Fishing for population structure in North Pacific seals: challenges, pitfalls and

solutionsGreg O’Corry-Crowe, Peter Boveng, Gail Blundell, Lori Quakenbush,

Vladimir Burkanov, Robert Small

Harbor Branch Oceanographic Institute-Florida Atlantic UniversityNational Marine Fisheries Service

Alaska Department of Fish and Game

The analysis of population genetic structure traditionally consists of:

A) Testing explicit hypotheses, such as genetic differentiation between breeding groups

B) Inference about what genetic heterogeneity means in terms of historical relationships or the level of contemporary gene flow and dispersal among groups

This proven difficult in several North Pacific seal species

1. Continuously distributed, often with multiple breeding sites2. Highly mobile – make long-distance seasonal movements3. Long-lived – many opportunities for effective or actual dispersal4. Roles of site fidelity v.s. philopatry unclear5. Large historical population sizes – high genetic diversity, low rates of drift

The resolution of population structure in North Pacific seals is crucial for investigating evolutionary processes (local adaptation, gene flow) and is central to effective management (biodiversity, stock identity)

Under such conditions, sampling at the appropriate location, season and spatial scale is central to resolving population genetic structure and ultimately dispersal and breeding patterns

Large sample numbers from breeding sites, ideally pups, over multiple years

To date sampling has been predominantly:A. opportunistic, inc. harvestB. tied to field studies that often occur outside the breeding season, C. focused on sub-adult and adult seals

Determining the population of origin of such samples is central to management objectives but their utility in characterizing baseline populations is limited

Species: harbor sealSpotted sealBearded sealRinged sealRibbon seal V. Burkanov

K.J. Frost

Genetic markersmtDNA (430bp)

Microsatellites (n=10 -18)

Statistical Hypothesis testing – a priori stratificationχ2, Fst, Фst, Rst

Phylogeography – a priori stratificationphylogenetic reconstruction, e.g. MSN

Landscape Genetics – no a priori stratificationModel-based cluster analysis (Structure)Individual-based spatial analysis

kin-based analysis – no a priori stratificationthe spatial distribution of close kin

Big picture at range-wide scale v.s detailed picture at local scales

Spotted seal, Phoca largha

Po Hai Sea to Beaufort Sealarge population sizes N ~ 300,000pack ice breeders – triadsbreeding concentrations have been identifiedextensive movements

Population structure across species rangeStock structureInterbreeding with harbor seals

Sampling regime: opportunisticsystematic (satellite tagging)hunting (seasonal)

mtDNA (419bp) n=249Microsats (18 loci) n=207

Spotted Seal – Phoca largha

Sample numbers: 249

K. Frost

5

50

13

30

60

21

15

29

Spotted seal, Phoca largha

Mitochondrial DNA

High mtDNA diversity , 172 haplotypes/249 samples

large historical population sizes

Subdivision among the: Bering/Chukchi/Beaufort Seas Okhotsk Sea Sea of Japan Po Hai Sea

No subdivision observed within the Bering/Chukchi/Beaufort Sea

suggests extensive movement and dispersal

supported by satellite telemetry

microsatellites

Structure, K=2 the most likely,

corresponds to: (1) B-C-B and Okhotsk

(2) Sea of Japan and Po-Hai sea

Spotted seal, Phoca largha

However, sample size is small andsampling regime was not ideal

V. Burkanov

Harbor seal, Phoca vitulina

Large population sizes, N >180,000

Continuously distributed in shelf waters

Hundreds of terrestrial and glacial ice breeding sites

Majority of movements <50km, but also extensive movements (>500km)

Uneven population density across range

Differing trends across range

Johns Hopkins Inlet (JHI)Glacier Bay National Park

Courtesy: Jaimie Womble

Harbor seal, Phoca vitulina

Large population sizesContinuously distributed in shelf watersHundreds of breeding sitesExtensive movements

Sample size: n=1,388Sampling sites , n=128

Sampling was uneven, occurred across all seasons and involved primarily sub-adults and adults

Initial stratification challenging

Mitochondrial DNA

High haplotypic diversity342 unique haplotypesweak phylogeographic partitioninggeneral isolation-by-distance patternclear macro-geographic structure among major centers of abundance

Westlake and O’Corry-Crowe, 2002

Harbor seal population genetic structure – Statistical power

O’Corry-Crowe et al., 2003

Statistical power:

Low: 13 areasModerate: 6 areasHigh: 12

Harbor seal population genetic structure – mtDNA findings

O’Corry-Crowe et al., 2003

?

?

?

mtDNA differentiation on the scale of 150-540km

Limited female dispersal

Current stocks are too broadly defined

Harbor seal population genetic structure – microsatelites (10 loci)

O’Corry-Crowe et al., 2003

Statistical power:

Low: 8 areasHigh: 10

Harbor seal population genetic structure – microsatellites (10 loci)

O’Corry-Crowe et al., 2003

Microsatellite differentiation on scale of 300-700km

appears to be less nDNA differentiation than mtDNA

Greater male mediated gene flow

Harbor seal population genetic structure: Landscape genetics

Landscape Genetics approach: no assumptions are made about population boundaries beforehand.

model-based clustering (Structure): K=1 is the most likely

No evidence of > 1 distinct nuclear gene poolNo deep genetic breaks indicative of long-term isolation of gene pools

Harbor seal population genetic structure - kin distance

Individual-based analysis

kinship, relatedness, genetic mark-recapture

GIS

∑ (Py – P*)

∑ (Px – P*)R =

Kin distance

0.1

0.0

0.2

0.7

0.05

Dispersal distanceGenetic discontinuitiesContemporary structure

Queller & Goodnight (1989)

Harbor seal population genetic structure – Kin distance

452,929 pair-wise R estimates

Most comparisons had R<0.2

Highest R>0.7, potential 1st or 2nd order relatives>80% did not share mtDNA lineagepairs were sampled up to 9 years apartkin distance can exceed 500kmmultiple links were found among some locations

Findings still preliminary

Conclusions

Historical population sizes were large in most seal species, generating high levels of neutral genetic variation and resulting in slow rates of genetic divergence, such that genetic differences are small and difficult to detect

Sampling regimes to date have not been optimal. Concerted efforts must be made to design sampling protocols to the question being addressed: characterize population structure in North Pacific seal species. Specifically, sample large numbers of seals, preferably pups, on breeding grounds over multiple years

All the analyses are data hungry, requiring substantial sample sizes from multiple groups/areas

Recent common ancestry, asymmetric dispersal and changing population dynamics indicate that equilibrium-based methods may not be appropriate

New markers need to be investigated, including markers under selection which may require fewer samples to detect biologically relevant population subdivision

Funding for this research was provided by NOAA-NMFS, and ADF&G

Much of the earlier work was conducted by Robin Westlake-Storey

Thanks are due to all those, many anonymous, who wentto the trouble of collecting and sending us samples, including: M. Cameron, A. Trukhin, J. Cesarone, B. Robson, L. Dzinich, K. Frost, G. Jarrell, L. Jemison, G. Sheffield, M. Kookesh, J. Lewis, L. Lowry, R. Suydam, B. Mahoney, E. Mathews, R. Pavlik, K. Raum-Suryan, M. Riedel, D. Savareese, R. Small, U. Swain, M. Turek , V. Vanek, D. Withrow, and K. Wynne,

Invaluable lab assistance was provided by:R. Westlake-Storey, K. Raschen, L. Hansen, C. Reed, A. S. Costa, C. Lux, Aviva Rosenberg, Monica DeAngelis, Marc Basterretche, Carolina Bonin, Amy Frey and Vicki Pease

For helpful advice and additional support, thanks to:K. Brix, L. Lowry, K.Frost, J. Bengtson, M. Payne, A. Jensen, R. LeDuc, J Burns, M. Adkison, B. Kelly and D. DeMaster

Alaska Ice-Seal Committee

Define population strata to test difficult in continuously distributed speciesdifficult if samples are not from semi-discrete breeding areas

Defining strata in continuously distributed species tends to be subjective, especially if you have no control over sample collection

Many breeding groups may not be identified or sampled