic structure.

White C, Selkoe KA, Watson J, Siegel DA, Zacherl DC, Toonen RJ - Proc. Biol. Sci. (2010)

Bottom Line: Explanatory power was strongest when we considered effects of multiple generations of larval dispersal via intermediary locations on the long-term probability of exchange between sites.Our results uncover meaningful spatial patterning to population genetic structuring that corresponds with ocean circulation.This study advances our ability to interpret population structure from complex genetic data characteristic of high gene flow species, validates recent advances in oceanographic approaches for assessing larval dispersal and represents a novel approach to characterize population connectivity at small spatial scales germane to conservation and fisheries management.

View Article: PubMed Central - PubMed

Affiliation: Marine Science Institute, University of California, Santa Barbara, CA 93106, USA. crowsfeather@gmail.com

ABSTRACT
Management and conservation can be greatly informed by considering explicitly how environmental factors influence population genetic structure. Using simulated larval dispersal estimates based on ocean current observations, we demonstrate how explicit consideration of frequency of exchange of larvae among sites via ocean advection can fundamentally change the interpretation of empirical population genetic structuring as compared with conventional spatial genetic analyses. Both frequency of larval exchange and empirical genetic difference were uncorrelated with Euclidean distance between sites. When transformed into relative oceanographic distances and integrated into a genetic isolation-by-distance framework, however, the frequency of larval exchange explained nearly 50 per cent of the variance in empirical genetic differences among sites over scales of tens of kilometres. Explanatory power was strongest when we considered effects of multiple generations of larval dispersal via intermediary locations on the long-term probability of exchange between sites. Our results uncover meaningful spatial patterning to population genetic structuring that corresponds with ocean circulation. This study advances our ability to interpret population structure from complex genetic data characteristic of high gene flow species, validates recent advances in oceanographic approaches for assessing larval dispersal and represents a novel approach to characterize population connectivity at small spatial scales germane to conservation and fisheries management.

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(a,b) Mean probability of dispersal between genetic sampling sites, overlaying mean surface currents 15 June–15 October 1993–1999 (arrows, size correlates with velocity) in the Santa Barbara Channel. Line thickness correlates with probability. (a) Probability of dispersal over a single generation, M; (b) long-term probability of dispersal over multiple generations, Mss. (c,d) Genetic differentiation in relation to derived oceanographic distance between sites, based on (c) M (infinite pairwise distances excluded) and (d) Mss (all pairwise sites included). Red squares, islands; green triangles, mainland; blue diamonds, cross channel. See text and table 2 for regression statistics.
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RSPB20092214F2: (a,b) Mean probability of dispersal between genetic sampling sites, overlaying mean surface currents 15 June–15 October 1993–1999 (arrows, size correlates with velocity) in the Santa Barbara Channel. Line thickness correlates with probability. (a) Probability of dispersal over a single generation, M; (b) long-term probability of dispersal over multiple generations, Mss. (c,d) Genetic differentiation in relation to derived oceanographic distance between sites, based on (c) M (infinite pairwise distances excluded) and (d) Mss (all pairwise sites included). Red squares, islands; green triangles, mainland; blue diamonds, cross channel. See text and table 2 for regression statistics.

Mentions: In the original forward transition matrix (M, representing dispersal over a single generation), mean probabilities of dispersal among coastal grid units representing the 10 geo-referenced genetic sampling sites ranged from zero to 0.51 per cent (figure 2a). Using Siegel et al.'s dispersal kernel, we transformed the probabilities into DODs that ranged from ∞ − 47 km, respectively (figure 3). Infinite distances (i.e. site pairs with zero probability of dispersal, occurring between 24 of the 45 pairs) were excluded, and regression of DOD against pairwise genetic differences was not statistically significant (FST: R2 = 0.08, p = ∼1; Dest: R2 = 0.24, p = 0.49; figure 2c and electronic supplementary material, figure S3a).


Ocean currents help explain population genetic structure.

White C, Selkoe KA, Watson J, Siegel DA, Zacherl DC, Toonen RJ - Proc. Biol. Sci. (2010)

(a,b) Mean probability of dispersal between genetic sampling sites, overlaying mean surface currents 15 June–15 October 1993–1999 (arrows, size correlates with velocity) in the Santa Barbara Channel. Line thickness correlates with probability. (a) Probability of dispersal over a single generation, M; (b) long-term probability of dispersal over multiple generations, Mss. (c,d) Genetic differentiation in relation to derived oceanographic distance between sites, based on (c) M (infinite pairwise distances excluded) and (d) Mss (all pairwise sites included). Red squares, islands; green triangles, mainland; blue diamonds, cross channel. See text and table 2 for regression statistics.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2871860&req=5

RSPB20092214F2: (a,b) Mean probability of dispersal between genetic sampling sites, overlaying mean surface currents 15 June–15 October 1993–1999 (arrows, size correlates with velocity) in the Santa Barbara Channel. Line thickness correlates with probability. (a) Probability of dispersal over a single generation, M; (b) long-term probability of dispersal over multiple generations, Mss. (c,d) Genetic differentiation in relation to derived oceanographic distance between sites, based on (c) M (infinite pairwise distances excluded) and (d) Mss (all pairwise sites included). Red squares, islands; green triangles, mainland; blue diamonds, cross channel. See text and table 2 for regression statistics.
Mentions: In the original forward transition matrix (M, representing dispersal over a single generation), mean probabilities of dispersal among coastal grid units representing the 10 geo-referenced genetic sampling sites ranged from zero to 0.51 per cent (figure 2a). Using Siegel et al.'s dispersal kernel, we transformed the probabilities into DODs that ranged from ∞ − 47 km, respectively (figure 3). Infinite distances (i.e. site pairs with zero probability of dispersal, occurring between 24 of the 45 pairs) were excluded, and regression of DOD against pairwise genetic differences was not statistically significant (FST: R2 = 0.08, p = ∼1; Dest: R2 = 0.24, p = 0.49; figure 2c and electronic supplementary material, figure S3a).

Bottom Line: Explanatory power was strongest when we considered effects of multiple generations of larval dispersal via intermediary locations on the long-term probability of exchange between sites.Our results uncover meaningful spatial patterning to population genetic structuring that corresponds with ocean circulation.This study advances our ability to interpret population structure from complex genetic data characteristic of high gene flow species, validates recent advances in oceanographic approaches for assessing larval dispersal and represents a novel approach to characterize population connectivity at small spatial scales germane to conservation and fisheries management.

View Article: PubMed Central - PubMed

Affiliation: Marine Science Institute, University of California, Santa Barbara, CA 93106, USA. crowsfeather@gmail.com

ABSTRACT
Management and conservation can be greatly informed by considering explicitly how environmental factors influence population genetic structure. Using simulated larval dispersal estimates based on ocean current observations, we demonstrate how explicit consideration of frequency of exchange of larvae among sites via ocean advection can fundamentally change the interpretation of empirical population genetic structuring as compared with conventional spatial genetic analyses. Both frequency of larval exchange and empirical genetic difference were uncorrelated with Euclidean distance between sites. When transformed into relative oceanographic distances and integrated into a genetic isolation-by-distance framework, however, the frequency of larval exchange explained nearly 50 per cent of the variance in empirical genetic differences among sites over scales of tens of kilometres. Explanatory power was strongest when we considered effects of multiple generations of larval dispersal via intermediary locations on the long-term probability of exchange between sites. Our results uncover meaningful spatial patterning to population genetic structuring that corresponds with ocean circulation. This study advances our ability to interpret population structure from complex genetic data characteristic of high gene flow species, validates recent advances in oceanographic approaches for assessing larval dispersal and represents a novel approach to characterize population connectivity at small spatial scales germane to conservation and fisheries management.

Show MeSH
Related in: MedlinePlus