megafaunal assemblages from two shelf stations west of svalbard

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Megafaunal assemblages from two shelf stations westof SvalbardMelanie Bergmann a , Nina Langwald a , Jörg Ontrup b , Thomas Soltwedel a , IngoSchewe a , Michael Klages a & Tim W. Nattkemper ba Deep-Sea Research Group, Alfred Wegener Institute for Polar and Marine Research,Bremerhaven, Germanyb Biodata Mining and Applied Neuroinformatics Group, Bielefeld University, Germany

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ORIGINAL ARTICLE

Megafaunal assemblages from two shelf stations west of Svalbard

MELANIE BERGMANN1*, NINA LANGWALD1, JORG ONTRUP2, THOMAS

SOLTWEDEL1, INGO SCHEWE1, MICHAEL KLAGES1 & TIM W. NATTKEMPER2

1Deep-Sea Research Group, Alfred Wegener Institute for Polar and Marine Research, Bremerhaven, Germany, and 2Biodata

Mining and Applied Neuroinformatics Group, Bielefeld University, Germany

AbstractMegafauna plays an important role in benthic ecosystems and contributes significantly to benthic biomass in the Arctic. Thedistribution is mostly studied using towed cameras. Here, we compare the megafauna from two sites located at differentdistances from the Kongsfjord: one station at the entrance to the fjord, another on the outer shelf. Although they are onlylocated 25 km apart and at comparable depth, there were significant differences in their species composition. While theinshore station was characterized by shrimps (2.5792.18 ind. m�2) and brittlestars (3.219 3.21 ind. m�2), the offshoresite harboured even higher brittlestar densities (15.2399.32 ind. m�2) and high numbers of the sea urchinStrongylocentrotus pallidus (1.2391.09 ind. m�2). Phytodetrital concentrations of the upper sediment centimetres weresignificantly higher inshore compared with offshore. At a smaller scale, there were also differences in the composition ofdifferent transect sections. Several taxa were characterized by a patchy distribution along transects. We conclude that thesedifferences were caused primarily by habitat characteristics. The seafloor inshore was characterized by glacial softsediments, whereas the station offshore harboured large quantities of stones. Although the use of a new web-2.0-based tool,BIIGLE (http://www.BIIGLE.de), allowed us to analyse more images (�90) than could have been achieved by hand, taxonarea curves indicated that the number of images analysed was not sufficient to capture the species inventory fully. Newautomated image analysis tools would enable a rapid analysis of larger quantities of camera footage.

Key words: Arctic, image analysis, megafauna, seafloor photograph, Svalbard

Introduction

Megafauna plays an important role in benthic

ecosystems and contributes significantly to benthic

biomass (e.g. Schwinghamer 1981; Lampitt et al.

1986; Christiansen & Thiel 1992), particularly in

the Arctic (Piepenburg et al. 1996). Megafauna

inhabits the sediment�water interface and is defined

as the group of organisms ]1 cm (Grassle et al.

1975; Rex 1981). They contribute considerably to

benthic respiration (Smith 1983; Smith Jr et al.

1993; Piepenburg et al. 1995) and have a strong

effect on the physical and biogeochemical microscale

environment (Huettel & Gust 1992; Smith Jr et al.

1993; Bett et al. 2001; Lochte & Pfannkuche 2002;

Guillen et al. 2008; Sumida et al. 2008). Megafaunal

organisms create pits, mounds and traces that

enhance habitat heterogeneity and thus, diversity of

smaller sediment-inhabiting biota (Soltwedel &

Vopel 2001; Hasemann 2006; Queric & Soltwedel

2007). Erect biota such as sponges or coldwater

corals enhance three-dimensional habitat complexity

and present shelter from predation (e.g. Collie et al.

1997; Kaiser et al. 1999). Megafaunal predators

control the population dynamics of their prey and

therefore shape benthic food webs and community

structure (e.g. Gray 1981; Feder & Pearson 1988;

Freire 1996; Sarda et al. 1998; Gallucci et al.

2008a). Benthic megafauna sequester carbon

through the continuous redistribution of organic

matter, oxygen and other nutrients in surficial

sediments (Bett et al. 2001; Ruhl 2007; Vardaro

et al. 2009; FitzGeorge-Balfour et al. 2010). An

understanding of megafaunal dynamics is therefore

vital to determine the probable fate of carbon at the

*Correspondence: Melanie Bergmann, Deep-Sea Research Group, Alfred Wegener Institute for Polar and Marine Research, Am

Handelshafen 12, 27570 Bremerhaven, Germany. E-mail: [email protected]

Published in collaboration with the University of Bergen and the Institute of Marine Research, Norway, and the Marine Biological Laboratory,

University of Copenhagen, Denmark

Marine Biology Research, 2011; 7: 525�539

(Accepted 11 October 2010; Published online 1 August 2011; Printed 12 August 2011)

ISSN 1745-1000 print/ISSN 1745-1019 online # 2011 Taylor & Francis

DOI: 10.1080/17451000.2010.535834

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seafloor, the world’s largest carbon sink (Ruhl et al.

2008). Despite their importance, knowledge about

megafaunal assemblages is scarce because of limita-

tions in adequate quantitative sampling gears for this

size fraction, logistic difficulties associated with

sampling and the effort required for analyses.

Traditionally, bottom trawls were used to sample

megafauna (e.g. Frauenheim et al. 1989; van

Leeuwen et al. 1994), also in polar waters (Voß

1988; Piepenburg et al. 1996). However, they have

low and variable catch efficiencies for different biota

(e.g. Lindeboom & de Groot 1998; Reiss et al.

2006) and are destructive. In recent years, towed

camera systems have become the key method to

investigate deep-dwelling megafauna (e.g. Hecker

1994; Nybakken et al. 1998; Bluhm 2001; Bluhm

et al. 2005; Jones et al. 2007a; Ruhl 2007). They

enable us to study the seafloor at the scale of

kilometres without disturbing habitats (Solan et al.

2003), which is particularly important as megafauna

are often characterized by a rare or aggregated

occurrence (Gutt & Starmans 2003; Thistle 2003;

Soltwedel et al. 2009). Camera footage still allows

us to discern spatial patterns at a high resolution and

shows the organisms in situ. Images therefore

provide information about habitat features such as

sediment properties, bottom currents, geological

and biogenic structures, tracks, detrital aggregations

or biotic interactions.

Although the Svalbard area may be subject to

climate forcing (Soltwedel et al. 2005; Hop et al.

2006; Forest et al. 2010) and despite the fact that the

Kongsfjord has been free of ice for three winters

(2006�2008) (Arctic Frontiers Symposium 2008),

the last published study on megafaunal shelf assem-

blages was conducted in 1991 (Piepenburg et al.

1996) using trawls. Other studies focused on the

shallower parts of the Kongsfjord (Jørgensen &

Gulliksen 2001; Sahade et al. 2004; Beuchel et al.

2006; Beuchel & Gulliksen 2008). Camera surveys in

the European Arctic concentrated on east Greenland

(Mayer & Piepenburg 1996; Piepenburg & Schmidt

1996b; Piepenburg et al. 1997; Starmans et al. 1999;

Jones et al. 2007b) and the Laptev (Piepenburg &

Schmidt 1997) and Barents Seas (Piepenburg &

Schmidt 1996a). Here, we compare the megafaunal

composition and distribution of two different sites

located at a different distance from the Kongsfjord:

one station at the entrance to the fjord, another

farther out on the outer shelf.

Material and methods

Study area

Two stations, which are part of a Norwegian time

series, were selected for benthic surveys to comple-

ment the current primarily pelagic data set within

the framework of the StatoilHydro-funded project

KongHAU (‘The Kongsfjord-HAUSGARTEN

transect case study: Impact of climate change on

Arctic marine community structures and food

webs’). The two stations Kb0 and V12 (hereafter

referred to as ‘inshore’ and ‘offshore’, respectively)

are at comparable water depths (Table I) and located

at the entrance of the open Kongsfjord and some

36 km to the west (Figure 1). The Kongsfjord is of

glacial origin. It is influenced by the West

Spitsbergen Current, the northernmost extension

of the North Atlantic Current (Hop et al. 2002) and

by the input of cold glacial freshwater, which results

in steep gradients in salinity and sedimentation rates

inside the fjord (Hop et al. 2002). While the West

Spitsbergen Current carries warmer water masses

with temperatures B28C and higher salinities the

arctic coastal water current transports colder

(B08C) arctic water masses (Piepenburg et al.

1996; Hop et al. 2002). Located at the fjord

entrance, the inshore station may also receive higher

quantities of nutrients and terrigenous material.

Sampling procedure

Two photographic transects were taken by an Ocean

Floor Observation System (OFOS) yielding 983

images in total (inshore: 484, 3.596 km; offshore:

499, 3.692 km) during RV Polarstern expedition

Table I. Summary of OFOS transects and sampling for voucher-specimens and sediments.

Station Station no. Date LatitudeN LongitudeE Depth (m) Gear

Inshore PS72/106-3 6/7/08 79801.64? 11804.85? 287 Box corer

Inshore PS76/136-3 7/7/10 79801.71? 11805.08? 291 MUC

Inshore PS72/106-4 6/7/08 79803.48? 11804.27? 259 OFOS start

Inshore 79801.56? 11805.79? 281 OFOS end

Offshore PS72/107-1 6/7/08 78859.07? 09831.11? 242 AGT start

78858.63? 09827.52? 225 AGT end

Offshore PS76/135-4 7/7/10 78858.88? 09831.01? 233 MUC

Offshore PS72/107-4 6/7/08 78858.73? 09829.80? 230 OFOS start

Offshore 7/7/08 78857.25? 09822.82? 223 OFOS end

Notes: AGT, Agassiz trawl; OFOS, Ocean Floor Observation System; MUC, multiple corer.

526 M. Bergmann et al.

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ARK XXIII/2 in 2008 (Table I). The OFOS frame

(120�110�120 cm, 385 kg) was equipped with a

still (BENTHOS, model 372-A) and a black and

white video camera (OKTOPUS), laser pointers

(Scholz), telemetry (AdiTech-Koax), forerunner

weight (20 cm rope length), two xenon head lamps

(OKTOPUS) and two flash lights (BENTHOS

flash, model 383). A constant aperture of 5.6 and

a double flash (600 WS) were used. The three laser

pointers were fixed at a distance of 52 cm to each

other and served as a size reference for the imaged

area. The still camera was mounted in a vertical

position to the seafloor to enable accurate density

estimates. It was loaded with a 30 m Kodak

Ektachrome 100 ASA film and triggered automati-

cally every 30 s to avoid spatial overlap of successive

pictures. The OFOS was towed for 4 h at ca 0.5

knots and a target altitude of 150 cm (indicated by

the position of the forerunner weight). It was

controlled by the winch operator who, relied on

the video display. The ship’s log book was consulted

to determine the transect lengths and water depths.

In addition, physical samples were taken by an

Agassiz trawl and a box corer (for gear specifications

see Bergmann et al. 2009) at the offshore and inshore

station, respectively (Table I). Inspection of fixed

voucher-specimens by taxonomic experts (see

Acknowledgements) enabled ground-truthing of

some of the megafaunal organisms recorded from

images (Table II). Species annotated with a ‘?’ refer to

those species observed on images that resemble vou-

cher-specimens, but there was some uncertainty due to

image quality. Voucher specimens are kept at the AWI.

During RV Polarstern expedition ARKXXV/2 in

June 2010 a video-controlled multiple corer (MUC)

was deployed at both stations (Table I) to collect

undisturbed sediment samples to determine the

phytodetrital flux to the seafloor. Three subsamples

were taken from different MUC cores with cut-off

syringes and analysed at 1-cm intervals down to

5 cm sediment depth. The bulk pigments registered

by this method were termed chloroplastic pigment

equivalents (CPE) (Thiel 1978). They were ex-

tracted in 90% acetone and measured with a Turner

fluorometer (Yentsch & Menzel 1963; Holm-

Hansen et al. 1965). Unfortunately, all MUC

deployments in 2007 at the offshore station failed

due to the presence of large stones.

Image analysis via BIIGLE

The digitalized images were uploaded onto the

BIIGLE (BioImage Indexing, Graphical Labelling

and Exploration) web-2.0 database. BIIGLE was

Figure 1. Location of the inshore and offshore station off the Kongsfjord, Svalbard.

Megafaunal assemblages from west of Svalbard 527

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Table II. Mean densities and dispersion properties (Ip) of megafaunal taxa recorded from photographic transects taken inshore and offshore

off the Kongsfjord entrance. (*) indicates voucher samples from a box corer (inshore) or an Agassiz trawl (offshore). (�) indicates presence

of a species.

Inshore Offshore

Taxon Mean SD Max Ip Mean SD Max Ip

Porifera

Porifera 0.01 0.05 0.51 0.02 0.09 0.71

Artemisina apollinis (Ridley & Dendy, 1886)* 0.04 0.18 1.08 �0.03 0.14 0.27 1.21 0.99

Tedania suctoria Schmidt, 1870* �Myxilla sp.* �Microcionidae* �

Cnidaria

Halecium muricatum (Ellis & Solander, 1786)* �

Halecium scutum Clark, 1976* �Stegopoma plicatile (Sars, 1863)* �Gersemia rubiformis (Ehrenberg, 1834)* 0.06 0.18 1.08 0.51 0.27 0.47 2.66 97.29

Alcyonacea � � � � 0.01 0.07 0.64

Anthozoa 0.05 0.14 0.68 1.13 0.07 0.20 1.16 �0.09

Actiniaria 0.04 0.17 1.35 0.11 0.24 1.10 0.33

Hormathia digitata (Muller O.F., 1776)* �Hormathia nodosa (Fabricius, 1780)* �Actinostolidae* �Actinidae gen.1 sp.1* �Actiniidae sp. cf. Epiactis sp.* �Ceriantharia � � � � 0.01 0.05 0.40

Mollusca

Leptochiton sp.* �

Gastropoda 0.04 0.15 0.79 0.07 0.01 0.06 0.45

Frigidoalvania janmayeni (Friele, 1878)* � �Lepeta caeca (Muller O.F., 1776)* �Solariella obscura (Couthouy, 1838)* �Oenopota sp.* �Cylichna sp.* �Philine finmarchica M.Sars, 1859* �Coryphella salmonacea (Couthouy, 1838)* �Tachyrhynchus reticulatus (Mighels & Adams, 1842)* �Volutopsius norwegicus (Gmelin, 1791)* �Ciliatocardium ciliatum (Fabricius, 1780)* �Neptunea despecta (Linnaeus, 1758)* �Colus sabini (Gray, 1824)* �Nuculana pernula Muller O.F., 1779* �Yoldiella solidula Waren, 1989* �Yoldiella propinqua (Leche, 1878)* �Astarte montagui (Dillwyn, 1817)* �Similipecten greenlandicus (Sowerby G.B. II, 1842)* �Cryptonatica affinis (Gmelin, 1791)* �Chlamys islandica (Muller O.F., 1776)* �Hiatella sp.* �Sepiolidae* �

Nemertea* �Annelida

Serpulidae 0.03 0.13 0.72 �0.03 0.65 1.07 6.49 0.50

Sabellidae* �Chone sp.* �Branchiomma sp. Kolliker, 1858* �Jasmineira cf. schaudinni Augner, 1912* �Pherusa sp.* �Leitoscoloplos mammosus* Mackie, 1987* � �Myriochele heeri Malmgren, 1867* �Myriochele cf. oculata (Zaks, 1922)* �Gattyana cirrhosa * �Harmothoe sp.* �Eunoe nodosa (M.Sars, 1861)* �Bylgides elegans (Theel, 1879)* �


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Table II (Continued)

Inshore Offshore


Bylgides groenlandicus (Malmgren,1867)* �Polynoidae* �Artacama proboscidea Malmgren, 1866* �Neoamphitrite affinis (Malmgren, 1866)* �Terebellides sp.* �Chaetozone spp.* �Cirratulus sp.* �Euphrosine sp.* �Brada granulosa Hansen, 1882* �Brada inhabilis (Rathke, 1843)* �Maldanidae* �Maldane sarsi Malmgren, 1865* �Maldane cf. arctica* �Chrimia biceps (M.Sars, 1861)* �Nicomache lumbricalis (O.Fabricius, 1780)* �Praxillura longissima Arwidsson, 1906* �Nephtys ciliata (O.F.Muller, 1776)* �Nothria conchylega (M.Sars, 1835)* �Prionospio sp.* � �Laonice cf. cirrata (M.Sars, 1850)* � �Laonice sp.* �Spiophanes kroeyeri Grube, 1860* �Syllis cornuta Rathke, 1843* �Scoletoma fragilis (O.F.Muller, 1776)* � �Lumbrinereidae * �Lysippe labiata Malmgren, 1866* �Amphicteis gunneri (M.Sars, 1835)* �Anobothrus gracilis (Malmgren,1866)* �Eteone flava (O.Fabricius, 1780)* �Eteone foliosa Quatrefages, 1865* �Phyllodocidae*

Spiochaetopterus typicus M.Sars, 1856* �Heteromastus filiformis (Claparede, 1864)* �Capitella capitata agg. (O.Fabricius, 1780)* �Pholoe cf. assimilis Orsted, 1845* �

Sipunculidae

Phascolion strombus (Montagu, 1804)* �Golfingia margaritacea (Sars, 1851)* �Nephasoma diaphanes Cutler et al., 1984* �

Pycnogonida

Colossendeis proboscidea (Sabine, 1824) 0.08 0.24 1.55 �0.46 � � � �Nymphon hirtipes? Bell, 1853* �

Crustacea

Munnopsis typica M. Sars, 1861* �Phoxocephalus holbolli (Kroyer, 1842)* �Paramphithoe hystrix (Ross, 1835)* �Halirages fulvocincta (M. Sars, 1858)* �Arrhis phyllonyx (Sars, 1858)* �Oedicerotidae* �Haploops sp.* �Stegocephalopsis ampulla (Phipps, 1774)* �Aristias tumidus (Kroyer, 1846)* �Themisto sp.* �Amphipoda � � � � 0.01 0.07 0.71

Hyas spp.* 0.03 0.12 0.83 0.00 0.05 0.46

Caridea* 2.57 2.18 10.70 0.50 0.04 0.15 0.89 0.39

Pandalus sp.* �Sclerocrangon sp.* �Crustacea 0.21 0.39 1.71 0.03 0.05 0.23 1.77 �0.06

Bryozoa

Myriapora coarctata (M. Sars, 1863)* � � � � 0.32 0.56 2.46 �0.41

Dendrobeania cf. fruticosa (Packard, 1863)* �


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developed within the framework of the StatoilHy-

dro-funded project CORAMM (Coral Risk Assess-

ment, Monitoring and Modelling) to accelerate and

ease the time-consuming process of manual image

analysis (Ontrup et al. 2009; Schoening et al. 2009).

It works in a standard web browser and can be used

to browse and label (�annotate) images (http://

www.BIIGLE.de, login: test, password: test) (Figure

2). The programme allows a network of remote

biologists or taxonomists to simultaneously label

visible biota in images. It therefore enhances ex-

change of (taxonomic) knowledge and transparency/

quality assurance of image analyses. Although BII-

GLE provides information on the location sampled,

the images are currently not geo-referenced.

Each transect was subdivided into thirds and 30

images selected from each transect section to test if

the taxonomic composition varied along the length of

the transect. To label an object, the appropriate taxon/

habitat label was selected from a drop-down menu to

the right of the BIIGLE window. The curser was then

positioned upon the appropriate object and labelling

completed by mouse click (Figure 2). Laser points

were labelled in the same fashion. Labelling was done

in a shaded room using the same computer monitor

(Dell, 19 inch). All biota and habitat features

recognized at maximum zoom were annotated with

label categories. Figure 3 shows examples of biota

frequently seen in images. Larger features such as

detrital fluff or soft corals were outlined with a

rectangle tool. Unidentifiable features were labelled

‘unknown’. Buried brittlestars were only labelled if

two or three arms and the disc were visible to avoid

double-counting. Images were excluded if they con-

tained sediment clouds, large quantities of reflecting

particles, if the illumination was too strong or low,

and/or if the distance from the bottom was exceed-

ingly large. Every image was analysed three times to

even out learning effects. To improve the accuracy of

density estimates, the well-illuminated area of each

image was outlined with the rectangle tool after

completion of all labelling processes. The area

calculations were based on the area within this frame,

and only labels inside this frame were computed to the

output table (csv file, Figure 2). The table details the

number of labels per label category and an area

Table II (Continued)

Inshore Offshore


Echinodermata

Crossaster papposus (Linnaeus, 1776)* � � � � 0.03 0.12 0.62 1.08

Icasterias panopla (Stuxberg, 1878)* � � � � 0.01 0.05 0.49

Pedicellaster typicus M. Sars, 1861* �Ctenodiscus crispatus (Retzius, 1805)* �Henricia perforata (O.F. Muller, 1776)* �Pteraster cf. pulvillus (M. Sars, 1861)* �Asteroidea 0.02 0.10 0.62 0.95 0.03 0.12 0.71 0.39

Ophiuroidea 3.21 3.21 14.00 0.50 15.23 9.32 84.90 0.50

Ophiura sarsii* Lutken, 1855* � �Ophiacantha bidentata (Bruzelius, 1805)* �Ophiura robusta (Ayres, 1851)* �Ophiopholis aculeata (Linnaeus, 1767)* �Strongylocentrotus pallidus Linnaeus, 1758* 0.15 0.39 2.00 0.34 1.23 1.09 6.04 �0.02

Eupyrgus scaber Lutken, 1857* �

Urochordata

Ascidiacea � � � � 0.005 0.05 0.46

Osteichthyes

Zoarcidae 0.005 0.05 0.44 0.01 0.08 0.71

Lycodes gracilis Sars, 1867* �Gymnelus sp.* �Gadus morhua Linnaeus, 1758 0.39 0.69 3.03 0.32 0.04 0.16 0.84 0.09

Anarhichas minor Olafsen, 1772 0.004 0.04 0.41 � � � �Lumpenus lampretaeformis? (Walbaum, 1792)* 0.01 0.05 0.36 0.02 0.09 0.71

Artediellus atlanticus Jordan & Evermann, 1898* �Hippoglossoides platessoides? (Fabricius, 1780)* 0.01 0.08 0.72 0.01 0.06 0.49

Pisces 0.02 0.09 0.61 0.005 0.05 0.45

Chondrichthyes

Amblyraja radiata (Donovan, 1808)* 0.01 0.05 0.52 � � � �

Highest densities and an aggregated distribution are indicated by bold type, italicized numbers indicate a random distribution; SD, standard

deviation; Max, maximum.


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Figure 2. Image from the offshore station labelled by BIIGLE via a regular web browser. The white rectangle outlines the area used for

analysis. Symbols represent different taxon or feature labels. The cod (Gadus morhua), for example, was marked with a yellow circle.

AA BB CC DD

FF

EE

GG

HH II JJ KK LL

MM NN PPOO QQ RR

AA BB CC DD

FF

EE

GG

HH II JJ KK LL

MM NN PPOO QQ RR

Figure 3. Examples of megafauna from the inshore and offshore station off the Kongsfjord: (A) Artemisina apollinis, (B) Gersemia rubiformis,

(C) Actinidae, (D) Hormathiidae, (E) Actinidae, (F) Ceriantharia, (G) Strongylocentrotus pallidus, (H) Serpulidae, (I) Lumpenus

lampretaeformis?, (J) Caridea, (K) Myriapora coarctata, (L) Ophiuroidea, (M) Anarhichas minor, (N) Amblyraja radiata, (O) Hippoglossoides

platessoides?, (P) Icasterias panopla, (Q) Colossendeis proboscidea, (R) Gastropoda.


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estimate based upon the distance between the three

laser points for each image.

Data analysis

The output table enabled us to calculate megafaunal

densities (individuals m�2) and to test for correla-

tions between habitat features and megafaunal

composition. ‘Habitat structure’ refers to the general

structure of the habitat, i.e. homogenous vs. hetero-

geneous. For example, a coverage of �60% of either

sand/mud or stones was considered homogenous.

Heterogeneity was assumed, if the ratio was 1:1

stones/mud. ‘Habitat type’ refers to the predominant

habitat, thus sand/mud, stony and stones/mud

(Collie et al. 2000). Species accumulation curves

were drawn to assess if the number of images

analysed were sufficient to describe the megafaunal

composition of each transect (Soltwedel et al. 2009).

Shannon�Wiener diversity (Shannon & Weaver

1963) and Pielou’s evenness (1969) was computed

for each image. Standard (non-)parametric tests

(e.g. one-way analysis of variance, Kruskall�Wallis

test) were used to compare the indices from both

sites. Routines from multivariate statistics (PRIMER

6.1.6) enabled us to determine differences in the

taxonomic composition between transects and trans-

ect parts based on Bray�Curtis similarity analysis.

All density data were �-transformed to counteract

the effect of very abundant taxa. Those taxa, which

accounted for B0.1% of all counted individuals in

all images, were excluded to reduce error (Mayer &

Piepenburg 1996). Cod were omitted from this

analysis as they appeared to follow the OFOS:

some individuals were recognized in consecutive

images. In addition, where higher taxa labels existed,

rare species were attributed to the respective higher

taxon. The similarities of different images and

transects were depicted in an ordination biplot

(MDS, non-metric multidimensional scaling). The

ANOSIM routine was used to test for differences in

the species composition of images from different

transects and transect sections. The BIOENV pro-

cedure was applied to identify the image features

(i.e. habitat structure, habitat type, worm tubes,

burrow entrances, traces, sea urchin test, shells,

(drop-) stones, white debris, detrital fluff), which

explain the taxonomic composition observed, best.

The calculation was based on Spearman’s rank

correlation. The spatial dispersion (i.e. the distribu-

tion of individuals along a transect) of key taxa was

assessed by Morisita’s standardized index Ip (Smith-

Gill 1975) using a custom-written macro (Schroder

2005). Index values indicate a random (�0),

aggregated (]0.5) or uniform distribution (]0.5).

Results

The time spent per image for labelling and control

checks ranged from 15 to 30 min. Because of time

constraints, 190 images, or an area of 440.9 m2

(inshore: 220 m2, offshore: 220.9 m2) was analysed

in total. The area covered per image varied between

0.57 m2 and 3.71 m2 (mean: 2.3290.56 m2

standard deviation). The seafloor of the inshore

station was characterized mostly by fine brown

mud or sand, with the occasional occurrence of

pebbles and cobbles, especially towards the end of

the transect. The offshore station harboured many

small and large stones, which corresponds with large

quantities of stones collected by trawl at this site.

Taxon area curves

The taxon area curves of the offshore and inshore

stations were characterized by a steep gradient,

which flattened slightly after some 40 and 80 images

at the offshore and inshore station, respectively

(Figure 4). However, an asymptote was not reached,

indicating that more images need to be analysed to

capture the species composition fully. Twenty-five

and 21 taxa were recorded from the offshore and

inshore station, respectively (Table II).

Species recorded

Twenty-eight taxa were labelled in total (Table II), 12

of which were identified to species level. Twenty-six

per cent of all biota carried the label ‘unknown’ and

were excluded from analyses. Of the identified biota

inshore, ophiuroids (46.1%) and shrimps (37.4%)

accounted for the highest densities. Although all

trawled specimens of shrimps were lost, photographs

of the specimens suggest the presence of four species

(possibly Pandalus borealis Krøyer, 1838, Sabinea

septemcarinata (Sabine, 1824), Lebbeus polaris

(Sabine, 1824), Sclerocrangon sp.), which could not

be distinguished on images from the seafloor. The

0

5

10

15

20

25

0 20 40 60 80 100

Number of images analysed

Cu

mu

lati

ve t

axo

n c

ou

nt

Kb0 V12

Figure 4. Taxon area curve for camera transects taken at the

inshore (91 images) and offshore (96 images) station off the

Kongsfjord.


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offshore station harboured even higher densities of

ophiuroids (83.2%), the sea urchin Strongylocentrotus

pallidus (6.7%) and serpulid tubes (3.5%). A tentacle

crown indicated that these were inhabited. All other

worm tubes were not counted since inhabited tubes

could not be distinguished from abandoned ones. As

worm tubes structure habitats (Rees et al. 2005), they

were considered a habitat factor instead. Since many

ophiuroids were partly buried, they could not be

identified to species level. The majority of the

ophiuroids collected by a trawl offshore belonged to

Ophiacantha bidentata (Bruzelius, 1805) followed by

Ophiura robusta (Ayres, 1851), Ophiura sarsii

(Lutken, 1855) and Ophiopholis aculeata (Linnaeus,

1767) (Table II). The most abundant sponge was

Artemisina apollinis, which often occurred together

with the soft coral Gersemia rubiformis. Anemones

cannot be identified to species level from images

alone (D. Fautin, pers. comm.). However, the trawl

caught Hormathia digitata (O.F. Muller, 1776), H.

nodosa (Fabricius, 1780), Tealidium cf. jungerseni

Carlgren, 1921, Actinostolidae and Actiniidae off-

shore (Table II). Not many fish other than cod (Gadus

morhua Linnaeus, 1758), which occurred in densities

as high as 6 ind. m�2, were recorded (Table II).

Differences between transects

Megafaunal densities offshore (18.31910.06 ind.

m�2) were more than twice as high as those from

inshore (7.0493.30 ind. m�2) (Mann�Whitney

U-test: PB0.0001). They ranged between 1.60

and 18.65 ind. m�2 and 3.15�90.20 ind. m�2 at

the inshore and offshore transect, respectively. The

inshore station harboured much higher densities of

cod (0�6 ind. m�2) compared with the offshore site

(0�3 ind. m�2), but these data have to be treated

with care as the fish appeared to follow the OFOS.

There were no significant differences between the

species diversity from the inshore (mean: 0.6990.40

standard deviation) and offshore station (0.6390.30)

(Mann�Whitney: P�0.12, W�9571.5). Evenness

was significantly higher inshore (0.7090.18) com-

pared with the offshore transect (0.4590.16)

(t�9.63, PB0.0001, df�176), indicating domi-

nance of fewer species offshore. Certain species, e.g.

the bryozoan Myriapora coarctata, the starfish

Crossaster papposus and Icasterias panopla were only

recorded offshore whilst the wolf fish Anarhichas

minor was exclusively found inshore (Table II).

ANOSIM also indicated significant differences in

the species composition from the two stations (global

R�0.72, P�0.001), which are reflected in the

grouping of the MDS plot (Figure 5). The species

composition was best explained by a combination of

the four variables ‘habitat type, worm tubes, tracks

and detrital fluff ’ (BIOENV, r�0.524, P�0.01),

although a combination of the two variables ‘habitat

type and worm tubes’ ranked only marginally lower

(r� 0.516, P�0.01). The density of worm tubes

was significantly higher inshore (21.3916.2 ind.

m�2) compared with the offshore transect (1.69

0.2 ind. m�2) (Mann�Whitney: PB0.0001). The

density of tracks was also significantly higher inshore

(0.5190.72 ind. m�2) compared with the offshore

transect (0.0590.02 ind. m�2) (Mann�Whitney:

Figure 5. MDS plot depicting the megafaunal composition from

transects taken inshore and offshore and respective transect

subsections (inshore: circles; offshore: squares; (white) start

section; (grey) middle section; (black) end section of transect).

A stress value of 0.12 indicates a good two-dimensional repre-

sentation of the data.

Chloroplastic pigment equivalents (µg ml-1)

0-1

1-2

2-3

3-4

4-5Offshore

0 10 20 30 40 50 60 70 80 90 1000 10 20 30 40 50 60 70 80 90 100

0-1

1-2

2-3

3-4

4-5

Sed

imen

t d

epth

(cm

)

Chlorophyll A

Phaeopigment

Inshore

Figure 6. Gradients of phytodetrital concentrations (CPE) in the upper 5 sediment cm of the inshore and offshore station off the

Kongsfjord. While chlorophyll a (black) represents fresh plant matter phaeopigments (grey) stand for refractory material.


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PB0.0001). In addition, the inshore harboured

significantly more burrows (0.1490.03 ind. m�2)

than the offshore transect (0.0390.02 ind. m�2)

(Mann�Whitney: P�0.0012). The concentrations of

phytodetrital matter in the top sediment cm were

significantly higher inshore compared with the

offshore station (Figure 6, t-test, P�0.017). The

chlorophyll a concentrations of the upper 2 cm were

significantly higher at the inshore cf. offshore station

(t-test, PB0.05). Only the top cm of sediment of

the inshore station contained significantly higher

phaeophytin concentrations cf. samples taken off-

shore (t-test, PB0.05).

The results of the SIMPER routine indicated an

average similarity of 53.4% for images from the

inshore and 65.7% for those from the offshore

station. The dissimilarity between the two sites was

68.6%. Images from the inshore transect were

characterized by shrimps and ophiuroids, constitut-

ing 95.5% of all species recorded. The offshore

transect was characterized by ophiuroids, S. pallidus

and serpulids which accounted for 93.9% of all

megafauna observed. Ophiuroids, shrimps and

S. pallidus contributed most to the differences in

the species composition (Table III).

Differences between transect sections and dispersion

Results from ANOSIM indicated that the middle

section of the inshore station had a different species

composition compared with its start and end section

(R�0.55; R�0.79, Table IV), which is also reflected

in the grouping of the MDS plot (Figure 5).

A BIOENVanalysis indicated that tests of sea urchins

and (drop-)stones explained the taxonomic composi-

tion best (r�0.45, P�0.01). There were no clear

differences in the species composition of different

sections of the offshore transect (Table IV, Figure 5).

All megafaunal organisms taken together were

patchily distributed along both transects (Ip�0.50

at both stations). Five out of 12 and 13 taxa tested

showed evidence of patchiness inshore and offshore,

respectively (Table II). Several taxa had an aggre-

gated distribution (G. rubiformis, C. papposus, ophiur-

oids) at both transects. Others had a clumped or

random distribution at only one of the two stations.

Some species had neither a patchy nor a clumped

distribution. Only pycnogonids (probably Colossen-

deis proboscidea) at the inshore transect and the

bryozoan M. coarctata at the offshore transect,

approached an Ip of �0.50, which indicates a uniform

distribution.

Discussion

Species inventory

Two species were recorded from images and trawls,

which were not reported in the comprehensive study

by Piepenburg et al. (1996) or others working in the

area: the sponge Artemisina apollinis and the soft

coral Gersemia rubiformis. While G. rubiformis is

distributed from the Arctic to Cape Hatteras,

Cobscook Bay and the Gulf of St. Lawrence

(WoRMS 2010) A. apollinis has so far been reported

from the Antarctic 200 nautical miles zone beyond

the coastline, European waters and the Kerguelen

EEZ (van Soest 2010).

The taxon area curves indicated that the number

of images analysed was not sufficient to fully

describe the species inventory. Although Jones

et al. (2007b) analysed an area, which was approxi-

mately twice as large as ours, their taxon area curves

resembled the shape of ours. This implies that areas

more than twice as large need to be analysed to

capture the species inventory sufficiently. Many

other studies analysed fewer images and/or did not

undertake such an evaluation (e.g. Mayer & Piepen-

burg 1996, Piepenburg & Schmid 1996b, 1997;

Ambrose et al. 2001; Bluhm et al. 2005). As manual

analysis is very time- and labour-intensive, auto-

mated detection tools would enable the rapid

analysis of larger numbers of images (Purser et al.

2009). Nevertheless, the use of BIIGLE allowed the

analysis of greater image quantities than could have

been achieved without this tool. Manual image

analysis would not allow the annotation of indivi-

Table III. Contribution of megafaunal taxa to dissimilarities in

the taxonomic composition from the inshore and offshore station

off the Kongsfjord (SIMPER routine).

Taxon Contribution (%) Cumulative (%)

Ophiuroidea 33.99 33.99

Caridea 20.53 54.52

Strongylocentrotus pallidus 12.38 66.89

Serpulidae 7.19 74.09

Gersemia rubiformis 4.73 78.81

Myriapora coarctata 4.39 83.21

Crustacea 3.64 86.85

Artemisina apollinis 2.78 89.63

Actiniaria 2.52 92.14

Table IV. Results from ANOSIM routine testing similarity of

different transect sections. Bold face denotes significantly different

megafaunal compositions.

Station Sections compared R p

Inshore 1, 2 0.55 0.001

1, 3 0.36 0.001

2, 3 0.79 0.001

Offshore 1, 2 0.14 0.001

1, 3 0.29 0.001

2, 3 0.21 0.001


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duals. Therefore, the analyser could not return as

easily to the image at a later stage to assess which

organisms had been marked and which were over-

looked the first time. The data cannot be corrected

as easily for learning effects. Manual area estimates

based on measurements taken by a ruler can be

assumed to be less accurate than those computed

automatically by BIIGLE. BIIGLE thus allowed us

to obtain more accurate results. It also enables

subsequent quality assurance by peers.

Species abundances

Piepenburg et al. (1996) reported that Ophiacantha

bidentata was the most prominent species (at 21 of

25 stations) around Svalbard waters. Brittlestars also

dominated megafaunal assemblages off the north-

east Greenland shelf (Piepenburg & Schmid 1996b;

Starmans et al. 1999), the Laptev (Piepenburg &

Schmid 1997) and Chukchi Seas (Ambrose et al.

2001). Similarly, ophiuroids were the most impor-

tant taxon recorded at both stations and O. bidentata

was the dominant ophiuroid in a trawl from the

offshore station.

While Piepenburg & Schmid (1996b) reported 10

epibenthic taxa in photographic transects from 54

stations off northeast Greenland, we recorded

12 species (plus 16 higher taxa) at only two stations.

This indicates a higher species richness off Svalbard.

The prevailing warmer West Spitsbergen Current

may allow the presence of boreal species off the

Kongsfjord (Hop et al. 2002), whereas sea ice

coverage and colder water temperatures may limit

the species number off northeast Greenland.

Furthermore, the species richness off northeast

Greenland may have changed since the 1990s in

response to the effects of climate variation.

The high densities of cod at the inshore station

highlight the need for a monitoring programme as a

small fleet of fishing boats has already started to

target this stock in recent years. With the retreat of

the sea ice and decreasing fish stocks in northern

Europe, fishing intensity may increase even more,

which could also affect the bottom communities

(Collie et al. 1997; Kaiser et al. 1999).

Differences between transects

Surprisingly, megafaunal densities were more than

twice as high offshore as those inshore although

the food supply (phytodetrital concentrations) at

the inshore station, which is located closer to the

fjord entrance, was higher. Even though phytode-

trital input may have been different in 2007,

detrital ‘fluff ’ was solely observed in images from

inshore and contributed significantly to differences

in the taxonomic composition. Bottom tempera-

tures were similar at both stations (inshore:

1.248C, offshore: 1.488C; Bauerfeind unpublished

data). The differences in densities may therefore be

rather a consequence of different seafloor charac-

teristics. The offshore station was characterized by

large quantities of stones that provide substrata for

epilithic species (Mayer & Piepenburg 1996;

Schulz et al. 2010), which are readily recorded

by cameras. The inshore station with its soft

sediments of glacial origin may favour less con-

spicuous infaunal organisms leading to lower

megafaunal density estimates. The higher densities

of indicators of infaunal activity such as worm

tubes, tracks and burrow entrances at this site,

corroborate this belief. Our megafaunal densities

are higher than those reported from comparable

depths at SE Greenland (Jones et al. 2007b), but

lower than those from NE Greenland and the

Chukchi Sea (Starmans et al. 1999; Ambrose

et al. 2001).

In general, well-structured heterogeneous envir-

onments such as our offshore station are assumed to

offer suitable substrata for different taxa and, thus,

increase diversity (Collie et al. 2000). However, our

results indicate similar diversities at both stations. By

contrast, evenness was even lower offshore implying

dominance. This was probably a result of very high

ophiuroid densities. High ophiuroids densities also

contributed to low evenness at the banks off north-

east Greenland (Piepenburg & Schmid 1996b).

The two transects analysed differed in their

species composition. The inshore transect was

characterized by ophiuroids and shrimps (probably

mostly Pandalus borealis). Pandalus borealis is the

most common shrimp in the Kongsfjord area and

commercially caught at depths �120 m (Hop et al.

2002). The higher shrimp densities inshore may

reflect P. borealis’ preference for soft sediments (Hop

et al. 2002). By contrast, the offshore station was

characterized by ophiuroids, Strongylocentrotus

pallidus and serpulids. The high incidence of stones

at this transect provided the substrate needed for

serpulids and first-rate grazing grounds for sea

urchins. Strongylocentrotus pallidus occurred in den-

sities of 520�30 m�2 at the northeast Greenland

shelf and in the northern Barents Sea and grazed

primarily on epibionts on stones (Bluhm et al. 1998;

Piepenburg & Schmid 1996b).

Generally speaking, the power of our analyses

would have benefitted from replicate camera tows at

both stations. Unfortunately, this was not possible

because of ship time constraints.


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Dispersion

In agreement with data from NE Greenland (Gutt

& Starmans 2003), several taxa were characterized

by an aggregated distribution. Aggregation is

caused by intra- and interspecific interactions

and/or environmental drivers, such as food avail-

ability or habitat heterogeneity (Gutt & Starmans

2003). The long-lived soft coral Gersemia rubiformis

was one of the few taxa that had a clumped

occurrence at both stations. It reproduces via

planula larvae, which are usually not dispersed

very far from the parent colony (Cimberg et al.

1981). While Gilkinson et al. (2005) reported a

patchy occurrence of G. rubiformis off eastern

Canada, Gutt & Starmans (2003) reported a

random dispersion for soft corals off NE

Greenland. Gersemia rubiformis rely on hard sub-

strata for attachment (Gilkinson et al. 2005) such

that their dispersion is probably driven by the

distribution of stones.

Ophiuroids were also characterized by an aggre-

gated distribution at both stations, which concurs

with the patchy ophiuroid distributions in the

NW Barents Sea, the NE Greenland shelf,

HAUSGARTEN (Piepenburg & Schmid 1996a;

Piepenburg & Schmid 1996b; Gutt & Starmans

2003; Soltwedel et al. 2009), boreal waters (e.g.

Brun 1969; Metaxas & Giffin 2004) and the tropics

(Lewis & Bray 1983) to name just a few studies.

Piepenburg & Schmid (1996a) suggested that the

distribution of brittlestars is controlled largely by

predation pressure. However, although ophiuroids

accounted for the highest densities recorded their

densities appeared to be lower than those reported

from elsewhere (Piepenburg & Schmid 1996a). This

could be due to locally higher levels of predation

pressure or differences in food availability. The

preceding warm winters and decreased ice cover

may have led to decreased food supplies (Schewe &

Soltwedel 2003; Forest et al. 2010) affecting ophiur-

oid population dynamics.

Still, even within the confines of our study area,

certain species had an aggregated distribution at

one station but not at the other, which was also

reported for megafaunal taxa from SE Greenland

(Jones et al. 2007b) and HAUSGARTEN

(Soltwedel et al. 2009). The sponge Artemisina

apollinis and serpulids, for example, had a clumped

distribution offshore but not inshore. Gutt &

Starmans (2003) suggested that ecological mechan-

isms, which cause patchiness, are sometimes effec-

tive and sometimes not. Both taxa rely on hard

substrata for attachment, which was more promi-

nent offshore and probably not evenly distributed

along the transect.

Consideration of species’ dispersion is crucial

when settling on transect lengths and/or the

number of images to be analysed. Short camera

transects or the analysis of small subsets of images

may lead to underestimates of megafaunal densities

and diversity. However, the manual analysis of

large quantities of footage is unfeasible as it is too

labour-intensive, time-consuming and error-prone

(Culverhouse et al. 2003). Automated object

detection could expedite this lengthy process and

increase the consistency of image analyses but

currently there is a substantial lack of image

processing tools to support high throughput image

analysis (MacLeod et al. 2010). Purser et al.

(2009) used machine-learning algorithms to

estimate coral coverage automatically. Similarly,

the labels gained via BIIGLE in this study could

be used to train a machine to automatically detect

key species or habitat features in the future. This

would allow us to improve our species inventory

and to discern spatial patterns of megafaunal

organisms at larger scales.

Acknowledgements

We thank the officers and crews of RV Polarstern for

their professional help and assistance at sea.

M. Ginzburg assisted with the phytodetrital analyses.

D. Janussen (sponges, Forschungsinstitut und Nat-

urmuseum Senckenberg), A. Pena (hydroids, Uni-

versidad de Valencia), E. Rodriguez (anthozoa,

American Museum of Natural History, New York),

L. v. Ofwegen (soft coral, National Museum of

Natural History, Leiden), S. Gromisz, M. Kedra J.

Legezynska and P. Kuklinski (polychaetes, sipuncu-

lids, amphipods and bryozoa, Institute of Oceanology

of the Polish Academy of Sciences), R. Bramber

(pycnogonids, Natural History Museum, London),

A. Waren (molluscs, Swedish Museum of Natural

History), A. Dilman, A. Mironov and A. Rogacheva

(asteroids, echinoids, holothuroids, P.P. Shirshov

Institute of Oceanology), M. Damerau (ophiuroids,

Institut fur Polarokologie) and P.R. Møller (fishes,

Zoological Museum Copenhagen) all kindly identi-

fied specimens from reference samples and/or

images. This work was part of the StatoilHydro-

funded projects CORAMM (Coral Risk Assessment,

Monitoring and Modelling) and ‘KongHAU’ (The

Kongsfjord-HAUSGARTEN transect case study:

Impact of climate change on Arctic marine commu-

nity structures and food webs). KongHAU is closely

linked to the EU projects HERMES/HERMIONE.

The suggestions of three anonymous referees im-

proved an earlier version of the manuscript. This is

publication no. awi-n18867 of the Alfred Wegener

Institute for Polar and Marine Research.


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megafaunal assemblages from two shelf stations west of svalbard

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