The Norwegian minke whale DNA register: a data base

monitoring commercial harvest and trade of whale products

Kevin A Glover1, Tore Haug2, Nils Øien1, Lars Walløe3, Lotta Lindblom2, Bjørghild B Seliussen1 &

Hans J Skaug1,4

1Institute of Marine Research, PO Box 1870, Nordnes, N-5817 Bergen, Norway; 2Institute of Marine Research, PO Box

6404, N-9294 Tromsø, Norway; 3Institute of Basic Medical Sciences, PO Box 1103, Blindern, N-0317 Oslo, Norway;4Department of mathematics, University of Bergen, N-5008 Bergen, Norway

Introduction 314

Specification of the NMDR 315

General organization and responsibility 315

Overview of the hunt and collection of tissue samples 316

DNA analyses 320

Data quality 320

Application of the register 322

Statistical power of identification 322

Checking meat sold on the Norwegian market 324

Export of whale products 324

Scientific research arising from the NMDR 325

Discussion 325

Future of the NMDR – looking to human DNA data bases and SNPs 325

Individual-based DNA registers: challenges and opportunities 326

Abstract

The application of genetics for the management of natural resources is expanding,

and within this field, DNA registers will play an increasing role. The Norwegian

minke whale DNA register, established in 1996, was designed primarily as a control

system to detect any attempts at illegal trade of products derived from other stocks of

minke whale, or other whale species, under cover of the legal Norwegian harvest

originating from the Northeast Atlantic. The register contains genetic data for 7644

of 7751 whales landed in the period 1997–2010. Profiles are established from

sequencing part of the mtDNA control region, analysis of 10 STRs and a sex-

determining marker. Probabilities of genotypes matching between two randomly

selected whales are 6.0)04 and 3.0)08 for five and eight of the STR loci, respectively.

This permits verification of traded whale products via match to the register. The

register has also been used in a number of ad hoc scientific studies resulting through

the accumulation of genetic, demographic and biological data. Here, we review the

register’s logistics, specifications and evaluate the potential to apply similar registers

to control the exploitation of other marine species.

Keywords CITES, data base, fisheries genetics, forensic, IWC, whales, wildlife

register

Correspondence:

Kevin A Glover, Insti-

tute of Marine Re-

search, PO Box 1870,

Nordnes, N-5817

Bergen, Norway

Tel.:

+00 47 55 23 63 57

E-mail: kevin.glover

@imr.no

Received 24 Apr 2011

Accepted 26 Oct 2011

F I S H and F I S H E R I E S , 2012, 13, 313–332

� 2011 Blackwell Publishing Ltd DOI: 10.1111/j.1467-2979.2011.00447.x 313

Conclusions 329

Acknowledgements 329

References 329

Supporting Information 332

Introduction

As the human population continues to expand, an

increasing strain is being placed on the world’s

natural resources, challenging biodiversity. Turning

to the world’s fisheries, which make a significant

contribution to human protein consumption, com-

mercial harvest has left a legacy of over-exploita-

tion. It is estimated that 85% of the world’s fisheries

are considered fully exploited, over-exploited,

depleted or recovering from depletion (FAO 2010).

To complicate management of these important

resources further, there are significant challenges

associated with by-catch (Harrington et al. 2005;

Diamond and Beukers-Stewart 2011; Lewison et al.

2011). Furthermore, illegal, unreported and unreg-

ulated (IUU) fishing is estimated to be globally worth

between 10 and 23.5 billion USD annually (Agnew

et al. 2009). In the future, greater regulation of both

legal and IUU fishing will be required to ensure

sustainable exploitation of the world’s fisheries.

Molecular genetic data have been widely imple-

mented to describe and identify populations and

management units within fisheries (Hauser and

Carvalho 2008; Waples et al. 2008; Reiss et al.

2009). In some cases, this has also provided the

ability to give management advice, although direct

translation of genetic data into fishery policy has not

been without its challenges (Waples et al. 2008; Reiss

et al. 2009). DNA methods have also been developed

for the identification of commercial fish and seafood

species (reviewed by Rasmussen and Morrissey

2008), and to improve compliance, traceability and

enforcement within fisheries (reviewed by Ogden

2008) and aquaculture (reviewed by Glover 2010).

These developments mirror the increasing trend of

monitoring illegal use of natural resources in general

(Gavin et al. 2010) and increasing focus on applying

genetic data to address issues of illegal harvest and

trade of wildlife (Manel et al. 2002; Baker 2008;

Ogden et al. 2009; Alacs et al. 2010; Ogden 2010).

DNA registers may be broadly defined as orga-

nized collections of genetic data, can accommodate

data generated by various types of molecular

markers, may include biological and demographic

information, and be implemented to address a

diverse range of questions. For the specific purpose

of wildlife and fisheries management, DNA registers

may play a monitoring and enforcement role

(Palsbøll et al. 2006; Baker 2008; Ogden 2008;

Ogden et al. 2009), and can provide capability to

accurately identify unknown sample(s) to specific

individuals, families, populations and species. For

regulation and law-enforcement in wildlife and

fisheries, the majority of DNA forensic challenges

deal with species identification (Ogden et al. 2009;

Tobe and Linacre 2010; Wilson-Wilde et al. 2010).

This challenge is often met by sequencing well-

characterized genes, for example cytochrome

c oxidase I (COI) which is used for ‘DNA barcoding’

species (Hebert et al. 2003), then searching large

public data bases such as GenBank for a close or

direct match. Going beyond species identification,

data bases of allele frequency data at multiple loci

for several or more populations (Shaklee et al. 1999;

Seeb et al. 2007) can permit the identification of

unknown individuals to population of origin using

statistical approaches (reviewed by Hansen et al.

2001; Manel et al. 2002, 2005; Ball et al. 2011).

Individual genetic assignment to population of

origin has identified poaching (Withler et al. 2004;

Wasser et al. 2007), illegal translocations (Frantz

et al. 2006), fishing competition fraud (Primmer

et al. 2000) and even ownership of fish-farm escap-

ees (Glover et al. 2008, 2010a). Finally, at the

narrowest end of the scale, registers of individual

samples, for example taken in a regulated fishery or

hunt, may be established to check for legality of

captured individuals later sold/distributed in the

market via direct match mis-match to the register

(Palsbøll et al. 2006).

The common minke whale occurring in the

Atlantic ocean, Balaenopthera acutorostrata acutoro-

strata, is a small (typical adult size 6–8 m total

length) baleen whale that is presumed to undertake

seasonal migrations from tropical regions where

they breed and overwinter to Arctic regions in the

summer months in the search of abundant food

(Jonsgard 1951, 1966). During this time of the

year, they are mainly limited to continental shelf

The Norwegian minke whale DNA register K A Glover et al.

314 � 2011 Blackwell Publishing Ltd, F I S H and F I S H E R I E S , 13, 313–332

areas although they are also found in offshore deep-

water areas, and their distribution is more or less

continuous from the eastern and central parts of the

North Atlantic to West Greenland (Horwood 1990;

Donovan 1991). These whales are abundant, and

the numbers in the Northeast Atlantic have been

estimated at 107 205 based upon mathematical

modelling from sighting survey data (Skaug et al.

2004). The development of modern whaling of the

species started in the Northeast Atlantic in the

1920s, and the exploitation of the species by

Norwegian fishermen escalated after 1945, reach-

ing its peak in the 1950s with annual catches of

some 3500 animals (Jonsgard 1951; Christensen

and Øien 1990). The initial Norwegian hunt

targeted the Northeast Atlantic stock, whereas the

area around the Jan Mayen island (belonging to the

Central Atlantic stock) was included in the 1960s

(Christensen and Øien 1990). From 1959, Norwe-

gian exploitation of minke whales decreased

because of national harvest regulations (Øien et al.

1987; Christensen and Øien 1990). International

regulations with quotas were introduced in all areas

by the International Whaling Commission (IWC) in

1976 (Øien et al. 1987), and an international

moratorium for all whaling was laid down by the

IWC, taking effect from 1987. Norway issued a

reservation against this moratorium but also halted

whaling in the period 1988 to 1993 because of

uncertainty regarding the stock situation. When

harvest was once again reinstated, annual quotas

were calculated using the Revised Management

Procedure (RMP) developed by the IWC (Skaug

et al. 2004), which uses catch history and the most

recent abundance estimates from the sighting sur-

veys as the basic input data (IWC 1999).

Shortly after Norway re-instated commercial har-

vest of minke whales in the Northeast Atlantic, a

DNA register, hereon referred to as the Norwegian

minke whale DNA register (NMDR), was established

by Bjørnar Olaisen and Berit M. Dupuy at the

Institute of Forensic Medicine at the University of

Oslo, Norway (RMI) (Olaisen 1997). The primary

objective of the register was to develop a control

system to detect any attempts at illegal trade of

products derived from other stocks of minke whale,

or other whale species, under cover of the legal

Norwegian harvest and trade of Northeast Atlantic

minke whale (Olaisen 1997; Anon. 1998). In short,

by having an individual genetic profile for all legally

captured whales, any suspicion of illegal harvest of

minke and/or other whale species would be possible

to examine by direct match to the register. Therefore,

a mis-match would suggest illegal harvest/trade.

Soon after its establishment, the NMDR register

was checked by an international group of scientists

(Palsbøll et al. 2006), who verified that meat

purchased on the Norwegian market was legal

(i.e. matched samples in the register) and that the

genotypes established from two stranded minke

whales sampled in Denmark were excluded (i.e. not

falsely identified to the register). The NMDR has

subsequently been discussed in several review

articles (e.g. Baker 2008; Ogden et al. 2009; Alacs

et al. 2010), and a number of scientific articles

using data from the register have been published

(see the section Research arising from the NMDR).

Nevertheless, despite the fact that the NMDR has

been operated for nearly 15 years, and possibly

represents the only operational individual-based

DNA register for a CITES listed species that is

commercially harvested, its specifications, methods

and logistics have never been presented. Therefore,

the aim of this paper is to review the NMDR and

how it interacts with commercial whaling.

Specification of the NMDR

General organization and responsibility

The NMDR is owned and managed by the Norwe-

gian Directorate of Fisheries (NDF) who are also

responsible for overseeing that the commercial

harvest of minke whales under Norwegian quota

is conducted according to the conditions and

regulations laid down nationally. Together with

commercial hunters and other governmental

research institutions, the NMDR is run in a coor-

dinated manner where all participants have a role

to play in the process (Fig. 1).

When the NMDR was first established in 1996,

the Institute of Marine Research in Tromsø (IMRt)

was given responsibility for organizing practical

details surrounding the register including supplying

necessary tissue sampling equipment for all boats

involved in whaling, long-term storage of tissue

samples sent in by whalers after the season,

organization of the biological data recorded on

captured whales (Table 1) and finally, preparation

of subsets of tissue samples ready for DNA analysis.

Once tissue samples are prepared by IMRt, they are

sent to the molecular genetics laboratory for DNA

analysis. This occurs once the hunting season has

ended, and all available remote sensor data and log

The Norwegian minke whale DNA register K A Glover et al.

� 2011 Blackwell Publishing Ltd, F I S H and F I S H E R I E S , 13, 313–332 315

books have been validated. While the time elapse

between cessation of the hunting season and start of

genetic analyses varies from year to year, at present,

there is a delay of 8–12 weeks before DNA samples

are sent to the analytical laboratory. Upon comple-

tion of DNA analyses, the responsible molecular

genetics laboratory sends quality-checked data back

to the NDF who store the data in the register. This

cycle of activity is repeated each season.

The annual commercial hunt of minke whales in

Norway starts in April and continues through to

August or September (exact timing varies yearly).

Whale meat is sold within Norway as seasonal fresh

produce, i.e. immediately upon landing, or as frozen

product which may enter the market for up to

several years. Thus, for fresh and quickly marketed

frozen products, there is a period in which meat is

available in the market, but the register is not

updated. The register is therefore only able to

provide an ad hoc monitoring and enforcement.

Nevertheless, the supply chain from boat to con-

sumer is characterized by few levels and companies

(Fig. 2), offering the ability to track meat ‘back-

wards’ into the supply chain if necessary.

Overview of the hunt and collection of tissue

samples

The commercial harvest of minke whales in Norway

is based on application of the Revised Management

Procedure (RMP) developed and implemented by the

International Whaling Commission’s (IWC) Scien-

tific Committee (SC). The RMP allocates catch

quotas to specific management areas. There are five

such management areas (IWC 2010) within the

region of interest to Norwegian whalers (Fig. 3).

In the period 1996–2010, the number of boats

actively involved in the yearly hunt varied between

18 and 34, showing a general decline in the past

5 years. In this period, the annual catch has varied

from 388 to 647 individuals, with the average

number of whales captured by boat per year increas-

ing and ranging from 12.5 to 26. The annual quota is

set for a 5-year period at a time. Within such periods,

unused quotas from the first year(s) are transferrable,

which has meant that the annual quota in the 1996–

2010 period has ranged from 435 to 1286. Signif-

icantly, the annual quota has never been taken.

Boats engaged in whaling have licences issued by

the NDF and must fulfil a range of other criteria laid

down by the Norwegian food safety authority and

Norwegian Maritime Directorate (not detailed here).

All vessels are equipped with a trip recorder

consisting of a tamper-proof automated sensor

system to independently monitor the whaling

activities onboard. The system includes logging

time and position by an independent GPS and

collects data from sensors placed in the boat,

including the cannon. Sensors are configured and

calibrated individually for each vessel, making it

Commercial whalersTissue samples, deck-

sheet, fishing log book, remote sensor data

IMRt:Registering/storingsamples, sampling equipment, Cross-

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IMRb:DNA analyses, Quality

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NDFOwn register, overall

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Figure 1 Relationships between the Norwegian Directorate of Fisheries (NDF) who own and manage the register, the

Institute of Marine Research (IMR) who conduct all practical work for the register, and the private companies

licensed to conduct whaling under Norwegian quota.

The Norwegian minke whale DNA register K A Glover et al.

316 � 2011 Blackwell Publishing Ltd, F I S H and F I S H E R I E S , 13, 313–332

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The Norwegian minke whale DNA register K A Glover et al.

� 2011 Blackwell Publishing Ltd, F I S H and F I S H E R I E S , 13, 313–332 317

possible to unequivocally determine firing of the

cannon, misses, hauling of the whale on deck and

other operational activities, by evaluating the com-

bination of sensor data values. The trip recorder

unit is sealed and equipped with backup batteries

and automatic restarting functions to follow any

system interruptions. In this way, the trip recorder

makes an effective provider of control data for the

manually submitted logbooks.

Prior to the start of each season, all whaling boats

are sent two equipment boxes (four for boats that

usually have a large catch) for taking tissue samples

upon which the DNA register is based. These

equipment boxes, known as box A and B, are

duplicates and contain a catch record sheet which is

in addition to the boats standard fishing log book,

sampling instructions and pre-labelled tubes con-

taining alcohol (A1-35 and B1-35) into which the

tissue samples are taken. A full description of these

boxes contents, including documents translated to

English, are available (Data S1).

When a whale is captured, it is winched onto the

boats deck while at sea, ready for flensing. Up to and

including the year 2004, whale inspectors (persons

employed by the NDF) were placed on each boat

throughout the hunting season to monitor the

hunt. These inspectors were able to and in most

cases assisted the whalers in taking the muscle

tissue samples which are subsequently used for

DNA analysis. Since termination of the inspector

system, whalers themselves have been responsible

for taking the tissue samples. In most cases, the

tissue sample for DNA analysis is taken prior to

flensing. A muscle tissue sample is placed into each

of the A and B tubes while the catch record sheet

and the boats fishing log book are completed.

Biological data are recorded from the whale

(Table 1), and if the captured whale is a pregnant

female, the length of the foetus is recorded and

tissue samples are collected (the foetus sample goes

into its own series connected to the mothers DNA

register number).

Whaling boats (18)Catch registered with

autori es, ssue samplesfor DNA analysis

Producers A (5)P d f h l

Producers B (7)Produc on of whale

Produc on of whalemeat purchased from

vessels

mea rom own vessel(s)and purchased from

other vessels

Wholesalers (10´s)Trading whale meat

Export

Commercial outlets(100´s)

Shops, restuarants,internet, diverse traders

Consumer

Figure 2 Logistics from whaling boat to commercial market showing approximate number of companies/units involved

in each step.

The Norwegian minke whale DNA register K A Glover et al.

318 � 2011 Blackwell Publishing Ltd, F I S H and F I S H E R I E S , 13, 313–332

The large tubes supplied in box A and B for tissue

collection permit whalers from having to deal with

standard laboratory type tubes (i.e. 1.5–2 mL),

which are more likely to be lost or damaged on a

commercial vessel. These also reduce the likelihood

of whalers taking too much muscle relative to the

tube size (thus compromising DNA quality). Fur-

thermore, the relatively large muscle samples col-

lected permits extraction of the final tissue sample for

DNA isolation from the middle of the sample. This

reduces the potential for intersample contamination

when they take tissue samples (for example, small

remains of meat/blood from previous whale on the

knife used to cut samples from the next whale).

Due to the fact that hunting minke whales is

dependent on stable weather conditions permitting

the sighting of individual animals, catches are very

patchy, with many days resulting in no catch, while

on ideal days, the most effective boats may capture

low double-figure numbers of whales. At no stage,

however, are two whales winched onto a boat at the

same time. This permits collection of tissue samples

and recording biological data one whale at a time,

thus reducing opportunity for mixing samples. Once

the season is finished, the A box is sent to the IMRt

(Fig. 1). The B box is retained on the vessel until the

A box has arrived at IMRt, upon which time the

B box is also sent to IMRt to prepare it for re-use in

the next season.

When samples have arrived at IMRt, catch record

sheets, fishing log books and remote sensor data are

cross-examined to verify the catch. Once completed,

a subsample of muscle is excised from each sample,

transferred to a new tube (containing ethanol) and

sent to IMRb for genetic analyses. In this process,

each whale is given a unique ID number that

identifies the whale in the register where also

information about vessel, time (year, month, date

and hours) and position of capture, sex, and length

of the whale can be found (Table 1). The remaining

muscle sample from each whale is stored at IMRt

indefinitely.

Figure 3 Map showing the five Revised Management Procedure management (RMP) areas, locations of 25 whale samples

purchased from shops in the present study (filled stars) and their capture positions identified through DNA match in

the Norwegian minke whale DNA register (NMDR) (filled circles). Management area ES = of the Svalbard-Bear Island

area, EB = the eastern Barents Sea, EW = the Norwegian Sea and coastal zones off North Norway, including the Lofoten

area, EN = the North Sea, CM = the western Norwegian Sea-Jan Mayen area.

The Norwegian minke whale DNA register K A Glover et al.

� 2011 Blackwell Publishing Ltd, F I S H and F I S H E R I E S , 13, 313–332 319

DNA analyses

Initial specifications for the DNA analyses upon

which the NMDR are based were established by the

RMI in Oslo in the mid-1990s (Olaisen 1997) and

were evaluated by the IWC working group on the

proposed specifications for a Norwegian DNA data

base register for minke whales (Anon. 1998).

Current specifications of the analyses, including

the analytical protocol, reagents and amplification

conditions, are presented (Data S2).

To provide individual whale recognition within

the register, it was decided that an approach similar

to newly developed human DNA registers should be

implemented. Thus, each whale’s profile was to be

established from the analysis of 10 polymorphic

STR loci, sequencing an approximately 300-bp

segment from the mtDNA control region and

analysing a sex-differentiating marker. The ratio-

nale for diverse marker types was that the STRs and

the sex marker would offer statistical capacity for

individual whale identification. This is similar to the

National DNA data base operated in UK (NDNAD)

where a combination of STR loci and a sex marker

are used (Gill et al. 2006; Tucker et al. 2010). In

addition, mtDNA sequencing was included in the

NMDR to provide species identification and, poten-

tially, assist in identification of population genetic

structure of the species for management purposes.

When the NMDR was first established, availability

of genetic markers and level of analytical technol-

ogy was limited. Consequently, STR markers, iso-

lated from other baleen whale species, were chosen

to start the register (Olaisen 1997). These markers

have been faithfully used throughout the registers

existence. This represents one of the registers

strengths, despite the fact that there are now a

larger range of markers available to be used for this

species.

Sequencing reads the genetic code directly and

thus does not require calibration to compare data

within and among laboratories. STR DNA markers

on the other hand are analysed by quantifying the

migration of PCR amplified STR alleles on a gel or in

a polymer-filled capillary, relative to labelled DNA

fragments of known size (called the size-standard).

This process requires the establishment of an allele

sizing system (often referred to as an allele ladder or

bins), which is usually produced by analysing a set

of samples and then determining bin positions. For

the NMDR, the initial calibration was conducted by

the RMI through the analysis of 338 whales taken

from the catch in 1996. To assist with allele size

designation and calibration of bins, the true size of

some alleles for all markers was determined by allele

specific sequencing, although this has not been used

to verify true size of all alleles including alleles added

subsequently.

The molecular genetic analyses upon which the

NMDR are based where first conducted by a

laboratory in Canada (catches for 1997–2002

analysed in the period 2000–03). Later, analyses

were conducted by two separate laboratories in

Iceland (catch 2003–05 then 2006), and since

2007, the analyses have been conducted by IMRs

molecular genetics laboratory located in Bergen

(IMRb). All laboratories were required to pass a

calibration and blind test prior to starting analyses

(see Data quality below).

The flow of work relating to the laboratory

analyses, as conducted by IMRb, is presented

(Fig. 4). The primary elements involve registration,

which includes both ‘duplication’ of tissue samples

for analysis series 1 and 2, and giving each sample a

unique number permitting quick identification of

DNA plate and tissue box. DNA is isolated in 96-well

format, and each plate includes ‡2 blank cells. All

samples are genotyped in series 1 and 2; then,

following quality checks of sequences by looking at

chromatograms and aligning sequences, and frag-

ment analysis by inspection of automatically size-

determined PCR amplicons (the latter by two

persons), the results from series 1 and 2 are cross-

checked to each other, once again by two persons.

Previous to IMRb taking responsibility for the

analyses, other laboratories have not duplicated all

STR analyses for both isolates. Instead, the second

DNA isolation included amplification of one marker

from each multiplex in addition to the mtDNA

sequencing in reverse direction. Duplication of all

fragment analyses as implemented by IMRb allows

for both cross-checking for potential sample mix ups

and an internal evaluation of genotyping errors and

technical artefacts. No discrepancy between analy-

sis series is permitted before data are delivered to the

register. In the rare case where a specific sample

gives a consistent and un-resolvable discrepancy,

this sample may be submitted to the register with an

additional comment.

Data quality

All laboratories, involved in conducting the genetic

analyses upon which the NMDR is based, were first

The Norwegian minke whale DNA register K A Glover et al.

320 � 2011 Blackwell Publishing Ltd, F I S H and F I S H E R I E S , 13, 313–332

sent a set of samples to calibrate the STR markers to

(up to 100 previously genotyped individuals). After

calibration, these laboratories were tested for accu-

racy of allele sizing by blind analysis of at least 20

known samples. Despite using different laboratory

equipment that required the use of slightly different

analytical protocols among laboratories (i.e. the

conversion from gel to capillary-based sequencing

and fragment analysis equipment occurred in the

period these analyses were conducted), all labora-

tories passed this calibration and blind test of

20 samples with the exception of one homozy-

gote–heterozygote discrepancy. This was observed

for a 216-bp 217-bp heterozygote observed at the

locus GATA417 by IMRb but incorrectly scored as a

217 homozygote by previous laboratories. This

marker has subsequently been shown to display

the highest genotyping error rate in the register

(Haaland et al. 2011).

STR loci are notoriously challenging to calibrate

among laboratories (Pasqualotto et al. 2007; Baric

et al. 2008; de Valk et al. 2009), display genotyping

errors (Bonin et al. 2004; Hoffman and Amos 2005;

Pompanon et al. 2005), and markers isolated from

All data cross checked in excel by two persons

DNA isolation 1

Tissue samples received in laboratory. All samples registered, given unique number

DNA isolation 2

Sequencing quality controlDo all samples fulfill critera 1–3:1. >50% overlap between F and R

sequences2. Entire fragment sequenced3. No sequencing discrepencies

Yes. Sequencingcomplete

Sequencing 1 (forward)

Sequencing 2 (reverse)

Microsatellite + sex marker analysis 1

Microsatellite + sex marker analysis 2

Quality controlchromatogram +

alignment

Quality controlchromatogram +

alignment

Quality control in Genemapper

Quality control in Genemapper

Fragment quality controlDo all samples fulfill ctiteria 1–3:1. All markers genotyped2. ≥50% markers genotyped in both

isolates3. No genotyping discrepancies

Yes. Fragment analysis

complete

No. Some samplesviolate points 1–3.Re-

runs needed

No. Some samplesviolate points 1–3.

Reruns needed

Data entered in NMDR

Figure 4 Work-flow for molecular genetic analyses conducted at the Institute of Marine Research in Bergen (IMRb)

who have been responsible for analyses in the period 2007-present.

The Norwegian minke whale DNA register K A Glover et al.

� 2011 Blackwell Publishing Ltd, F I S H and F I S H E R I E S , 13, 313–332 321

other species are often more prone to technical

challenges such as null alleles. Given the above

challenges exhibited by STRs, and that the NMDR

has changed analytical laboratories several times,

evaluation of data quality is important. This was

recently addressed through the blind re-analysis of

20 randomly selected whales from each of the

yearly catches in the period 1997–2008 (Haaland

et al. 2011). From the successful re-analysis of 234

samples (six samples dropped out in re-analysis),

these authors reported 31 genotyping discrepancies

between entry in the register and re-analysis, giving

an average error rate of 0.013 per locus. These

authors did not reveal any systematic shifts in allele

sizing, and the error rate decreased with time

suggesting increasing genotyping quality. Of the

31 discrepancies, 18 represented false allele size

calls (eight of which were single base pairs while 10

were >1 bp), 10 represented false homozygotes and

three represented false heterozygotes. Thus, it was

concluded that the calibration and blind-control

protocol each new laboratory overtaking the regis-

ter was required to conduct was effective in avoid-

ing any systematic drift in allele size over time as

a result of changing apparatus and reagents.

Furthermore, these authors documented that the

observed low error rate would not detract from the

registers’ primary individual identification function

as this could be accounted for in the match mis-

match to entries and that tissue and DNA storage

permit re-analysis of close matches in case this is

required.

Data quality in the register, as documented

above, is also indirectly confirmed by the fact that

the number of alleles observed in the entire register

for the 10 STR loci quickly reached a plateau after

the first years, and only six new alleles were

observed in the period 2003–10, despite analyses

being conducted in four separate laboratories dur-

ing this period (Fig. 5).

Application of the register

Statistical power of identification

From a total of 7751 whales landed in the period

1997–2010, a total of 7644 individuals have their

tissue samples and DNA profiles organized within

the NMDR (Table 2). Of the 107 whales landed (i.e.

entering the Norwegian market), but lacking DNA

profiles, missing DNA profiles are almost exclusively

caused by the whaling boat ‘forgetting’ to take the

sample at sea, in addition to mixing of samples on

the boat so that one whale was analysed twice at

the expense of another individual. This ranges from

0 to 19 whales’ missing profiles per year. While

there was at first no increase in the frequency of

unsampled whales upon termination of the whaling

inspector system at the end of the 2004 season, the

period 2007–10 showed a distinct albeit small

increase. Nevertheless, the register contains 98.7%

of the whales, which have potentially reached the

Norwegian market, offering a comprehensive oppor-

tunity to monitor and control trade of whale meat.

Number of whales genotyped

Cum

ulat

ive

num

ber o

f alle

les

100

110

120

130

140

150

160

0 1000 2000 3000 4000 5000 6000 7000 8000

Lab. 1. 1997-2002 Lab. 2. 2003 -2005 Lab. 3. 2006 Lab. 4. 2007-2010+

Figure 5 Cumulative number of

alleles observed for ten STR loci

pooled in the Norwegian minke

whale DNA register (NMDR) in the

period 1997 (initiation) to the

2010 (present).

The Norwegian minke whale DNA register K A Glover et al.

322 � 2011 Blackwell Publishing Ltd, F I S H and F I S H E R I E S , 13, 313–332

The number of loci, numbers of alleles and allele

frequencies are important variables in the calcula-

tion of probability of two genetic profiles matching.

Using data from just five of the 10 STR gives a very

strong probability for diagnostic identification, while

inclusion of eight or more of the loci gives proba-

bilities of match less than 3.0)08 (i.e. there is less

than a one in 10 million chance of two random

whales matching at eight or more of the 10 STR

loci) (Table 3). This is the probability that two given

profiles should match by chance. Of more direct

interest is the probability that a given (market)

sample should match one or more entry in the DNA

register by chance, which for a register size of 7644

is given by 76 443.0)08 = 0.0002, still a small

number. This superfluity of loci is an efficient way of

dealing with genotyping error, in that even if

requiring only nine of ten matching loci, the

probability of a match by chance is still effectively

zero.

Table 2 Numbers of individuals represented in the Norwegian minke whale DNA register (NMDR) sorted by year.

Year

DNA

register1

IWC catch

statistics2

Not

landed3 Landed4 Duplicates5

Missing

samples6

Lab

problem7

Total

missing8

1997 488 503 7 496 3 5 0 8

1998 609 625 11 614 1 4 0 5

1999 571 591 17 574 2 1 0 3

2000 469 487 6 481 4 8 0 12

2001 538 552 11 541 2 1 0 3

2002 625 634 9 625 0 0 0 0

2003 637 647 9 638 1 0 0 1

2004 530 544 7 537 7 0 0 7

2005 626 639 6 633 3 4 0 7

2006 531 545 7 538 4 2 1 7

2007 580 597 5 592 6 6 0 12

2008 511 536 4 532 149 7 0 21

2009 474 485 1 484 8 1 1 10

2010 455 468 2 466 5 6 0 11

Total 7644 7853 102 7751 60 45 2 107

1Number of unique individuals contained in the DNA register (not containing duplicates).2Number of individuals caught by Norway, including individuals not landed.3Number of individuals killed, but not taken onboard the vessel.4Number of individuals taken onboard the vessel.5Number of occurrences of (tissue) sample switching on board the vessel as detected by comparison of genetic profiles. The result is

that two samples have been returned from one individual, and no sample has been returned for one individual.6Number of individuals for which tissue samples are missing for other reasons than sample switching.7Genetic laboratory not able to obtain microsatellite profile from tissue sample.8The difference between the columns ‘Landed’ and ‘DNA register’.9Among these were two triplets (three samples taken from the same individual, on the expense of two other individuals).

Table 3 Probability of genetic profiles matching by chance at k out of 10 STR loci in the Norwegian minke whale DNA

register (NMDR).

No. of loci (k ) 0 1 2 3 4 5 6 7 8 9 10

No. of matches 1 168 8084 1 116 1550 4 628 099 1 105 486 168 222 17 145 1246 72 1 0 0

Probability 0.406 0.388 0.161 0.038 0.006 6.0E-04 4.3E-05 2.5E-06 3.0E-08 0 0

Probabilities were evaluated empirically as the proportion of pairwise comparisons within the register that matched at exactly k loci. The

analysis was based on a subset of the register (7586 individuals) not being involved in duplicate pairs. It is noted that the probability of

matching at eight loci is based on only one match and is hence not accurately estimated.

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Checking meat sold on the Norwegian market

Samples of whale meat purchased on the Norwe-

gian market in 1999 and 2000 were checked by an

international group who found no evidence of illicit

trade (Palsbøll et al. 2006). However, no routine

checking of whale products in the Norwegian

market has been conducted. This is primarily

because there has been no reason to suspect illegal

harvest in this period. This is a consequence of the

fact that the harvest is strictly regulated in several

forms (i.e. remote sensor data and inspectors

onboard in the early stages) and, not least, that

the annual quota has always exceeded the annual

catch which means that there are few incentives to

conduct illegal harvest. Nevertheless, to validate the

register’s continuing function, a total of 25 whale

meat samples, from a range of outlets (Fig. 3), were

purchased in 2010 and 2011 and analysed here.

These samples were genotyped for STRs according

to the standard protocol for the NMDR (Data S2).

The resulting genetic profile for these samples was

then checked against the DNA register for all

samples in the period 1997–2010.

Twenty-four of the 25 samples matched at all loci

to single whales in the register (Table 1; Data S3).

Most of the samples originated from whales cap-

tured in 2010 (17), although some samples from

both 2009 (4) and 2008 (3) were found on the

market. Meat from the harvest in 2007, or earlier

seasons, which would be past the permitted sale by

date of 3 years, was not found.

A single whale product, purchased from a super-

market chain outlet located in the east of Norway

(sample 8 in Table 1 and Data S3), did not match

any whale in the register (closest match was a

whale captured in 1997 where only six of ten STR

loci matched). At the outset, a sample purchased in

the market that fails to match directly with a sample

in the register could reflect evidence of illicit trade.

However, missing samples (Table 2) make this more

complicated. Over the period 2007–10, the propor-

tion of missing samples was (12 + 19 + 10 + 11)/

(592 + 532 + 484 + 466) = 52/2074 = 0.025

(Table 2). From the binomial law, it follows that the

probability of all market samples out of 25 should be

contained in the DNA register is only 0.34, i.e.

finding one or more missing sample is a likely event

(P = 0.66).

To investigate further the sample of whale meat

not matching to any profile in the register, the

NMDR was inspected for samples captured by the

company selling this unmatched sample. The com-

pany selling this specific product trade only in meat

from their own whaling vessel. Further investiga-

tion revealed that their vessel failed to take a DNA

sample from one individual in 2008 (their only

‘missing sample’ in the period 2005–10 from over

250 whales captured). It was concluded very

probable that the purchased meat came from the

whale captured in 2008 where the DNA sample was

not taken. This is due to the fact that the sex

reported by the vessel and as revealed by the genetic

analyses matched, none of the other meat pur-

chased from this company deviated from the regis-

ter, the company had meat of this harvest year/age

in the market (two of the three other identified

samples from 2008 were purchased from this

supplier), the company does not trade meat from

other whaling boats (and no evidence to the

contrary was found here), and the company

reported that they had sold meat to this specific

commercial outlet.

Export of whale products

2008 marked the first year that Norwegian com-

panies conducted international trade of whale

products since the NMDR was established. In total,

whale products for human consumption have been

exported from <50 individuals harvested in the

period 2008–10. This has been conducted by a

limited number of companies in strict regulation of

the NDF who issued the export licence. In addition

to meeting food regulation criteria required for

export, the legitimacy of these whales was docu-

mented by presenting all genetic data together with

the whale meat that was sent for export. This was

addressed in the form of official papers from the NDF

detailing whale number in the NMDR and its

genotypic data supplied by the IMRb. Thus, the

legitimacy of the whale meat exported from Norway

to Japan was checked by Norway prior to export

and by Japan upon entry. Clearly, so long as only

meat from whales where a DNA profile exists are

exported, international trade of whale products

would not be subject to the missing sample

challenges observed for monitoring meat traded on

the domestic market.

It is possible for other laboratories or independent

third parties to monitor and control international

trade of whale products even though interlaborato-

ry calibration for STR analyses is challenging

(Pasqualotto et al. 2007; Baric et al. 2008; de Valk

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et al. 2009). This could be done by other laborato-

ries calibrating as was successfully done in the case

of the NMDR (Haaland et al. 2011) or by creating

an allelic ladder from known samples as conducted

when the NMDR was checked by an independent

international laboratory (Palsbøll et al. 2006).

Scientific research arising from the NMDR

In addition to its primary function of monitoring

commercial trade of whaling derived products, data

included in the NMDR have been used in a series of

scientific studies conducted ad hoc (Table 4). Several of

these were only possible owing to the existence of the

register and result from the accumulation of biolog-

ical, demographic and genetic data over time. In

addition to studies listed, the register is actively being

used for a variety of studies including population

genetic analyses, genetic mark-recapture, migration

behaviour, studies of relatedness among individual

and demographic structure in the population.

Time-series data sets represent a major resource

to understand a range of processes. In the future,

it is likely that this sort of data will permit an

increasing number of studies where the long-term

dynamics of the population(s) can be studied

in demographic and genetic context. Given tissue

and DNA storage, there is for example the

possibility in the future to start matching these

biological data to large suites of single nucleotide

polymorphism markers (SNPs), to understand

greater how the demographics and genetics are

linked.

Discussion

Future of the NMDR – looking to human DNA data

bases and SNPs

The NMDR is expected to exist as a control system

for the legal capture of minke whales under

Norwegian quota for the foreseeable future. It is

Table 4 Summary of published scientific studies where data from the Norwegian minke whale DNA register (NMDR)

formed the basis of the study.

Data used from register Main results Reference

mtDNA, micro, bio, catch Genetic assignment techniques permitted the first documentation

of Balaenopthera bonaerensis (Antarctic minke) in the Arctic and the

first documentation of hybridization between minke whale species

(Glover et al. 2010b)

Micro, catch Individual sample match to register permitted identification of

minke whale offal in the stomach of Greenland shark (Somniosus

microcephalus). Linked the whale(s) and shark(s) in space and

time

(Leclerc et al. 2011)

Micro Re-analysis of samples from 1996 to 2008 permitted further

elucidation of STR genotyping errors when combined with mixed

models and documented genotyping quality in register

(Haaland et al. 2011)

mtDNA, micro Analysis of 20 samples purchased on Norwegian market, and two

stranded whales in Denmark tested the register’s function.

(Palsbøll et al. 2006)

mtDNA, micro, bio, catch Mother and foetus DNA profiles compared to infer (half of)

father’s profile. This paternal profile was subsequently matched

against the NMDR, and a small number of fathers were identified.

(Skaug and Øien 2005)

mtDNA, micro, bio, catch The NMDR (years 1997–2002) was screened for pairs of closely

related individuals. In total, 21 pairs were inferred. One female

was common to three pairs, having a parent–offspring

relationship to each of the three other individuals, yielding

information about promiscuity in minke whales.

(Skaug et al. 2008, 2010)

mtDNA, micro, bio, catch Population genetic studies with focus on testing IWC hypotheses

about stock structure.

(IWC 2009a)

mtDNA = analysis of mtDNA, micro = analysis of STR data including sex marker, bio = use of biological data (weight length etc.),

catch = use of catch data (position, time).

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therefore not a question if the register is continued

but rather an issue about how it is continued.

Single nucleotide polymorphisms (SNPs) are

being projected as the new class of genetic marker

that may overtake STR analyses for all but a small

range of highly specialized uses (Seeb et al. 2011).

The rapid development in new generation sequenc-

ing technologies permitting the identification of

large resources of SNPs in non-human and non-

model organisms (Hudson 2008; Garvin et al.

2010), in addition to the rapid development of

semi-automated genotyping technologies, is helping

to drive these attentions. Nevertheless, despite the

fact that most disciplines within human genetics are

considerably more advanced than for other species,

human DNA forensic data bases are still based upon

STRs and not SNPs. For example, the UK National

DNA data base (UK NDNAD) is built upon a single

multiplex of 10 STR loci and the amelogenin sex

marker (see Cotton et al. 2000), and the Federal

Bureau of Investigation combined DNA index sys-

tem (CODIS) includes a set of 13 STR loci and the

amelagenin sex marker (Budowle et al. 1998). The

transition from STR to SNP loci has not occurred

thus far despite the fact that validated forensic

panels of SNPs exist for humans (Dixon et al. 2005;

Kidd et al. 2006; Pakstis et al. 2007; Pomeroy et al.

2009) and that the forensic science community

appears to regularly re-evaluate this situation (Gill

2001; Gill et al. 2004; Amorim and Pereira 2005).

However, many of the arguments for maintaining

STR analyses as opposed to converting to SNPs for

human data bases are linked specifically to the

nature of these data bases and would not be

relevant for a transition in the NMDR. This is

because human DNA registers contain huge

amounts of data for highly robust and validated

and highly efficient STR multiplexes, and many of

tissue/DNA samples have not been stored, thus

prohibiting re-analysis with SNPs, re-analysis would

in any case be highly resource demanding, and that

mixtures of tissues are not effectively addressed by

biallelic markers. However, unlike human DNA

data bases where persons breaking the law may be

at large for decades following a crime (permitting

start of a cold-case), whale meat is not expected to

be stored and enter the commercial market for more

than ‘a few years’. Consequently, it would be

possible for the NMDR to complete a transition

from STRs to SNP markers without necessitating

re-analysis of the previous samples. Furthermore,

given that the NMDR is based upon three STR

multiplexes, in addition to mtDNA analyses via

sequencing in both directions, the time to analyse

any given set of samples is considerably higher for

the NMDR than for a human register largely based

upon a single multiplex amplification of all STR

markers. Consequently, production and establish-

ment of SNP multiplexes including mtDNA SNPs,

which could be species specific, could potentially

replace and considerably improve analytical time

and cost for the NMDR. For other marine species

where a similar type of register is established to

monitor a strictly controlled fishery or harvest, it is

likely that SNPs represent the most appropriate

marker class of genetic marker upon which to base

the register.

Individual-based DNA registers: challenges and

opportunities

There are a wide range of technical, logistical, legal

and economic issues linked with establishing and

operating any DNA register. For example, the

budget relating to the collection, registration, stor-

age and genetic analysis of samples in the NMDR is

approximately 500 000 USD annually. Looking at

DNA registers for monitoring trade of fisheries and

wildlife products in general, some of the challenges

have been previously discussed (e.g. Palsbøll et al.

2006; Baker 2008; Ogden et al. 2009; Alacs et al.

2010). In addition, challenges linked with the

application of a DNA register for wildlife forensic

applications, such as the documentation required in

connection with the chain of custody of ‘suspect

samples’ and validation of marker robustness in

highly degraded tissues, have been addressed (e.g.

Ogden et al. 2009). Here, we concentrate on points

linked with the implementation of a DNA register

for the specific purpose of individual identification

against a register of legally sampled individuals to

monitor harvest and trade.

Two major logistical challenges have been iden-

tified through operation of the NMDR. These include

missing DNA profiles for whales that have been

captured legally and entered the domestic market,

and, the fact that the register is only ‘updated’ and

thus fully operation once the products have entered

the market.

At the outset, a sample not matching any profile

in the register may indicate illegal harvest and from

this, the obvious defence argument would be to

blame the missing sample. However, as previously

discussed (Palsbøll et al. 2006), so long as the

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326 � 2011 Blackwell Publishing Ltd, F I S H and F I S H E R I E S , 13, 313–332

number of missing samples is not too high, and it is

possible to permit ad hoc verification of movements

of such samples into the market if necessary (Fig. 2),

then it is likely to be possible to detect any such

attempts of fraud. Sampling ‘backwards’ in the

supply chain could reveal if there are several or just

one missing samples present in the supplier’s

products and/or to verify trade routes. This individ-

ual sample tracking approach has been successfully

used to link two ends of a supply chain for a blue

whale (Balaenoptera musculus) traded in a Japanese

market (Cipriano and Palumbi 1999).

While viable, it is not ideal to have to apply an ad

hoc approach to adjust for missing samples in an

individual-based register as described earlier. Fur-

thermore, the problem of missing samples is likely to

represent a challenge experienced by all individual-

based DNA registers and is not unique to the NMDR.

However, where licences for partaking in the fishery

or hunt are required, as is the case for the

commercial harvest of minke whales in Norway,

the opportunity to fine companies for each sample

they fail to take, and revoke permits upon repeat-

edly failing to take tissue samples of some whales

exists. This could be used as a way to reduce the

frequency of missing samples. An alternative

approach could be to implement a system whereby

tissue samples are presented upon landing.

At the present, the quality-checked data for any

seasons catch are entered into the NMDR at least

6 months after the time at which this meat is

available in the market as fresh or frozen product.

The delay between harvest and updated register is

due to the fact that samples are only sent to IMRt

ready for entry in the register once the season has

ended, and all samples are collated, in addition to

the laboratory analytical time (months). Therefore,

any attempts to detect illegal trade would represent

an ad hoc approach similar to the spot-checks

reported here, and as conducted previously (Pals-

bøll et al. 2006). Clearly, if samples were presented

and registered at the time of landing as indicated

above, this would not only help alleviate the

likelihood for missing samples, it also offers the

potential to speed up the rate at which each whale

entered the register, so long as samples were

registered and analysed as and when they came in.

However, while this could in principle work, it

would cause a great strain on all persons involved

in the register as this would mean that staff and

facilities would have to be on stand-by during the

whole season. The unpredictable catch, influenced

by weather and other factors, would lead to dead

periods followed by intense periods where the

majority of the samples suddenly arrive. In addi-

tion to strain on the staff involved, this would also

challenge the quality checks of remote sensor data

and fishing log books as conducted at the end

of each season prior to samples being sent for DNA

analysis (Fig. 1). It is therefore questionable

whether such an approach would be viable for

the NMDR, especially given that the low number of

operators and companies involved in the logistics

of trading whale meat on the Domestic Norwegian

market (Fig. 2) does permit ad hoc sampling to

monitor and potentially identify evidence of illegal

Table 5 Interaction between some of the key attributes of the commercial Norwegian minke whale harvest, and the

operation of an individual-based DNA register to monitor and regulate harvest and trade.

Attribute Consequence

Low to moderate harvest size (N ) Relatively simple logistics for collection and analysis of samples, including data storage

High economic value per-unit

harvested

Favourable genotyping unit per harvest unit cost. Thus economically feasible maintenance

of an individual sample-based DNA register

Strictly regulated harvest High degree of compliance of whalers associated with the hunt to adhere to regulations, fill

out additional catch forms and take samples for analyses

Few boats involved in harvest Relatively simple logistics for administration, regulation and enforcement of the hunt and

register

Limited and well-defined market

including supply chain

Good opportunity to actively monitor the market and potentially unveil illegal harvest and

trade. Results in higher potential for compliance and thus a more sustainable harvest

CITES listed species A non-economic-based incentive for implementing a DNA register as part of a sustainable

harvest

The Norwegian minke whale DNA register K A Glover et al.

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trade. Nevertheless, use of genetic data in ‘real-

time’ fisheries management is achieved in some

regions, and if samples were analysed as and when

they arrived in, potentially combined with freezing

meat and only releasing it into the market once

the register is updated, could be solutions for other

harvests (see below).

Some of the key elements characterizing the

commercial hunt for minke whales in Norway, and

how these influence viability of the NMDR itself, are

listed (Table 5). There are several important attri-

butes linked with the minke whale hunt that make

establishment and operation of a DNA register for

the primary purpose of individual sample identifica-

tion feasible. Firstly, the commercial harvest of

minke whales is highly regulated, whales have a

high commercial and ecological value per unit, and

a moderate number of individuals are captured each

season. In addition, the low number of companies

involved in the harvest itself, and the well-defined

supply chain and commercial market (Fig. 2), per-

mits good opportunity to both monitor and regulate.

Together, these contribute to the registers logistical

and economic viability to monitor and regulate the

harvest. It is likely that DNA registers with the

primary purpose to track individual samples, as for

the NMDR, will only be viable if many of these key

characteristics are present or there are mitigating

characteristics. For example, the application of DNA

registers to monitor individual samples for a low per-

unit value species that are potentially harvested in

their millions, from geographically broad regions, by

a wide range of countries and companies, traded

through extensive networks, as is the case for the

majority of fish species commercially harvested in

the world’s oceans, is not going to be viable in the

foreseeable future. Naturally, the use of genetic tools

in the regulation of fisheries falling into this category

is, and will continue to be, of upmost importance in

the future given that most of the worlds fisheries are

overfished and or recovering from over-exploitation

(FAO 2010), and the major global challenges with

IUU fishing (Agnew et al. 2009). However, regula-

tion of such fisheries using genetic data will need to

be based upon species identifications for semi-

processed or fully processed products (Rasmussen

and Morrissey 2008) and establishing data bases

over populations to regulate population and poten-

tially geographical site of exploitation (Ogden 2008;

Stokstad 2010).

Whales and other marine mammals are exploited

by a range of countries for various reasons, includ-

ing aboriginal, commercial and scientific. At the

present, around 1500 individuals of baleen whales

caught annually for these purposes (IWC 2009b). In

addition, several thousand animals are caught

through directed catches of small cetaceans as well

as in many fisheries involving cetacean by-catch

problems. While parts of this harvest is strictly

regulated, such as the commercial exploitation of

minke whales in Norway as described here, chal-

lenges experienced by the fin-fish fishing communi-

ties such as IUU fishing (Ainsworth and Pitcher

2005; Agnew et al. 2009) and by-catch (Harring-

ton et al. 2005; Diamond and Beukers- Stewart

2011; Lewison et al. 2011) also exist for some

whaling operations. For example, genetic monitor-

ing of fish markets in Asia where whales harvested

from by-catch and scientific whaling are traded has

revealed significant evidence of unreported exploi-

tation of species (Baker et al. 2006), in addition to

underreporting in the number of harvested individ-

uals (Dalebout et al. 2002; Baker et al. 2007;

Lukoschek et al. 2009). Clearly, the individual

whale register approach outlined in the present

article has the ability to be implemented into many

of these harvesting operations. In turn, this could

assist in the legitimization of sustainable whaling,

especially if the registers to be established were

transparent and validated by a panel of interna-

tional scientists.

Although the range of limitations associated with

implementing DNA registers to monitor individual

samples may limit their applicability to many com-

mercial fin-fish fisheries, their implementation will

not necessarily be limited to commercial exploitation

of whales. There are a number of fish species that

have high commercial or ecological value and that

are in need of better regulation. For example, there is

growing demand to increase the use of DNA-based

methods for the monitoring and regulation of

exploitation of sharks and rays that are in sharp

decline (Shivji et al. 2002, 2005; Clarke et al. 2006;

Dulvy et al. 2008). Furthermore, many fish from the

suborder Scombroidei (tunas, mackerels and billfish)

display challenging fisheries management problems,

not least for the highly valued bluefin tuna (Thunus

thynnus) (MacKenzie et al. 2009; Kurota et al. 2010;

Vinas et al. 2011; Webster 2011). There is clearly

potential to implement DNA registers to monitor

individual samples captured in some of these directly

or indirectly targeted fisheries, which in turn may

permit the successful sustainable exploitation of

some of these species.

The Norwegian minke whale DNA register K A Glover et al.

328 � 2011 Blackwell Publishing Ltd, F I S H and F I S H E R I E S , 13, 313–332

For species that are exploited at very low levels

(either directly or as part of a harvest following

mortal by-catch), population-based assignments

may not be possible, especially if the genetic baseline

is incomplete and/or complicated. Here, DNA reg-

isters monitoring trade in individual samples may

offer the only ability to monitor commercial exploi-

tation and verify legitimacy of highly valued prod-

ucts.

Conclusions

The NMDR register, which has been operated in the

period 1997-present, possibly represents the only

fully operational DNA register implemented to

monitor the commercial exploitation of a marine

species, at the individual sample level. The close

interaction of the NMDR, regulatory authorities

(NDF) and the whalers themselves provides an

example of how a highly regulated marine harvest

can be conducted, in addition to how an individual-

based DNA register can be implemented to monitor

and control the sustainable harvest of marine

resources. While not without operational and

logistical challenges, the experiences gained

through operation of the NMDR clearly illustrate

that DNA registers to track individual samples are

viable. Furthermore, they may serve an important

preventative effect to IUU exploitation. Where some

of the basic conditions are met (Table 5), there is

potential for implementing similar registers to

strictly regulate the sustainable harvest of other

important marine species. Given the rapidly increas-

ing numbers of SNP markers in non-model organ-

isms, rapid ongoing developments in genotyping

throughput and the continued decrease in genotyp-

ing costs, the list of species which such an approach

is viable will expand in the future.

Acknowledgements

We would like to acknowledge Anne G. S. Eide for

conducting laboratory work for the 25 whales

tested within and analysis of the 2010 year class.

We would like to acknowledge Dr Andy J. Hopwood

from the Forensic Science Service in UK for discus-

sions regarding human DNA registers. We acknowl-

edge helpful discussion on earlier drafts of this

manuscript with Hild Ynnesdal from the Norwegian

Directorate of Fisheries. The editor and three anon-

ymous referees are acknowledged for constructive

criticism on earlier drafts of this manuscript.

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Supporting Information

Additional Supporting Information may be found in

the online version of this article:

Data S1. Equipment and instructions sent to

commercial whalers for taking tissue samples to be

used in the Norwegian minke whale DNA register

(NMDR).

Data S2. Laboratory protocol for genetic analy-

ses conducted at the Institute of Marine Research

(IMR), in Bergen.

Data S3. Exert from the Norwegian minke whale

DNA register (NMDR). Data is illustrated for 25

samples purchased from Norwegian shops in 2010

and 2011, genotyped, then matched to its entry in

the register.

Please note: Wiley-Blackwell are not responsible

for the content or functionality of any supporting

materials supplied by the authors. Any queries

(other than missing material) should be directed to

the corresponding author for the article.

The Norwegian minke whale DNA register K A Glover et al.

332 � 2011 Blackwell Publishing Ltd, F I S H and F I S H E R I E S , 13, 313–332