University of Groningen

Assessing genetic structure of thornback ray, Raja clavataChevolot, Malia Sylvaine Claude Odette Maëlle

IMPORTANT NOTE: You are advised to consult the publisher's version (publisher's PDF) if you wish to cite fromit. Please check the document version below.

Document VersionPublisher's PDF, also known as Version of record

Publication date:2006

Link to publication in University of Groningen/UMCG research database

Citation for published version (APA):Chevolot, M. S. C. O. M. (2006). Assessing genetic structure of thornback ray, Raja clavata: A thornysituation?. s.n.

CopyrightOther than for strictly personal use, it is not permitted to download or to forward/distribute the text or part of it without the consent of theauthor(s) and/or copyright holder(s), unless the work is under an open content license (like Creative Commons).

Take-down policyIf you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediatelyand investigate your claim.

Downloaded from the University of Groningen/UMCG research database (Pure): http://www.rug.nl/research/portal. For technical reasons thenumber of authors shown on this cover page is limited to 10 maximum.

Download date: 26-06-2020

CHAPTER 1 General introduction In 1883, Thomas Huxley proclaimed that the cod and herring fisheries—and probably all of the great sea fisheries—were inexhaustible. Unfortunately, Huxley’s claim proved to be wrong. Less than a century later both fisheries collapsed and by 1997, 60 of the major world-fish resources were defined either as fully exploited or over-exploited, with no positive change since (FAO 2004; Hutchings & Reynolds 2004). The collapses of major commercial species has raised urgent concerns for fisheries management and sustainability, as well as for fundamental—and possibly irreversible—top-down effects on marine foodwebs and biodiversity.

Although less discussed, the loss and decline of non-target species are also an important issue for fisheries management and conservation. Skates and rays provide a good example of this category with a decline of 72% in the NE Atlantic over the past 30 years (Fig. 1). Elasmobranchs, like skates and rays, have low commercial value in comparison to teleosts and are regular victims of the commercial by-catch as well as recreational fisheries. Because reporting of species composition of the by-catch has historically either been lacking or insufficiently specific, it has been difficult to assess the magnitude of the declines on a species-specific basis (Ellis et al. 2005b). As a consequence, fisheries impact has typically gone unnoticed until populations crash (Crouse 1999), as for example, the disappearance of the common skate, Dipturus batis (formerly Raja batis) (Brander 1981) and the white skate, Rostroraja alba (Dulvy et al. 2000) in the Irish Sea.

The thornback ray, Raja clavata L. (Fig. 2) is a significant component of the by-catch in demersal mixed fisheries. However, it is also a locally targeted species in inshore long-line and gill-net fisheries along the British Isles. Among rays and skates it is the most commercially valuable species in Northern European waters. Stock estimates showed a decline of nearly 80% in the North Sea between 1951 and 1988 (Walker & Heessen 1996), 45% in the Irish Sea between 1988 and 1997 (Dulvy et al. 2000; Rogers & Ellis 2000) and 73% in French waters (FAO-Fishstat 2006) Their reduced abundance and distribution in the North Sea has led to concern about the sustainability of ray and skate populations in depleted areas along the Dutch coasts and North Sea proper (Walker & Heessen 1996). Since 1997, thornback ray stocks are considered to be outside of the safe biological limits in the North Sea (ICES 2005).

7

Chapter 1

Years1980 1985 1990 1995 2000 2005

Lan

ding

s in

tons

500

1000

1500

2000

2500

3000

3500

4000

Fig 3. Total landings of thornback rays in French waters only (FAO-Fishstat 2006).

Population genetic studies can provide important information for conservation of a species by helping to define conservation units on the basis of genetic stocks. The definitions of stocks are many (reviewed in Carvalho & Hauser 1994), but in generally agreed terms “stock” refers to “a group of organisms whose demographic/genetic trajectory is largely independent from other such groups” (Waples 1998). In genetic terms, the stock is equivalent to the population, i.e., a group of individuals of a sexually reproducing species within which mating take place randomly to form the panmictic unit. In ecological terms, the stock refers to a group of interacting organisms of the same species occupying a particular space at a particular time (Waples & Gaggiotti 2006).

The genetic/ecological stock concept is relevant because it provides a specific unit for both exploitation and management, whereas defining a stock a priori, based on geographical areas is seldom useful for most species and may lead to discrepancies between “biological stocks” and “management stocks”. For example, biological stocks may migrate seasonally from one area to another, resulting in a much larger geographical scale than the defined management units; or at the opposite extreme, several biological stocks may occur in one single management unit. Such a mismatch may lead to mismanagement including loss of genetic diversity leading to further decline of the stock (Pawson & Jennings 1996; Norse & Crowder 2005).

Identification of genetic stocks is usually assessed by the degree to which populations are connected, i.e., the extent to which populations in different parts of the species’ range are linked by exchange of larvae, recruits and adults (Palumbi

8

Introduction

2003). Indeed, population structure of a species and its strength depend on many interacting factors including life history (growth rate, maturity age, fecundity, mating behavior), demographic parameters (population size and its fluctuation, sex ratio) and genetic factors (genetic drift, selection, mutation, gene flow). Disentangling these many processes is not easy but has been greatly facilitated by the availability of highly polymorphic genetic markers and more powerful analysis methods. Thus, the means to assess genetic stock structure is increasingly robust.

As part of the NWO Prioriteit Programme “Sustainable Use of Marine Natural Resources” (1998-2008), Theme 1 addressed “the analysis of spatial scales over which populations of marine organisms interact and the possible mismatch with the scales of human exploitation systems.” Emphasis was placed on fisheries with a focus on the North Sea demersal mixed fishery which consists of flatfish, rays and skates. Two PhD projects were initiated—one on the European plaice (Pleuronectes platessa) (Hoarau 2004) and one on the thornback ray (Raja clavata) (this thesis). The general questions of interest were:

• What is the spatial scale and connectivity of genetically defined populations or stocks of the thornback ray (Raja clavata) in the North Sea/Northern Atlantic?

• How well do indirect estimates of dispersal and connectivity based on

genetic data correspond to direct estimates based on demographic tagging data?

• How well does life history type (characterized by low fecundity, no pelagic

larval stage and low dispersal) predict spatial structure as compared with the flatfish, European plaice, P. platessa (characterized by high fecundity, a pelagic larval stage and high dispersal)?

• What is the estimated effective population size (Ne)?

• Is there evidence for multiple paternity?

• What is the spatial scale of population genetic differentiation in another

Rajidae species, the thorny skate, Amblyraja radiata, and how similar is this scale to Raja clavata?

• What recommendations can be made to better inform fisheries management

about by-catch species such as skates and rays?

9

Chapter 1

Elasmobranchs Elasmobranchs (Figs. 4 and 5) belong to the Class Chondrichthyes (cartilaginous fishes) and are the oldest group of vertebrates with first fossil records dating from 350-400 million years BP (Capetta et al. 1993). They are also the oldest vertebrate group presenting internal fertilization and specialized male copulatory organs. Elasmobranchs (sharks, rays and skates) are characterized by slow growth, low fecundity and long life-spans. Interestingly, they show a high variability in reproductive mode—from oviparous to viviparous (Dulvy & Reynolds 1997), which has evolved several times independently.

Lamniformes (7 families, 16 species)

Pristiophoriformes(1 family, 5 species)

Squaliformes (4 families, 103 species) Heterodontiformes(1 family, 9 species)

Squatiniformes (1 family, 17 species)

Torpediniformes(2 families, 60 species)

Hexanchiformes (2 families, 5 species)

Pristiformes(1 family, 7 species)

Orectolobiformes(7 families, 33 species)

Raja clavata

Rajiformes (10 families, 485 species)Rays and skates

Carchariniformes (8 families, 230 species)

Lamniformes (7 families, 16 species)

Pristiophoriformes(1 family, 5 species)

Squaliformes (4 families, 103 species) Heterodontiformes(1 family, 9 species)

Squatiniformes (1 family, 17 species)

Torpediniformes(2 families, 60 species)

Hexanchiformes (2 families, 5 species)

Pristiformes(1 family, 7 species)

Orectolobiformes(7 families, 33 species)

Raja clavata

Rajiformes (10 families, 485 species)Rays and skates

Carchariniformes (8 families, 230 species)

Fig. 4. Diversity of elasmobranchs. Picture sources from FAO except Raja clavata from M. Chevolot

10

Introduction

Mammals

Reptiles

Amphibians

Lobe-finned fishes

Ray-finned fishes

Chondrichthyes

Agnathans

AcipenderLatimeria

HydrolagusCallorhinchus

PotamotrygonUrobatis

RhinobatosRaja

CentroscymnusCentroscyllium

DalatiasSqualus

DeaniaSquatina

ChlamydoselachusPristiophorus

HeterodontusTriakis

GaleocerdoApristurus

ScyliorhinusCarcharias

AlopiasMitsukurina

HemiscylliumOrectolobus

Bony Fish (teleost)

Chimeras

Batoids(Rajidae)

Squaliformes

Squatiniformes

Heterodontiformes

Carchariniformes

Lamniformes

Orectolobiformes

PlacentasMarsupials

MonotremesBirds

CrocodilesLizards and snakes

TuataraTurtles

Frogs

Teleosts

Salamenders

CaeciliansLungfishesCoelocanths

GarsBowfinsSturgeonsBichir

Lampreys

Sharks and skates

Chimaeras

Hagfishes

Mammals

Reptiles

Amphibians

Lobe-finned fishes

Ray-finned fishes

Chondrichthyes

Agnathans

AcipenderLatimeria

HydrolagusCallorhinchus

PotamotrygonUrobatis

RhinobatosRaja

CentroscymnusCentroscyllium

DalatiasSqualus

DeaniaSquatina

ChlamydoselachusPristiophorus

HeterodontusTriakis

GaleocerdoApristurus

ScyliorhinusCarcharias

AlopiasMitsukurina

HemiscylliumOrectolobus

Bony Fish (teleost)

Chimeras

Batoids(Rajidae)

Squaliformes

Squatiniformes

Heterodontiformes

Carchariniformes

Lamniformes

Orectolobiformes

PlacentasMarsupials

MonotremesBirds

CrocodilesLizards and snakes

TuataraTurtles

Frogs

Teleosts

Salamenders

CaeciliansLungfishesCoelocanths

GarsBowfinsSturgeonsBichir

Lampreys

Sharks and skates

Chimaeras

Hagfishes

Fig. 5. Phylogeny a) of vertebrates based on morphological, paleontological and molecular data (from Meyer & Zardoya 2003) and b) of Chondrichthyes based on the large and small subunits of the rDNA (Maximum Likelihood tree from Winchell et al. 2004).

The Rajidae (Fig. 5) is one of the most diverse families with >220 described species. Strictly speaking, species from this family are referred as skates, whereas species belonging to the Myliobatidae are rays. However, in European waters, short-nosed rajid species are colloquially referred to as rays and long-nosed species as skates (Dulvy et al. 2000). This extends to the common names. We use the terms interchangeably in the context of formal or informal taxonomic designation.

Rajid fossils date from the Late Cretaceous (ca 97 Mya) and indicate a rapid radiation (McEachran & Dunn 1998) with some 220 extant taxa described. Taxonomic identification based on morphological characters remains problematic because of the relatively few morphological characters available combined with morphological conservatism among species (Stehmann & Bürkel 1994; McEachran & Dunn 1998; Tinti et al. 2003). Phylogenetic studies based on morphological characters (165 species worldwide) were able to resolve relationships at the subfamily level but not at the species level (McEachran & Dunn 1998; Valsecchi et al. 2005). Furthermore, the taxonomic status for some lineages remains unclear (Lloris et al. 1991; Stehmann & Bürkel 1994) and taxonomic sampling is generally poor and biased towards temperate species. Only one molecular phylogeny (15 species, Atlantic and Mediterranean) has been published based on the 16S rDNA and the mtDNA control region (Valsecchi et al. 2005). The consequences of such limited knowledge is that misidentifications are common and reliable estimates of particular species stocks are, therefore, open to question.

11

Chapter 1

Thornback ray (Raja clavata ) The thornback ray, Raja clavata belongs to the Rajidae and is widely distributed in the eastern Atlantic from the Faroe Islands to Mauritania, including adjacent waters, the Mediterranean and Black Seas (Fig. 6a). It has also been reported along the Atlantic and Indian coasts of southern Africa (Stehmann & Bürkel 1994), although the taxonomic status in these waters is unclear (Fig. 6a).

Around the British Isles, thornback rays are most abundant in coastal waters and large bays, including the Wash, Outer Thames Estuary, Solent, Carmarthen Bay, Cardigan Bay, Liverpool Bay and Solway Firth (Fig. 6b, Ellis et al. 2005a). The abundance of this species is strongly correlated with depth, seabed sediment type, prey availability and suitable egg-laying substrata (Martin et al. 2005). Thornback rays are mostly nocturnal predators, feeding mostly on crustaceans and small fishes. Studied of stomach contents of thornback rays and of skates, in genera,l do not reflect any prey preference, but the availability and abundance of prey (Ajayi 1982; Daan et al. 1993). The ecological role of thornback rays in the ecosystem has not been yet really evaluated.

North Sea

English Channel

Irish Sea

Celtic Sea

Ireland

Britain

France

Netherlands

Brittany

Wash

OTECB

LB

SF

SO Belgium

North Sea

English Channel

Irish Sea

Celtic Sea

Ireland

Britain

France

Netherlands

Brittany

Wash

OTECB

LB

SF

SO Belgium

a)

b)North Sea

English Channel

Irish Sea

Celtic Sea

Ireland

Britain

France

Netherlands

Brittany

Wash

OTECB

LB

SF

SO Belgium

North Sea

English Channel

Irish Sea

Celtic Sea

Ireland

Britain

France

Netherlands

Brittany

Wash

OTECB

LB

SF

SO Belgium

a)

b)

Fig. 6. Distribution of Raja clavata. (a) Overall distribution, (b) UK waters. OTE=Outer Thames Estuary, SO=Solent, CB=Carmarthen Bay, LB=Liverpool Bay, SF=Solway Firth) (Ellis et al. 2005). The taxonomic status of thornback rays in Namibia and South Africa is uncertain (See Text).

12

Introduction

Raja clavata is an oviparous species with internal fertilization in which females mature at between 9 and 12 years of age (Nottage & Perkins 1983). Little is known about actual courtship/mating behavior in R. clavata. Following mating in early spring, the eggs are deposited on the seabed as egg cases, with pairs of eggs laid on alternate days over a period of several weeks from February to September (Holden 1975; Koop 2005). The fecundity rate per female is low, estimated at between 48-150 eggs/year (Holden 1975; Ryland & Ajayi 1984; Ellis & Shackley 1995). After 4-5 months incubation, fully formed rays (10-13 cm) hatch (Ellis & Shackley 1995) (Fig. 7).

Laying season: February to September (but egg-cases can be found all year)

MaleFemale

9-12 years

4-5 months later

Mating season in early spring, probably in shallow water

Laying season: February to September (but egg-cases can be found all year)

MaleFemale

9-12 years

4-5 months later

Mating season in early spring, probably in shallow water

Fig. 7. Life cycle of Raja clavata.

Migration of R. clavata has been followed in two tagging studies conducted in the Thames Estuary. Classic mark-and-recapture data have shown that juveniles tend to remain in deeper waters (10-30 m deep) for several years, whereas adults show seasonal movements, from deeper waters (10 to 30 m) in winter, to shallower waters (<10 m) in the spring, where they are presumed to mate and spawn (Walker et al. 1997). “Home range” has been estimated to be rather small, as recaptured individuals were mostly found close to their release point, with 80% remaining

13

Chapter 1

within 75 km (Walker et al. 1997). A second study using Data Storage Tags (DSTs) showed that the seasonal movement could be extended to juveniles (between 30 and 60 cm in length) and further indicated that most individuals were philopatric, returning to the same area every season (Hunter et al. 2005a; Hunter et al. 2005b). The DST study extended the “home range” to a maximum traveling distance of 130 km. Migrations between the southern North Sea and the English Channel, as well as between the English and French coasts of the English Channel, have also been thought to be rare. Walker et al. (1997) hypothesized that this separation was probably due to the deeper waters and strong currents in the Dover Strait. Altogether, tagging studies have suggested that R. clavata may have a restricted range and potentially strong, localized population differentiation. If this is so, then replenishment of locally depleted stocks from neighboring populations could be minimal in which case, vulnerability may increase. Thorny skate (Amblyraja radiata) The thorny skate (Fig. 8) is a widely distributed species in the North Atlantic from Hudson Bay to South Carolina, USA in the west, Greenland, Iceland and Spitzbergen in the north, and from Norway to the southern North Sea (including the western Baltic) in the east (Stehmann & Bürkel 1994). Thorny skates live in shallow coastal waters but extend their habitat to a depth of 1000 m. Their biological characteristics are similar to thornback rays. They mature at 5 to 6 years (Walker 1998; Sulikowski et al. 2005) and are oviparous, producing 20–80 eggs per female each year. Fully formed skates hatch after several months (ca. 8-11 cm disc width). The species seems to be reproductively active all year round in areas where the reproductive biology has been studied (i.e. in the Gulf of Maine: Sulikowski et al. 2005, North Sea: Walker 1998). Tagging studies of thorny skates in UK waters have shown that 85% of the individuals remained within a 110 km area (Walker et al. 1997; Heessen 2004). These observations combined with the life history traits suggest that, like for R. clavata, population genetic differentiation may be relatively strong. An assessment of population genetic structure over its range as compared with R. clavata, is of interest to management and conservation, but also to know how well life history traits can predict the degree of population structure in Rajidae. It is also of interest in the broader phylogeographic and demographic context of historical population growth.

14

Introduction

Fig. 8. Amblyraja radiata. Picture M. Chevolot.

Conservation status The World Conservation Union1 (IUCN) was created in 1956 to evaluate species’ status using five criteria (Table 1). Species are categorized as critically endangered, endangered or vulnerable. Among vertebrates, ca 40% of the described species have been evaluated. Fishes are poorly represented with only 2,914 evaluated among 29,300 described (ca 10%). Among the 2,914 evaluated fishes, 1,173 species (40%) are considered threatened, i.e., critically endangered, endangered or vulnerable. Among the elasmobranchs, 529 of 958 species (55%) were evaluated, for which 129 species are considered to be threatened (IUCN/SSC 2004). The thornback ray is listed as “nearly threatened”, which means it is close to be qualified as vulnerable and needs to be closely surveyed; and the thorny skate has not been yet evaluated.

The IUCN has also acknowledged the need to prevent loss of genetic diversity in order to maintain the evolutionary potential of a species and its adaptability to changing environments. Thus, genetic diversity has become an important component in conservation and management programs. Studying population genetics provides quantitative data for evaluating the risk of losing genetic diversity, assessment and change in effective population size, evaluating the possibility of replenishment of depleted areas from sister areas, and the scale of genetic connectivity.

1 The use of the name “World Conservation Union” began in 1990, but the full name and the acronym are often used together as many people still know the Union as IUCN (International Union for the Conservation of Nature and Natural Resources).

15

Chapter 1

Table 1. IUCN criteria for critically endangered, endangered and vulnerable species. Criteria Critically endangered

(CR) Endangered

(EN) Vulnerable

(VU) A1- Observed, estimated. inferred or suspected reduction in population size over the past 10 years or three generations of at least: A2- Population size reduction within 10 next years or 3 generations, projected or suspected to be at least of:

80% 80%

50% 50%

20% 20%

B- Extent of occurrence or area of occupancy estimated to be less of and estimates indicating any two of the following:

100 km2

10 km2

Severely fragmented or known to exist at only one location. Continuing decline, and extreme fluctuations

5000 km2

500 km2

Severely fragmented or known to exist at not more than five locations. Continuing decline and extreme fluctuations

20000 km2

2000 km2

Known to exist at no more than 10 locations. Continuing decline and extreme fluctuations

C- <250 mature individuals and estimated continuing decline of at least 25% within 3 years or one generation, or continuing decline in number and population structure (severely fragmented or all individuals in a single population)

<2500 mature individuals and estimated continuing decline of at least 20% within 5 years or 2 generations continuing decline in number and population structure (severely fragmented or all individuals in a single population)

<10000 mature individuals and estimated continuing decline of at least 10% within 10 years or 3 generations continuing decline in number and population structure (severely fragmented or all individuals in a single population)

D- Population estimated number of mature individuals

<50 <250 <1000 or population characterized be an acute restriction in its area of occupancy or in the number of locations

E- Probability of extinction within 10 years or three generations

>50% >20% within 20 years or 5 generations

10% within 100 years

Population genetic studies in marine fish General features The genetic component of population structure is determined by the interplay of four evolutionary forces: gene flow, genetic drift, selection and mutation. Using neutral

16

Introduction

markers, only gene flow and drift are considered important. Gene flow will tend to homogenize genetic variation among populations, whereas genetic drift will increase the genetic differentiation between populations. Because most marine fish have a large potential for dispersal including a passive larval phase and active swimming of adults, and very large populations, gene flow is expected to be high and the effects of genetic drift low. Thus, the predicted result is weak population differentiation. Early allozyme studies involving few, not-very-polymorphic loci gave credence to this view. Ward et al. (1994) reviewed FST estimates (a measure of population differentiation ranging from 0 to 1) for >100 fish species. The mean for marine species was only 0.062 as compared with 0.108 for anadromous species like salmon and 0.222 for freshwater species. Waples (1998) went a step further with the review of marine species, concluding that the median FST for marine species is probably closer to 0.02 (based on either allozyme or microsatellite data; slightly higher for mtDNA data). With the development of highly polymorphic microsatellite loci a decade ago, estimates of <0.001 are now detectable and statistically significant. However, such low values call into question what the biological significance (if any) may be for extremely low genetic differentiation (discussed by Waples 1998; Waples & Gaggiotti 2006). Leaving this discussion aside, virtually all modern surveys show that most marine fish populations are significantly differentiated. However, genetic homogeneity can still remain over a large geographical scale (e.g. Hoarau et al. 2002b; Zatcoff et al. 2004). Depth (including continental margins), isolation by distance and classical biogeographical barriers are often described as the main barriers to gene flow (Hoarau et al. 2002b; Reid et al. 2005). However, in some species, strong currents, larval retention areas and/or salinity/temperature gradients play an important role in the pattern of genetic structure such as for example in European sea bass (Bahri-Sfar et al. 2000), herring (Jørgensen et al. 2005) and North Sea cod (Hutchinson et al. 2001). In Elasmobranchs Because elasmobranchs have different life-history traits than teleosts (i.e., internal fertilization, no pelagic larval phase, smaller census population size, and potential for strong philopatry), population genetic differentiation is expected to occur at a smaller scale and be mostly driven by behavior rather than physical geographical barriers. Very few genetic studies are available for this group and all surveys have almost exclusively involved sharks (Table 2). At the oceanic scale, in the great white shark, Charcharidon carcharias, Pardini et al. (2001) found differentiation only between South African and Australian locations using the mtDNA control region but no differentiation using microsatellite loci, suggesting male-biased dispersal. In the sandbar shark, Carcharinus plumbeus, Heist & Gold (1999) found no differentiation (three microsatellite loci) in population structure between the mid-Atlantic Bight and the western Gulf of Mexico; this was also the case in the Atlantic sharp nose shark, Rhizoprionodon terranovae, with mtDNA RFLP (Heist et al. 1996a). In the short fin, mako shark, Isurus oxyrinchus, using mtDNA RFLP markers, genetic differentiation

17

Chapter 1

was only found between North Atlantic and all other oceans (Heist et al. 1996b). However, a more recent study using the same mtDNA RFLPs and four microsatellite loci showed genetic differentiation between the South Atlantic and Pacific and higher levels of genetic differentiation with mtDNA than with microsatellite also suggesting a male-biased dispersal (Schrey & Heist 2003). In the scalloped hammerhead shark, Sphyrna lewini, strong genetic differentiation was found between oceans and less along continental margins using a mtDNA marker. The authors suggested that nurseries along contiguous continental margins facilitated high gene flow between them but have restricted gene flow between oceans (Duncan et al. 2006). In the grey nurse shark, Charcharias taurus, high genetic differentiation was found between South Africa, Western Australia and Eastern Australia (Stow et al. 2006). Finally, no genetic differentiation among ocean basins and low genetic diversity was found in the basking shark, Cetorinus maximus, using a mtDNA marker (Rus Hoelzel et al. 2006).

In more regional-scale studies, in which differentiation was found, it has mostly been interpreted in relation to philopatric behavior. In the lemon shark, Negaprion brevirostris, Feldheim et al. (2001) found weak but significant population structure (four microsatellite loci) in the western Atlantic Ocean. Keeney et al. (2005) also found weak but significant population structure (eight microsatellite loci and control region of the mtDNA) in the blacktip shark, Carcharinus limbatus, between nine nursery areas in the northwestern and Caribbean Sea. Gardner & Ward (1998) found significant differentiation among several Australian locations in the Australian gummy shark, Mustelus antarticus (28 allozyme loci and mtDNA RFLP). In the Pacific angel shark, Squatina californica, genetic differentiation was found between the southern and northern California Channel Islands using 25 allozyme loci (Gaida 1997) and in the shovel nose guitar shark, Rhinobatos productus, a rajiform species, genetic differentiation was found between Baja de California and the Pacific coast using mtDNA control region RFLP (Sandoval-Castillo et al. 2004).

Prior to this thesis, only one population structure study on a Rajidae could be found in the literature. Blake (1976) studied thornback rays (Raja clavata) in the Irish Sea using a single eye-lens protein locus and found no differentiation.

18

Introduction

Ref

eren

ces

Stow

et a

l. (2

006)

Kee

ney

et a

l. (2

005)

Hei

st &

Gol

d (1

999)

Pard

ini e

t al.

(200

1)

Rus

Hoe

lzel

et a

l. (2

006)

Hei

st e

t al.

(199

6b)

Schr

ey &

Hei

st

(200

3)

Gar

dner

& W

ard

(199

8)

Feld

heim

et a

l. (2

001)

Bla

ke (1

976)

Sand

oval

-Cas

tillo

et

al.

(200

4)

Hei

st e

t al.

(199

6a)

Gai

da (1

997)

Dun

can

et a

l. (2

006)

Res

ults

Stro

ng g

enet

ic d

iffer

entia

tion

betw

een

the

thre

e lo

catio

ns

Sign

ifica

nt d

iffer

entia

tion

betw

een

all 9

nu

rser

ies.

Mal

e bi

ased

dis

pers

al.

No

diff

eren

tiatio

n

Gen

etic

diff

eren

tiatio

n be

twee

n So

uth

Afr

ica

and

the

two

othe

r loc

atio

ns w

ith m

tDN

A m

arke

r and

no

diff

eren

tiatio

n w

ith n

ucle

ar m

arke

rs. M

ale

bias

ed d

ispe

rsal

.

No

gene

tic d

iffer

entia

tion.

Gen

etic

diff

eren

tiatio

n be

twee

n N

orth

Atla

ntic

an

d al

l oth

er lo

catio

ns.

Gen

etic

diff

eren

tiatio

n be

twee

n N

orth

Atla

ntic

an

d N

orth

Pac

ific

with

nuc

lear

mar

kers

. Gen

etic

di

ffer

entia

tion

betw

een

Sout

h A

tlant

ic a

nd

Paci

fic a

nd b

etw

een

Nor

th A

tlant

ic a

nd a

ll ot

her

loca

tions

with

mtD

NA

. Pos

sibl

e m

ale-

bias

ed

disp

ersa

l.

Gen

etic

diff

eren

tiatio

n be

twee

n So

uth

and

Nor

ther

n N

ew W

ales

and

som

e ev

iden

ce a

lso

of

gene

tic d

iffer

entia

tion

of T

owns

ville

Sign

ifica

nt d

iffer

entia

tion

betw

een

all l

ocat

ions

ex

cept

bet

wee

n G

ulliv

an B

ay a

nd M

arqu

esas

K

ey.

No

gene

tic d

iffer

entia

tion.

Gen

etic

diff

eren

tiatio

n be

twee

n th

e tw

o lo

catio

ns.

No

gene

tic d

iffer

entia

tion.

Gen

etic

diff

eren

tiatio

n be

twee

n N

orth

ern

and

Sout

hern

Isla

nds.

Dee

p w

ater

may

act

as p

hysi

cal

barr

ier t

o ge

ne fl

ow.

Hig

h ge

netic

diff

eren

tiatio

n am

ong

ocea

ns a

nd

high

gen

e flo

w b

etw

een

nurs

erie

s alo

ng

cont

inen

tal m

argi

ns.

Loca

tions

One

loca

tion

in S

outh

Afr

ica,

one

in w

este

rn

Aus

tralia

and

one

in e

aste

rn A

ustra

lia

9 nu

rser

y ar

eas i

n th

e C

arib

bean

Sea

s, G

ulf o

f M

exic

o an

d N

orth

wes

tern

Atla

ntic

One

loca

tion

in th

e m

id-A

tlant

ic b

ight

and

two

in

the

wes

tern

Gul

f of M

exic

o

Sout

h A

fric

a, N

ew Z

eala

nd a

nd A

ustra

lia

New

Zea

land

, Tai

wan

, Nor

way

, Sco

tland

, W

este

rn N

orth

Atla

ntic

, Med

iterr

anea

n Se

a,

Car

ibbe

an S

ea, S

outh

Afr

ica

Two

loca

tions

in th

e N

orth

Atla

ntic

, one

in th

e So

uth

Atla

ntic

, One

in th

e N

orth

and

one

in th

e So

uth

Paci

fic

Sam

e th

an fo

r Hei

st e

t al.

(199

6a) p

lus o

ne

loca

tion

in th

e N

orth

Atla

ntic

, one

in th

e N

orth

Pa

cific

, and

two

on S

outh

Afr

ica

coas

ts

5 lo

catio

ns a

roun

d A

ustra

lia

Four

loca

tions

, one

in G

ulliv

an B

ay a

nd

Mar

ques

as k

ey in

Flo

rida,

Bim

ini I

slan

ds

(Bah

amas

) and

Ato

s das

Roc

as (B

razi

l)

Gul

f of C

alifo

rnia

and

Pac

ific

coas

t of B

aja

Cal

iforn

ia

Two

loca

tions

: one

in G

ulf o

f Mex

ico

and

one

on

the

sout

heas

tern

coa

st o

f the

USA

3 lo

catio

ns in

the

Cal

iforn

ian

Cha

nnel

Isla

nds:

Sa

nta

Cru

z, S

anta

Ros

a Is

land

s and

San

ta

Cle

men

te Is

land

15 lo

catio

ns: 6

loca

tions

in th

e Pa

cific

Oce

ans,

4 lo

catio

ns in

the

Indi

an O

cean

, 5 lo

catio

ns in

the

Atla

ntic

.

Gen

etic

di

ffer

entia

tion

F ST

(AFL

P)=0

.295

ΦST

(mito

)=0.

35

ΦST

(msa

t)=0.

007

ΦST

=0.0

02

R ST=

0.00

03

F ST(

mito

)=0.

86

No

info

rmat

ion

for m

icro

sate

llite

No

info

rmat

ion

θ=0.

14

θ (m

sat)=

0.00

14

R ST=

0.00

29

θ (m

ito)=

0.14

8

No

info

rmat

ion

θ=0.

016

No

info

rmat

ion

ΦST

=0.6

3

No

info

rmat

ion

θ=0.

082

ΦST

=0.7

49 (a

ll)

ΦST

=0.5

19 a

mon

g

ocea

ns

Mol

ecul

ar m

arke

r use

d

235

AFL

Ps a

nd m

tDN

A c

ontro

l re

gion

mtD

NA

con

trol r

egio

n an

d 8

mic

rosa

tellt

e lo

ci

3 m

icro

sate

llite

loci

mtD

NA

con

trol r

egio

n an

d 5

min

isat

ellte

loci

mtD

NA

con

trol r

egio

n

mtD

NA

RFL

P

4 m

icro

sate

llite

loci

and

mtD

NA

R

FLP

from

Hei

st e

t al.

(199

6a)

28 a

llozy

me

loci

and

mtD

NA

R

FLP

4 m

icro

sate

llite

loci

One

allo

zym

e lo

cus

mtD

NA

con

trol r

egio

n R

FLP

mtD

NA

RFL

P

25 a

llozy

me

loci

mtD

NA

con

trol r

egio

n (5

48 b

p)

Tabl

e 2

Sum

mar

y of

pre

viou

s pop

ulat

ion

gene

tic st

ruct

ure

on e

lasm

obra

nchs

Spec

ies

Car

char

ias t

auru

s (G

rey

nurs

e sh

ark)

Car

char

inus

lim

batu

s (B

lack

tip sh

ark)

Car

char

inus

plu

mbe

us

(San

dbar

shar

k)

Car

char

odon

car

char

ias

(Gre

at w

hite

shar

k)

Cet

orin

us m

axim

us

(Bas

king

shar

k)

Isur

us o

xyri

nchu

s (S

horf

in m

ako)

Isur

us o

xyri

nchu

s (S

horf

in m

ako)

Mus

telu

s ant

artic

us

(Aus

tralia

n gu

mm

y sh

ark)

Neg

apri

on b

revi

rost

ris

(Lem

on sh

ark)

Raja

cla

vata

(Tho

rnba

ck ra

y)

Rhin

obat

os p

rodu

ctus

(S

hove

lnos

e gu

itarf

ish)

Rhiz

opri

onod

on te

rrae

nova

e (A

tlant

ic sh

arpn

ose

shar

k)

Squa

tina

calif

orni

ca

(Pac

ific

ange

lsha

rk)

Sphy

rna

lew

ini

(Sca

llope

d ha

mm

erhe

ad

shar

k)

19

Chapter 1

Census and effective population size Census population size (N) refers to the estimated number of adult individuals in a population whereas effective population size (Ne) refers to those individuals that actually contribute to the next generation. In the ideal case the two would be equivalent under an assumption of equal sex ratio, equal reproductive success among individuals and constant population size. In reality, the effective population size is several times smaller than the census population size due to any deviations from the ideal population model (Box 1: factors affecting Ne). Frankham (1995) reviewed 192 published estimates of Ne (based on demographic data) from 102 species (amphibians, mollusks, birds, mammals, insects, reptiles and plants) and concluded that Ne/N ratio is, on average, 1/9 or about 11% (Frankham 1995). For these reasons, Ne is considered to be a better estimator of the genetic property of a population than N and is an important parameter for conservation.

In bony fishes (Table 3), Ne/N ratio is estimated to be much smaller, i.e., up to several orders of magnitude smaller from 10-3 to 10-6 (Turner et al. 2002; Hauser et al. 2002; Hutchinson et al. 2003; Hoarau et al. 2005; Poulsen et al. 2006). Estimates of Ne, in these cases were based on temporal sampling methods (Box 2: estimating Ne). These results illustrate that even species with very large census population sizes are actually quite dependent on a small number of individuals and illustrate clearly the need to estimate Ne for conservation.

Table 3. Census and effective population sizes estimated for marine bony fishes. Species N Ne Ne/N ratio New Zealand red snapper (Hauser et al. 2002)

Pagrus auratus 3.3*106 180 1.8-2.8*10-5

North Sea Cod (1960-1970) (Hutchinson et al. 2003)

Gadus morhua 3.1*106

121 3.9*10-5

European plaice (Hoarau 2004)

Pleuronectes platessa ~108 (Iceland) ~109 (North Sea)

1733 (Iceland) 19,535 (North Sea)

2*10-5

Red drum (Turner et al. 2002)

Scianops ocellatus 3.4*106 ~3,000 10-3

North Sea and Baltic Cod (Poulsen et al. 2006)

Gadus morhua No information 1500 (BalticSea) >10,000 (North Sea)

~10-5

20

Introduction

BOX 1: Parameters influencing the effective population size, Ne

- Fluctuations in population size Population size of a species may fluctuate through time as a consequence of resource availability, a variable environment or a catastrophe. In this case:

)(1/∑=iee NtN ,

with i the effective population size at the ieN th generation and t the number of generations.

Thus, if the population goes through a severe reduction in population size (a bottleneck), the actual effective population size will be reduced in comparison to N.

- Variation in reproductive success In stable populations, the mean number of offspring is k=2 to replace both parents. If we consider only the effect of variance in reproductive success then:

)2/()24( +−= ke VNN ,

with Vk the variance in reproductive success. Thus, the higher the variance in reproductive success, the lower the Ne.

- Unequal sex ratio

)/(4 emefemefe NNNNN +=

with Nef the effective number of breeding females and Nem of breeding males. Thus, the more deviation there is from the 1:1 sex-ratio, the lower the Ne is in comparison to N.

- Inbreeding

)1/( FNNe += ,

with F being the inbreeding coefficient. Thus, the more inbred the population is, the smaller the Ne is.

- Overlapping generations Based on simulation studies, the effect of overlapping generations on the Ne remains unclear but suggests a slight lowering (Lande & Barrowclough 1987; Frankham et al. 2002). Frankham (1995) showed that fluctuations in population size are the major cause of reduced Ne, followed by variation in reproductive success and unequal sex-ratio.

21

Chapter 1

BOX 2: Estimating Ne The effective population size, Ne, is affected by demographic parameters such as growth, sex ratio, mating system (Caballero 1994), which are difficult to directly estimate in natural populations. Ne can be indirectly estimated by assessing the change in allelic frequencies through time based solely on genetic drift, assuming no selection, no mutation and no migration. The temporal approach of estimating the harmonic mean of Ne over a time-period uses a maximum likelihood approach (Waples 1989; Wang 2001; Wang & Whitlock 2003; Wang 2005). The object is to find the estimated Ne that will best fit the temporal change in allelic frequencies in a model where genetic drift is the only evolutionary force (Anderson et al. 2000; Wang 2001; Berthier et al. 2002)

Causes of the small Ne/N ratio in marine bony fishes have mainly been attributed to high variance in reproductive success (Box 1). This is based on the fact that most marine fish are characterized by a type III survivorship (i.e., high fecundity and high juvenile mortality) and the observation that “sweepstakes” recruitment (Hedgecock 1994) may be common (Larson & Julian 1999; Planes & Lenfant 2002; McPherson et al. 2003; Pujolar et al. 2006); a situation arising when young-of-the-year might come from a very small number of successful breeders as a consequence of matched breeding time and local oceanographic conditions. This kind of recruitment promotes huge variance in reproductive success among breeders (Hedrick 2005).

Rajidae are not characterized by a type III survivorship. On the contrary, they have low fecundity, high juvenile survival (Daan et al. 1990; Dulvy et al. 2000; Dulvy & Reynolds 2002; Keeney et al. 2005) and an equal sex ratio at birth (Ryland & Ajayi 1984; Ellis & Shackley 1995; Heessen 2004). Egg and juvenile mortality is apparently low as evidenced by a 73% hatching of laid eggs (Ellis & Shackley 1995). The mean survival for the 0-10 y age-group was estimated at 68 % (Ryland & Ajayi 1984) and although this survival might be smaller for lower age classes, it is often considered to be roughly constant. In comparison, in the European plaice, P. platessa, the egg mortality has been estimated to be as high as 20%/day (Beverton et al. 1992) and juvenile mortality at 4%/day (Van der Veer et al. 1990). It thus can be expected that the Ne/N ratio will be much higher for skates as variance in reproductive success may be lower.

Other factors, however, can promote variance in reproductive success such as mating behavior. A few direct observations in Rajiformes have described a complex mating behavior where females could be choosy although sometimes they mated with several males (Brockman 1975; Tricas 1980; McCourt & Kerstitich 1980; Young 1993; Nordell 1994; Yano et al. 1999; Chapman et al. 2003). At this stage, the population dynamics of rays and the relative contributions of the parameters listed in Box 1 on effective population size remain unclear. There are no long term

22

Introduction

survey data to guide us in the role of fluctuations in population size although long life-span and overlapping generations may counteract its effect. Effects of fisheries Potential loss of genetic diversity (Box 3) is strongly related to small Ne. Using theoretical simulations, a population with an effective population size of 500 will lose 5% of its initial expected heterozygosity within 50 generations, while a population with an Ne of 50 will lose 40% over the same number of generations (Franklin & Frankham 1998). These authors suggested that the minimum Ne needs to be 50 individuals for a population for the short term and 500 individuals for the long term. Such numbers have seemed irrelevant in fisheries biology where population sizes are estimated in hundreds of millions to tens of billions. Recently, however, the role of additional factors associated with small population Ne/N ratio and recovery potential have come under discussion. In most marine fishes, the minimal threshold of genetic diversity needed to ensure stock recovery remains unclear (Hutchings 2000).

Box 3: Genetic Diversity

Genetic diversity is the relative level of polymorphism at a locus (or loci) expressed as expected heterozygosity or allelic/nucleotide/haplotype diversity.

A locus is polymorphic if it has more than one allele, and none of the allelic frequencies exceeds 0.99 or 0.95.

Expected heterozygosity (He) is the number of heterozygotes under Hardy-Weinberg equilibrium. When more than two alleles are present at a locus, then

∑=

−=j

iie pH

1

21

with the allelic frequency of the iip th allele and j the total number of alleles.

Allelic diversity is the total number of alleles summed over all loci divided by the number of loci. It is more sensitive then expected heterozygosity in detecting loss of diversity because of its greater sensitivity to population size (Spencer et al. 2000).

l

nNa

l

ia∑

== 1

with l the number of loci and na, the number of alleles.

23

Chapter 1

Decline in census population size due to fishing pressure can lead to a decline of the effective population size. In this case, the effect of genetic drift will be stronger leading to a loss of genetic diversity. This has been documented in several cases: in the New Zealand orange roughy, Hoplostehus atlanticus (Smith et al. 1991); in the New Zealand red snapper, Pagrus auratus, (Hauser et al. 2002); and in the North Sea cod, Gadus morhua, (Hutchinson et al. 2003), though a more recent study showed no loss of genetic diversity for the North Sea and Baltic Sea cod (Poulsen et al. 2006). In one case, instead of a loss of genetic diversity, a significant increase of inbreeding was demonstrated between 1950 and 2002, which strongly correlated with increased fishing pressure in European plaice (P. platessa) (Hoarau et al. 2005).

Fishing pressure can also disrupt life history traits and mating behavior, which are important parameters affecting Ne (Rowe & Hutchings 2003). For example, fishing selects for larger individuals because they are easier to catch. This, in turn, leads to a lower age of maturity and smaller size (Rijnsdorp 1993; Walker 1998; ICES 2005). This is likely to have consequences for reproductive success, as smaller males may have less sperm and/or a decrease in sperm vigor. Likewise, females may be less experienced in choosing sheltered habitat to release their eggs. Fisheries may also affect the sex ratio in a population as one of the two sexes may be caught in higher number. The consequence is that the most abundant sex can have difficulties to find a mate, leading to an Allee effect (Rowe & Hutchings 2003). Indeed, as the density of the population is lowered, finding a mate can become more difficult even without a sex skew and may change the general reproductive behavior (Stephens & Sutherland 1999; Allendorf et al. 2001). Effect of reduced mate choice on behavior could be a shift from polyandry to monoandry (Rowe & Hutchings 2003), reducing then Ne (Sugg & Chesser 1994). At the opposite, if smaller males have less sperm, limiting the egg fertilization, then polyandrous females may become the most common in heavily exploited areas like in the American lobster (Homarus americanus) (Gosselin et al. 2005). Phylogeography and historical processes Phylogeography provides a window on historical processes—such as the Last Glacial Maximum (LGM, 20,000 BP) and earlier—that have left their evolutionary signatures on the present geographic distributions of genetic traits (i.e. population genetic structure) (Avise 2000). Thus, past events such as population expansion, population bottlenecks, and vicariance can also contribute to our understanding of the contemporary pattern of population genetic structure. This is mostly important in regions where past climate change has drastically redistributed the biota. For example, glaciation cycles of the past 2.4 million years, have periodically restricted species ranges into disjunct refugia, driving genetic differentiation between them due to genetic drift and restricted gene flow. As ice sheets retreated, populations expanded generally following the leading edge hypothesis (Ibrahim et al. 1996). In

24

Introduction

this model, theory predicts that the leading edges will be less genetically diverse as founders move away from the genetically-more-diverse former refugia. Thus, based on the level of genetic diversity, its distribution and phylogenetic relationship among DNA haplotypes, aspects of historical demography can be reconstructed.

Highly mobile organisms with long-lived, pelagic larval stages such as marine bony fishes may have been able to escape local extinction because their habitats were only marginally modified and/or the possibility to move away from the front was much stronger. In this case, recolonization of previously ice-covered areas would have been rapid with little population differentiation between regions. In contrast, shallow subtidal/intertidal organisms with short distance dispersal would have experienced direct loss of habitat due to ice scouring, local extinction and, eventually, strong genetic differentiation between isolated refugia (Avise et al. 1987). Skates might be predicted to occupy an intermediate position as they are free to move but are still dependent on bottom substrate for feeding and egg laying. Technical Issues Sampling Studying population genetic structure in vagile organisms is challenging because high levels of gene flow maintain overall low genetic differentiation and sampling single populations may not be self-evident (Fig. 9). When locations are naturally genetically isolated, the risk of sampling an admixed population is almost zero; but when populations overlap in a location the difficulty of good sampling can become difficult.

Isolation Panmixia

Divergence

Where to sample?

A B C D

Isolation Panmixia

Divergence

Where to sample?

A B C D

Fig. 9. Continuum of population differentiation (modified from Waples & Gaggiotti 2006). Each group of circles represents a group of locations with varying degree of connectivity (geographical overlap and/or migration). A=Complete independence, B=Modest connectivity, C=Substantial connectivity, D= Panmixia.

25

Chapter 1

Ways to minimize this problem at the outset of a study include: 1) collection of fixed size classes in an effort to minimize overlapping generations; 2) sampling far enough apart (based on what ever information is available that suggests different populations) in order to detect differences; and most of all 3) the inclusion of temporal sampling of the same sites where possible. If differences are consistently found, the result is probably real. In the event that more than one population is inadvertently sampled (a Wahlund effect) (Waples 1998); this will be detected in the genetic analysis as a departure from Hardy-Weinberg Equilibrium (HWE).

In order to maximize statistical power—the ability to reject a null hypothesis of no differentiation—an adequate number of individuals must be sampled per putative population/location. As a rule of thumb, at least 50 individuals per location are required (Waples 1998). This criterion was difficult to achieve for rays and skates. For thornback rays, the average number of individuals caught per haul is typically 0.2 (Rijnsdorp et al. 1996). Taking into account only those sessions in which thornback rays were fished, the average number of individuals per haul was 2.2. In order to approach the 50-individuals prerequisite, it was necessary to pool hauls within a distance of 7 nmi. The decision for this distance class was based on tagging studies. Even applying these measures, however, it was not always possible to reach the target number of 50 samples per location. As will become clear, however, this limitation did not seriously affect the final results. DNA

Contemporary DNA was extracted from muscle tissue using either a modified CTAB protocol (Hoarau et al. 2002b) or a silica based protocol (Elphinstone et al. 2003). Historical DNA was extracted from preserved vertebrae or tissue surrounding vertebrae taken from archived collections at the CEFAS (Centre for Environmental Fisheries and Aquaculture Sciences, Lowestoft, UK). Samples from 1965 were preserved in ethanol and were extracted using a SDS based protocol for archived samples (Hutchinson et al. 1999). Samples from 1974, however, were preserved in formaldehyde. We used the method of (Schander & Kenneth 2003) with success. However, subsequent PCR amplification success was very low (0-35%) forcing us to exclude the 1974 samples.

Specific precautions have to be taken when working with archived samples to avoid contamination either by present-day samples or other species. For these reasons, all DNA extractions of archived samples were performed realized with filter tips and negative control in a DNA-free laboratory Microsatellite loci Microsatellite loci are tandemly repeated motifs of two to five bases scattered throughout the genomes of most eukaryotes (Fig. 10). They are codominant, assumed to be neutral and hypervariable with a fast mutation rate. These

26

Introduction

characteristics have made them the marker of choice for studying population genetic structure (Jarne & Lagoda 1996) having replaced earlier generation allozyme loci. A decade of experience with microsatellite loci in hundreds of different species has established their power for addressing almost all types of population genetic questions, as well as revealed their weaknesses. Technical artifacts such as null alleles (i.e., non-amplification of some alleles), stuttering (Taq polymerase slippage during PCR amplifications) and large allele drop-out (higher amplification rates of shorter alleles than longer ones) are commonly encountered and can be accounted for (Van Oosterhout et al. 2004). The main shortcomings of microsatellites are the problem of a reliable mutation model and homoplasy, which limits their utility in cases where mutation rate needs to be determined (Angers et al. 2000; Estoup et al. 2002). The assumption of neutrality is also coming into question (Ranum & Day 2002; Li et al. 2002). Aside from this, however, they remain a powerful category of markers.

Power to detect differentiation is also related to the number of microsatellite loci and their level of polymorphism. For population level surveys of this type, between five and ten loci are typically used. In the present study we used five loci with allelic diversity ranging from 8 to 57 alleles/locus for a total of 124 alleles.

CCTTAAGTACTATCCGTGTGTGTGTGTGTGTGTGCCATGGATTCAT

Forward PCR Primer Reverse PCR Primer Microsatellite region

Allele 1: GTGTGTGTGTGT = motif GT repeated 6 times

Allele 2: GTGTGT = motif GT repeated 3 times

Fig. 10. Example of a microsatellite sequence and two possible alleles; in this example a heterozygote.

Developing microsatellite markers is now considered routine, although it remains difficult in some species. Reasons for this are unknown, though it is apparently related to the number and distribution of microsatellite loci in the genome. Even with enrichment techniques, it is sometimes difficult to find enough candidate loci. In other cases, loci are plentiful but not very polymorphic. In the case of R. clavata, microsatellite development was moderately difficult, requiring two enriched libraries and the sequencing of 432 clones from which 40 primer sets were designed and ultimately five polymorphic loci were produced. Mitochondrial DNA (mtDNA) Mitochondrial loci/haplotypes are the most widely used markers for phylogeographic studies in animals and protists. For this study, we used a fragment

27

Chapter 1

of 290 bp from the Cytochrome b gene. The main advantages of mtDNA are that it is generally maternally inherited, haploid and putatively does not recombine (Avise 2000)—although recombination in animal mtDNA has now been shown to occur in some species and is probably more frequent than previously thought (Hoarau et al. 2002a; Tsaousis et al. 2005; Gantenbein et al. 2005; Guo et al. 2006).

Additional important advantages of mtDNA are : 1) that it allows inferences of historical demography from haplotype divergences and their frequency (Avise et al. 1988); and 2) its smaller effective population size (Ne), i.e., four times smaller than nuclear DNA markers (Birky et al. 1989). Thus, the effect of genetic drift is stronger and higher levels of population differentiation can be detected with mtDNA than with nuclear DNA. This can be of a great importance in populations that have not reached migration/genetic drift equilibrium.

28

Introduction

Outline of the thesis The development of microsatellite loci for the thornback ray, Raja clavata is described in Chapter 2.

Evidence for regional population structure around UK using the newly developed microsatellite loci is presented in Chapter 3. In this initial survey, collections were obtained from 14 locations—six in the North Sea, four in the English Channel and four in the Irish Sea. Some locations could be sampled twice, either in two different seasons, or in two different years. This provided a test of population stability. It was hypothesized that relatively strong population differentiation would be found, and that the spatial scale of genetic differentiation with the home range estimates based on tagging data would be in proximal agreement.

A large-scale phylogeographic survey covering the entire European range of the species was conducted using both microsatellite and mtDNA (Chapter 4). We asked how recent climatic history has shaped the regional distribution of R. clavata along northeastern Atlantic shores including the Mediterranean basin; and to what extent historical imprints of refugia, recolonization and demographic expansion were detectable. Finally by increasing the spatial scale, it was possible to establish major geographical barriers to gene flow for R. clavata.

The decline in numbers of thornback rays in the Irish Sea and the North Sea raised the question of effective population size and the possible impact of fisheries on the genetic diversity. Using temporal samples collected from archived vertebrae (1965, 2003 and 2004), I estimated the effective population size (Ne) and the possible loss of genetic diversity (Chapter 5).

The mating system of a species can greatly influence the level of genetic structure and the spatial scale of population differentiation. In Chapter 6, I present a multiple paternity study, in which four females clutches were analyzed.

A comparative phylogeographic survey of a second North Atlantic species, the thorny skate, Amblyraja radiata, is presented in Chapter 7. I used mtDNA haplotype data (as in the case of R. clavata reported in Chapter 4) and collected samples in Iceland, Norway, North Sea, Kattegat, and Newfoundland. I expected to find similar levels of population genetic differentiation and similar geographical barriers to gene flow as for R. clavata, as these two species shared similar life history traits.

Finally, Chapter 8 summarizes the main conclusions from this thesis.

29

Chapter 1

References Allendorf FW, Leary RF, Spruell P, Wenburg JK (2001) The problems with hybrids: Setting conservation guidelines. Trends in Ecology & Evolution, 16, 613-622. Anderson EC, Williamson EG, Thompson EA (2000) Monte Carlo evaluation of the likelihood for Ne from temporally spaced samples. Genetics, 156, 2109-2118. Angers B, Estoup A, Jarne P (2000) Microsatellite size homoplasy, SSCP, and population structure: A case study in the freshwater snail Bulinus truncatus. Molecular Biology and Evolution, 17, 1926-1932. Ajayi TO (1993) Food and Feeding-Habits of Raja Species (Batoidei) in Carmarthen Bay, Bristol Channel. Journal of the Marine Biological Association of the United Kingdom, 62, 215-223. Avise JC (2000) Phylogeography: The history and formation of species, 1st edn. Harvard University Press. Cambridge, UK. Avise JC, Arnold J, Ball RM, Bermingham E, Lamb T, Neigel JE, Reeb CA, Saunders NC (1987) Intraspecific phylogeography: The mitochondrial DNA bridge between population genetics and systematics. Annual Review of Ecology and Systematics, 18, 489-522. Avise JC, Ball RM, Arnold J (1988) Current versus historical population sizes in vertebrate species with high gene flow: A comparison based on mitochondrial DNA lineages and inbreeding theory for neutral mutations. Molecular Biology and Evolution, 5, 331-344. Bahri-Sfar L, Lemaire C, Ben Hassine OK, Bonhomme F (2000) Fragmentation of sea bass populations in the western and eastern Mediterranean as revealed by microsatellite polymorphism. Proceedings of the Royal Society of London Series B-Biological Sciences, 267, 929-935. Berthier P, Beaumont MA, Cornuet JM, Luikart G (2002) Likelihood-based estimation of the effective population size using temporal changes in allele frequencies: A genealogical approach. Genetics, 160, 741-751. Beverton RJH, Iles TC (1992) Mortality rates of 0-group plaice (Pleuronectes platessa L.), Dab (Limanda limanda L.) and Turbot (Scophthalmus maximus L.) in European waters. 2-Comparison of mortality rates and construction of life table for 0-group plaice. Netherlands Journal of Sea Research, 29, 49-59. Birky CW, Fuerst P, Maruyama T (1989) Organelle gene diversity under migration, mutation, and drift - Equilibrium expectations, approach to equilibrium, effects of heteroplasmic cells, and comparison to nuclear genes. Genetics, 121, 613-627. Blake K (1976) Polymorphic forms of eye lens protein in the ray Raja clavata (Linnaeus). Comparative Biochemistry and Physiology Part B, 54B, 441-442. Brander K (1981) Disappearance of common skate Raia batis from Irish Sea. Nature, 290, 48-49. Brockman F (1975) An observation on mating behavior of the southern stingray, Dasyatis americana. Copeia, 1975, 784-785. Caballero A (1994) Developments in the prediction of effective population size. Heredity, 73, 657-679.

30

Introduction

Capetta H, Duffin C, Zidek J (1993) Chondrichthyes. In: Fossil records 2 (ed. Benton M), pp. 593-610. Chapman Hall, London. Carvalho GR, Hauser L (1994) Molecular genetics and the stock concept in fisheries. Review in Fisheries and Fish Biology, 4, 326-350. Chapman DD, Corcoran MJ, Harvey GM, Malan S, Shivji MS (2003) Mating behavior of southern stingrays, Dasyatis americana (Dasyatidae). Environmental Biology of Fishes, 68, 241-245. Crouse D (1999) The consequences of delayed maturity in human-dominated world. In: Life in the slow lane: ecology and conservaton of long-lived marine animals (ed. Musick J), pp. 195-202. American Fisheries Society, Bethesda, Maryland (USA). Daan N, Bromley PJ, Hislop JRG, Nielsen NA (1990) Ecology of North-Sea fish. Netherlands Journal of Sea Research, 26, 343-386. Daan N, Johnson B, Larsen JL, Sparholt H (1993) Analysis of the ray (Raja spec). Samples collected during the 1991 International Stomach Sampling project. ICES C.M. 1993/G:15. 17pp. Dulvy NK, Metcalfe JD, Glanville J, Pawson MG, Reynolds JD (2000) Fishery stability, local extinctions, and shifts in community structure in Skates. Conservation Biology, 14, 283-293. Dulvy NK, Reynolds JD (1997) Evolutionary transitions among egg-laying, live-bearing and maternal inputs in sharks and rays. Proceedings of the Royal Society of London Series B-Biological Sciences, 264, 1309-1315. Dulvy NK, Reynolds JD (2002) Predicting extinction vulnerability in skates. Conservation Biology, 16, 440-450. Duncan KM, Martin AP, Bowen BW, De Couet HG (2006) Global phylogeography of the scalloped hammerhead shark (Sphyrna lewini). Molecular Ecology, 15, 2239-2251. Ellis JR, Cruz-Martinez A, Rackham BD, Rogers SI (2005a) The distribution of chondrichthyan fishes around the British Isles and implications for conservation. Journal of Northwestern Atlantic Fisheries Sciences, 35, 195-213. Ellis JR, Dulvy NK, Jennings S, Parker-Humphreys M, Rogers SI (2005b) Assessing the status of demersal elasmobranchs in UK waters: A review. Journal of the Marine Biological Association of the UK, 85, 1025-1047. Ellis JR, Shackley SE (1995) Observations on egg-laying in the thornback ray. Journal of Fish Biology, 46, 903-904. Elphinstone MS, Hinten GN, Anderson MJ, Nock CJ (2003) An inexpensive and high-throughput procedure to extract and purify total genomic DNA for population studies. Molecular Ecology Notes, 3, 317-320. Estoup A, Jarne P, Cornuet JM (2002) Homoplasy and mutation model at microsatellite loci and their consequences for population genetics analysis. Molecular Ecology, 11, 1591-1604. FAO (2004). The state of world fisheries and aquaculture: Fisheries Resources. FAO Fisheries, Rome, ISBN 92-5-105177-1. FAO-Fishstat (2006) Fishstat: Universal software for fishery statistical time series. Fishery information, Data and statistic Units (FIDI), FAO, Rome, Italy.

31

Chapter 1

Feldheim KA, Gruber SH, Ashley MV (2001) Population genetic structure of the lemon shark (Negaprion brevirostris) in the western Atlantic: DNA microsatellite variation. Molecular Ecology, 10, 295-303. Frankham R (1995) Effective population size-adult population size ratios in wildlife: A review. Genetical Research, 66, 95-107. Frankham R, Ballou J, Briscoe D (2002) Introduction to Conservation genetics, fourth edn. University Press. Cambridge. Franklin I, Frankham R (1998) How large must populations be to retain evolutionary potential? Animal conservation, 1, 69-71. Gaida IH (1997) Population structure of the Pacific angel shark, Squatina californica (Squatiniformes: Squatinidae), around the California Channel Islands. Copeia, 738-744. Gantenbein BFV, Gantenbein-Ritter IA, Balloux F (2005) Evidence for recombination in scorpion mitochondrial DNA (Scorpiones : Buthidae). Proceedings of the Royal Society of London Series B-Biological Sciences, 272, 697-704. Gardner MG, Ward RD (1998) Population structure of the Australian gummy shark (Mustelus antarcticus Gunther) inferred from allozymes, mitochondrial DNA and vertebrae counts. Marine and Freshwater Research, 49, 733-745. Gosselin T, Sainte-Marie B, Bernatchez L (2005) Geographic variation of multiple paternity in the American lobster, Homarus americanus. Molecular Ecology, 14, 1517-1525. Guo XH, Liu SJ, Liu Y (2006) Evidence for recombination of mitochondrial DNA in triploid crucian carp. Genetics, 172, 1745-1749. Hauser L, Adcock GJ, Smith PJ, Ramirez JH, Carvalho GR (2002) Loss of microsatellite diversity and low effective population size in an overexploited population of New Zealand snapper (Pagrus auratus). Proceedings of the National Academy of Sciences of the USA, 99, 11742-11747. Hedgecock D (1994) Does variance in reproductive success limit effective population sizes of marine organisms? In: Genetics and Evolution of Aquatic Organisms. (ed. Beaumont AR), pp. 122-134. Chapman and Hall, London. Hedrick PW (2005) A standardized genetic differentiation measure. Evolution, 59, 1633-1638. Heessen HJLE (2004). Development of Elasmobranchs Assessment, DELASS. DG Fish study contract 99/055. Final report 605p. Heist EJ, Gold JR (1999) Microsatellite DNA variation in sandbar sharks (Carcharhinus plumbeus) from the Gulf of Mexico and mid-Atlantic Bight. Copeia, 182-186. Heist EJ, Musick JA, Graves JE (1996a) Mitochondrial DNA diversity and divergence among sharpnose sharks, Rhizoprionodon terraenovae, from the Gulf of Mexico and Mid-Atlantic bight. Fishery Bulletin, 94, 664-668. Heist EJ, Musick JA, Graves JE (1996b) Genetic population structure of the shortfin mako (Isurus oxyrinchus) inferred from restriction fragment length polymorphism analysis of mitochondrial DNA. Canadian Journal of Fisheries and Aquatic Sciences, 53, 583-588. Hoarau G. (2004) Population genetics structure of plaice (Pleuronectes platessa) in Northern Europe. University of Groningen, The Netherlands.

32

Introduction

Hoarau G, Boon E, Jongma DN, Ferber S, Palsson J, Van der Veer HW, Rijnsdorp AD, Stam WT, Olsen JL (2005) Low effective population size and inbreeding in Plaice (Pleuronectes platessa): An abundant but overexploited flatfish. Proceedings of the Royal Society of London Series B-Biological Sciences, 272, 497-503. Hoarau G, Holla S, Lescasse R, Stam WT, Olsen JL (2002a) Heteroplasmy and evidence for recombination in the mitochondrial control region of the flatfish Platichthys flesus. Molecular Biology and Evolution, 19, 2261-2264. Hoarau G, Rijnsdorp AD, Van der Veer HW, Stam WT, Olsen JL (2002b) Population structure of plaice (Pleuronectes platessa L.) in Northern Europe: Microsatellites revealed large-scale spatial and temporal homogeneity. Molecular Ecology, 11, 1165-1176. Holden MJ (1975) Fecundity of Raja clavata in British waters. Journal du Conseil International pour l'Exploration de la Mer, 36, 110-118. Hunter E, Buckley A.A., Stewart C., Metcalfe J.D. (2005a) Migratory behavior of the thornback ray, Raja clavata in the Southern North Sea. Journal of the Marine Biological Association of the UK, 85, 1095-1105. Hunter E, Buckley A.A., Stewart C, Metcalf JD (2005b) Repeated seasonal migration by a thornback ray in the southern North Sea. Journal of the Marine Biological Association of the UK, 85, 1199-1200. Hutchings JA (2000) Collapse and recovery of marine fishes. Nature, 406, 882-885. Hutchings JA, Reynolds JD (2004) Marine fish population collapses: Consequences for recovery and extinction risk. Bioscience, 54, 297-309. Hutchinson WF, Carvalho GR, Rogers SI (1999) A nondestructive technique for the recovery of DNA from dried fish otoliths for subsequent molecular genetic analysis. Molecular Ecology, 8, 893-894. Hutchinson WF, Carvalho GR, Rogers SI (2001) Marked genetic structuring in localised spawning populations of cod Gadus morhua in the North Sea and adjoining waters, as revealed by microsatellites. Marine Ecology-Progress Series, 223, 251-260. Hutchinson WF, Van Oosterhout C, Rogers SI, Carvalho GR (2003) Temporal analysis of archived samples indicates marked genetic changes in declining North Sea cod (Gadus morhua). Proceedings of the Royal Society of London Series B-Biological Sciences, 270, 2125-2132. Ibrahim KM, Nichols RA, Hewitt GM (1996) Spatial patterns of genetic variation generated by different forms of dispersal during range expansion. Heredity, 77, 282-291. ICES (2005) Report on the working group on elasmobranch fishes (WGEF). Lisbon, Portugal, ICES CM 2006/ACFM:03 -232 p. IUCN/SSC (2004) A global species assessment: 2004 IUCN red list of threatened species. IUCN Publishing Services Unit. Cambridge, UK. Jarne P, Lagoda PJL (1996) Microsatellites, from molecules to populations and back. Trends in Ecology & Evolution, 11, 424-429. Jørgensen HBH, Hansen MM, Bekkevold D, Ruzzante DE, Loeschcke V (2005) Marine landscapes and population genetic structure of herring (Clupea harengus L.) in the Baltic Sea. Molecular Ecology, 14, 3219-3234. Keeney DB, Heupel MR, Hueter RE, Heist EJ (2005) Microsatellite and mitochondrial DNA analyses of the genetic structure of blacktip shark (Carcharhinus limbatus) nurseries in the

33

Chapter 1

northwestern Atlantic, Gulf of Mexico, and Caribbean Sea. Molecular Ecology, 14, 1911-1923. Koop JH (2005) Reproduction of captive Raja spp. in the Dolfinarium Harderwijk. Journal of the Marine Biological Association of the UK, 85, 1201-1202. Lande R, Barrowclough GF (1987) Effective population size, genetic variation, and their use in population management. In: Viable Population for Conservation. (ed. Soulé ME), pp. 87-123. Cambridge University Press, Cambridge, UK. Larson RJ, Julian RM (1999) Spatial and temporal genetic patchiness in marine populations and their implications for fisheries management. California Cooperative Oceanic Fisheries Investigations Reports, 40, 94-99. Li YC, Korol AB, Fahima T, Beiles A, Nevo E (2002) Microsatellites: genomic distribution, putative functions and mutational mechanisms: A review. Molecular Ecology, 11, 2453-2465. Lloris D, Rucabado J, Figueroa H (1991) Biogeography of the macaronesian ichthyofauna (the Azores, Madeira, The Canary Islands, Cape Verde and the African enclave). Boletim do Museu municipal do Funchal, 43, 191-241. Martin C, Vaz S, Ernande B, Ellis JR, Eastwood P, Coppin F, Harrop S, Meaden G, Carpentier A (2005) Spatial distributions (1989-2004) and preferential habitats of thornback ray and lesser-spotted dogfish in the Eastern English Channel. ICES Theme Session on Elasmobranch Fisheries Science (N). McCourt R, Kerstitich A (1980) Mating behavior and sexual dimorphism in dentition in the stingray, Urolophus concentricus, from the Gulf of California. Copeia, 1980, 900-901. McEachran JD, Dunn KA (1998) Phylogenetic analysis of Skates, a morphologically conservative clade of elasmobranchs (Chondricthyes: Rajidae). Copeia, 271-290. McPherson AA, Stephenson RL, Taggart CT (2003) Genetically different Atlantic herring Clupea harengus spawning waves. Marine Ecology-Progress Series, 247, 303-309. Meyer A, Zardoya R (2003) Recent advances in the (molecular) phylogeny of vertebrates. Annual Review of Ecology Evolution and Systematics, 34, 311-338. Nordell SE (1994) Observations of the mating behavior and dentition of the round stingray, Urolophus Halleri. Environmental Biology of Fishes, 39, 219-229. Norse E, Crowder L (2005) Marine conservation Biology: The science of maintaining the sea's biodiversity, first edn. Island Press. Washington. Nottage AS, Perkins EJ (1983) Growth and maturation of roker Raja clavata L. in the Solway Firth. Journal of Fish Biology, 23, 43-48. Palumbi SR (2003) Population genetics, demographic connectivity and the design of marine reserves. Ecological Applications, 13, S146-S158. Pardini AT, Jones CS, Noble LR, Kreiser B, Malcolm H, Bruce BD, Stevens JD, Cliff G, Scholl MC, Francis M, Duffy CA, Martin AP (2001) Sex-biased dispersal of great white sharks. Nature, 412, 139-140. Pawson MG, Jennings S (1996) A critique of methods for stock identification in marine capture fisheries. Fisheries Research, 25, 203-217. Planes S, Lenfant P (2002) Temporal change in the genetic structure between and within cohorts of a marine fish, Diplodus sargus, induced by a large variance in individual reproductive success. Molecular Ecology, 11, 1515-1524.

34

Introduction

Poulsen NA, Nielsen EE, Schierup MH, Loeschcke V, Gronkjaer P (2006) Long-term stability and effective population size in North Sea and Baltic Sea cod (Gadus morhua). Molecular Ecology, 15, 321-331. Pujolar JM, Maes GE, Volckaert FAM (2006) Genetic patchiness among recruits in the European eel Anguilla anguilla. Marine Ecology-Progress Series, 307, 209-217. Ranum LPW, Day JW (2002) Dominantly inherited, non-coding microsatellite expansion disorders. Current Opinion in Genetics & Development, 12, 266-271. Reid DP, Pongsomboon S, Jackson T, McGowan C, Murphy C, Martin-Robichaud D, Reith M (2005) Microsatellite analysis indicates an absence of population structure among Hippoglossus hippoglossus in the North-west Atlantic. Journal of Fish Biology, 67, 570-576. Rijnsdorp AD (1993) Fisheries as a large scale experiment on life history evolution: disentangling phenotypic and genetic effects in changes in maturation and reproduction of North Sea plaice, Pleuronectes platessa L. Oecologia, 96, 391-401. Rijnsdorp AD, van Leeuwen PI, Daan N, Heessen HJL (1996) Changes in abundance of demersal fish species in the North Sea between 1906-1909 and 1990-1995. Ices Journal of Marine Science, 53, 1054-1062. Rogers SI, Ellis JR (2000) Changes in the demersal fish assemblages of British coastal waters during the 20th century. Ices Journal of Marine Science, 57, 866-881. Rowe S, Hutchings JA (2003) Mating systems and the conservation of commercially exploited marine fish. Trends in Ecology & Evolution, 18, 567-572. Rus Hoelzel A, Shivji M, Magnussen J, Francis M (2006) Low worldwide genetic diversity in the basking shark (Cetorhinus maximus). Biology Letters. Ryland JS, Ajayi TO (1984) Growth and population dynamics of three Raja Species (Batoidei) in Carmarthen Bay, British Isles. Journal du Conseil International pour l'Exploration de la Mer, 41, 111-120. Sandoval-Castillo J, Rocha-Olivares A, Villavicencio-Garayzar C, Balart E (2004) Cryptic isolation of Gulf of California shovelnose guitarfish evidenced by mitochondrial DNA. Marine Biology, 145, 983-988. Schander C, Kenneth HM (2003) DNA, PCR and formalinized animal tissue: A short review and protocols. Organisms Diversity & Evolution, 3, 195-205. Schrey AW, Heist EJ (2003) Microsatellite analysis of population structure in the shortfin mako (Isurus oxyrinchus). Canadian Journal of Fisheries and Aquatic Sciences, 60, 670-675. Smith PJ, Francis RICC, Mcveagh M (1991) Loss of genetic diversity due to fishing pressure. Fisheries Research, 10, 309-316. Spencer CC, Neigel JE, Leberg PL (2000) Experimental evaluation of the usefulness of microsatellite DNA for detecting demographic bottlenecks. Molecular Ecology, 9, 1517-1528. Stehmann M, Bürkel DL (1994) Rajidae. In: Fishes of the North-eastern Atlantic and Mediterranean Vol. I (ed. Whitehead PJP, Bauchot ML, Hureau J-C, Nielsen J, & Tortonese E), pp. 163-196. UNESCO, Paris. Stephens PA, Sutherland WJ (1999) Consequences of the Allee effect for behaviour, ecology and conservation. Trends in Ecology & Evolution, 14, 401-405.

35

Chapter 1

Stow A, Zenger K, Briscoe D, Gillings M, Peddemors V, Otway N, Harcourt R (2006) Isolation and genetic diversity of endangered grey nurse shark (Carcharias taurus) populations. Biology Letters, 2, 308-311. Sugg DW, Chesser RK (1994) Effective population sizes with multiple paternity. Genetics, 137, 1147-1155. Sulikowski JA, Kneebone J, Elzey S, Danley PD, Howell WH, Jurek J, Tsang PCW (2005) The reproductive cycle of the thorny skate (Amblyraja radiata) in the western Gulf of Maine. Fishery Bulletin, 103, 536-543. Tinti F, Ungaro N, Pasolini P, De Panfilis M, Garoia F, Guarniero I, Sabelli B, Marano G, Piccinetti C (2003) Development of molecular and morphological markers to improve species-specific monitoring and systematics of Northeast Atlantic and Mediterranean skates (Rajiformes). Journal of Experimental Marine Biology and Ecology, 288, 149-165. Tricas T (1980) Courtship and mating related behaviors in mylobatid rays. Copeia, 1980, 553-556. Tsaousis AD, Martin DP, Ladoukakis ED, Posada D, Zouros E (2005) Widespread recombination in published animal mtDNA sequences. Molecular Biology and Evolution, 22, 925-933. Turner TF, Wares JP, Gold JR (2002) Genetic effective size is three orders of magnitude smaller than adult census size in an abundant, estuarine-dependent marine fish (Sciaenops ocellatus). Genetics, 162, 1329-1339. Valsecchi E, Pasolini P, Bertozzi M, Garoia F, Ungaro N, Vacchi M, Sabelli B, Tinti F (2005) Rapid Miocene-Pliocene dispersal and evolution of Mediterranean rajid fauna as inferred by mitochondrial gene variation. Journal of Evolutionary Biology, 18, 436-446. Van der Veer HW, Pihl L, Bergman MJN (1990) Recruitment Mechanisms in North-Sea Plaice Pleuronectes platessa. Marine Ecology-Progress Series, 64, 1-12. Van Oosterhout C, Hutchinson WF, Wills DPM, Shipley P (2004) MICRO-CHECKER: Software for identifying and correcting genotyping errors in microsatellite data. Molecular Ecology Notes, 4, 535-538. Walker PA. (1998) Dynamics of North Sea ray populations. University of Amsterdam, The Netherlands. Walker PA, Heessen HJL (1996) Long-term changes in ray populations in the North Sea. Ices Journal of Marine Science, 53, 1085-1093. Walker PA, Howlett G, Millner R (1997) Distribution, movement and stock structure of three ray species in the North Sea and eastern English Channel. Ices Journal of Marine Science, 54, 797-808. Wang JL (2001) A pseudo-likelihood method for estimating effective population size from temporally spaced samples. Genetical Research, 78, 243-257. Wang JL (2005) Estimation of effective population sizes from data on genetic markers. Philosophical Transactions of the Royal Society B-Biological Sciences, 360, 1395-1409. Wang JL, Whitlock MC (2003) Estimating effective population size and migration rates from genetic samples over space and time. Genetics, 163, 429-446. Waples RS (1989) A generalized approach for estimating effective population size from temporal changes in allele frequency. Genetics, 121, 379-391.

36

Introduction

Waples RS (1998) Separating the wheat from the chaff: Patterns of genetic differentiation in high gene flow species. Journal of Heredity, 89, 438-450. Waples RS, Gaggiotti O (2006) What is a population? An empirical evaluation of some genetic methods for identifying the number of gene pools and their degree of connectivity. Molecular Ecology, 15, 1419-1439. Ward RD, Woodwark M, Skibinski DOF (1994) A comparison of genetic diversity levels in marine, freshwater, and anadromous fishes. Journal of Fish Biology, 44, 213-232. Winchell CJ, Martin AP, Mallatt J (2004) Phylogeny of elasmobranchs based on LSU and SSU ribosomal RNA genes. Molecular Phylogenetics and Evolution, 31, 214-224. Yano K, Sato F, Takahashi T (1999) Observations of mating behavior of the manta ray, Manta birostris, at the Ogasawara Islands, Japan. Ichthyological Research, 46, 289-296. Young RF (1993) Observation of the mating behavior of the yellow stingray, Urolophus jamaicensis. Copeia, 1993, 879-880. Zatcoff MS, Ball AO, Sedberry GR (2004) Population genetic analysis of red grouper, Epinephelus morio, and scamp, Mycteroperca phenax, from the southeastern US Atlantic and Gulf of Mexico. Marine Biology, 144, 769-777.

37

Chapter 1

38