Goldsworthy-Et-Al-Troph-2013.Pdf

Ecological Modelling 255 (2013) 38–57

Contents lists available at SciVerse ScienceDirect

Ecological Modelling

jo urnal homepage: www.elsevier.com/locate/ecolmodel

Trophodynamics of the eastern Great Australian Bight ecosystem: Ecological

change associated with the growth of Australia’s largest ﬁshery

a,∗ a,b a,c d a,e,b

Simon D. Goldsworthy , Brad Page , Paul J. Rogers , Cathy Bulman , Annelise Wiebkin ,

a,e,b a,e a,e,f a g

Lachlan J. McLeay , Luke Einoder , Alastair M.M. Baylis , Michelle Braley , Robin Caines ,

e a,c a,e a a

Keryn Daly , Charlie Huveneers , Kristian Peters , Andrew D. Lowther , Tim M. Ward

South Australian Research and Development Institute, Aquatic Sciences, 2 Hamra Ave, West Beach, South Australia 5024, Australia

Department of Environment, Water and Natural Resources, GPO 1047, Adelaide, South Australia 5001, Australia

School of Biological Sciences, Flinders University, GPO Box 2100, Adelaide, South Australia 5001, Australia

CSIRO Marine Research, GPO Box 1538, Hobart, Tasmania 7001, Australia

University of Adelaide, School of Earth and Environmental Sciences, North Terrace, Adelaide, South Australia 5005, Australia

Deakin University, Princess Highway, Warrnambool, Victoria 3280, Australia

University of South Australia, Mawson Lakes, South Australia 5095, Australia

a r t i c l e i n f o a b s t r a c t

Article history: We used the Ecopath with Ecosim software to develop a trophic mass-balance model of the eastern

Received 17 May 2012

Great Australian Bight ecosystem, off southern Australia. Results provide an ecosystem perspective of

Received in revised form 21 January 2013

Australia’s largest ﬁshery, the South Australian sardine ﬁshery, by placing its establishment and growth

Accepted 23 January 2013

in the context of other dynamic changes in the ecosystem, including: the development of other ﬁsh-

Available online 1 March 2013

eries; changing abundances of apex predator populations and oceanographic change. We investigated

the potential impacts of the sardine ﬁshery on high tropic level predators, particularly land-breeding

Keywords:

seals and seabirds which may be suitable ecological performance indicators of ecosystem health. Results

Eastern Great Australian Bight

indicate that despite the rapid growth of the sardine ﬁshery since 1991, there has likely been a negli-

Food web model

gible ﬁshery impact on other modelled groups, suggesting that current levels of ﬁshing effort are not

Ecopath with Ecosim

Sardine impacting negatively on the broader ecosystem structure and function in the eastern Great Australian

Sardinops sagax Bight. Results highlight the importance of small pelagic ﬁsh to higher trophic levels, the trophic changes

Fishing impacts that have resulted from loss and recovery of apex predator populations, and the potential pivotal role

of cephalopod biomass in regulating ‘bottom-up’ trophic processes. The ability to resolve and attribute

potential impacts from multiple ﬁsheries, other human impacts and ecological change in this poorly

understood region is highlighted by the study, and will be critical to ensure future ecologically sustainable

development within the region.

1. Introduction as important in marine ecosystems in the transfer of production

from plankton to higher trophic level species (marine mammals,

There is growing concern about the global impacts of increased seabirds and large predatory ﬁsh), and concerns about the poten-

ﬁshing effort on ecosystem structure and function. Much of this tial impacts on high trophic level species from localised depletion

concern stems from the growth of fisheries that target low trophic by fisheries has been identified by many studies (Cury et al., 2000,

level species (planktivorous small pelagic ﬁsh), which currently 2011; Jennings et al., 2012; Smith et al., 2011). Although some

∼

account for 30% of global landings (Ainley and Blight, 2009; studies have successfully demonstrated the relationships between

Branch et al., 2010). This growth has been largely driven by overﬁshing of low trophic level species and the impacts on higher

increased demand for ﬁsh meal production, feed or fertiliser for trophic levels, especially seabirds (Cury et al., 2011; Frederiksen

the aquaculture and agriculture industries and only a small portion et al., 2005; Jahncke et al., 2004; Myers et al., 2007), the numerical

is processed for human consumption (Alder et al., 2008; Merino and trophodynamic relationships between predators and prey are

et al., 2010; Naylor et al., 2009). Small pelagic ﬁshes are recognised poorly understood, even in regions where there are commercially

valuable ﬁsheries (Abrams and Ginzburg, 2000; Cury et al., 2011). As

such, numerical modelling of ecosystem dynamics is increasingly

∗ being utilised to resolve these complex relationships (see review by

Corresponding author.

E-mail address: [email protected] (S.D. Goldsworthy). Fulton, 2010) and to achieve ecosystem based ﬁshery management

S.D. Goldsworthy et al. / Ecological Modelling 255 (2013) 38–57 39

(EBFM) objectives (Pikitch et al., 2004). The latter is dependent The EGAB supports high densities of small pelagic ﬁshes,

on the development of reliable indicators of ecosystem status and the dominant species being sardine and anchovy (Engraulis

health (Cury et al., 2011; Lozano-Montes et al., 2011; Pikitch et al., australis) (Ward et al., 2006). Other important small pelagic

2004; Samhouri et al., 2009). The objectives underpin ecologically ﬁsh species include blue mackerel (Scomber australasicus), jack

sustainable development (ESD) frameworks that form the basis for mackerel (Trachurus declivis), yellowtail scad (T. novaezelandiae),

modern management of Australian ﬁsheries; however, there are redbait (Emmelichthys nitidus), maray (Etrumeus teres) and saury

few examples where they are achieved or put into practice. They (Scomberesox saurus). Primary and secondary production in the

include: (i) avoid degradation of ecosystems, (ii) minimise risk of EGAB appears to be underpinned by a unique northern bound-

irreversible change to assemblages of species and ecosystem pro- ary current system, the Flinders Current (Middleton and Bye, 2007;

cesses, (iii) obtain and maintain long-term socioeconomic beneﬁts Middleton and Cirano, 2002; van Ruth et al., 2010a, 2010b; Ward

without compromising the ecosystem, and (iv) generate knowledge et al., 2006), the dominant oceanographic feature of which is coastal

of ecosystem processes sufﬁcient to understand the consequence upwelling that occurs between November to May, especially off

of human actions (Pikitch et al., 2004). the Bonney Coast, Kangaroo Island and southern and western Eyre

The South Australian sardine (Sardinops sagax) ﬁshery (sar- Peninsula (McClatchie et al., 2006; Middleton and Bye, 2007; van

dine ﬁshery) is Australia’s largest ﬁshery by mass of catch. It was Ruth et al., 2010a, 2010b; Ward et al., 2006) (Fig. 1). This coastal

established in 1991 to provide feed for the southern blueﬁn tuna upwelling has oceanographic, biological and ecological similari-

(SBT, Thunnus maccoyii) mariculture industry in Port Lincoln, South ties to the larger and more productive eastern boundary currents

Australia (Fig. 1) (Ward et al., 2005). Operated as a purse seine ﬁsh- that underpin the Benguela, Humbolt, California and Canary Cur-

ery, sardine catch within this region is centred on southern Spencer rent upwelling systems (Mann and Lazier, 1996; Middleton and

Gulf, Investigator Strait and the western Eyre Peninsula in the east- Platov, 2003; Ward et al., 2006), although the latter typically have

ern Great Australian Bight (EGAB) (Ward et al., 2005). Spawning an order of magnitude higher productivity and small pelagic ﬁsh

∼

biomass of sardine was estimated to be 165,000 t in 1995 (Ward biomass compared to the EGAB (Guénette et al., 2008).

et al., 2009), but it declined by over 70% to ∼37,000 t in 1996 The rich pelagic resources of the EGAB underpin arguably the

following an unprecedented mass mortality event, recovered to greatest density and biomass of apex predators to be found in

∼146,000 t in 1998 and then declined by over 70% again to ∼36,000 t Australian coastal waters. These include marine mammals such as

in early 1999 following a second mass mortality event (Ward et al., pygmy blue whales (Balaenoptera musculus brevicauda), and >80%

2001). Between 1994 and 2001, ﬁshery catches ranged between of Australia’s populations of New Zealand fur seals (Arctocephalus

2500 and 6500 t each year, but the total allowable commercial forsteri) and Australian sea lions (Neophoca cinerea) (Branch et al.,

catch (TACC) was expanded and the harvest increased markedly 2007; Goldsworthy et al., 2003, 2009), and the Australian fur seal (A.

to 42,475 t in 2005, and then stabilising around 30,000 t from 2007. pusillus doriferus) (Shaughnessy et al., 2010). All seal species were

Fig. 1. Location of the eastern Great Australian Bight (EGAB) ecosystem included in the Ecopath with Ecosim model. The depth contours are 100, 200, 500, 1000 and 2000 m.

40 S.D. Goldsworthy et al. / Ecological Modelling 255 (2013) 38–57

subjected to early colonial sealing, with recovery of fur seal popula- of the EGAB ecosystem. Ecopath was developed by Polovina

tions commencing in the 1970s and 1980s (Goldsworthy and Page, (1984), based on a simple steady-state trophic box model, and

2007; Ling, 1999; Shaughnessy and McKeown, 2002). Other key further developed by Christensen and Pauly (1992) and Walters

apex predators include seabirds, such as short-tailed shearwaters et al. (1997). Whereas Ecopath enables description of the static

(Pufﬁnus tenuirostris), little penguins (Eudyptula minor) and crested state energy ﬂow of an ecosystem at a particular point in time,

terns (Sterna bergii); pelagic sharks including bronze whalers (Car- Ecosim enables dynamic simulations based on Ecopath parameters

charhinus brachyurus) and dusky shark (C. obscurus), white shark that allow the estimation of ecosystem response to environmental

(Carcharodon carcharias) and shortﬁn mako (Isurus oxyrinchus); perturbations. The Ecopath with Ecosim software has now been

and predatory ﬁshes, such as southern blueﬁn tuna and yellowtail used to describe a diverse range of aquatic ecosystems world-wide,

kingﬁsh (Seriola lalandi) (Copley, 1996; Goldsworthy et al., 2003; and details of the ecological theory and mathematical equations

Goldsworthy and Page, 2007; Ward et al., 2006). that underpin its key functions have been extensively detailed

The EGAB supports some of Australia’s most valuable ﬁsheries, elsewhere (e.g. Christensen and Walters, 2004; Grifﬁths et al.,

including four main Commonwealth and ﬁve main South Australian 2010; Piroddi et al., 2010; Shannon et al., 2008).

(State) managed ﬁsheries (Knight and Tsolos, 2010; Wilson et al.,

2009). The main Commonwealth ﬁsheries that operate are the 2.2. Model area and structure

southern blueﬁn tuna purse seine ﬁshery (SBT), GAB Trawl (GABT),

South East Trawl (SET), and shark gillnet component of the Gill Hook We modelled the eastern Great Australian Bight (EGAB) pelagic

and Trap ﬁshery (GHAT) (Wilson et al., 2009). The main South Aus- ecosystem, a region off the South Australian coast that includes con-

◦ ◦

tralian State managed ﬁsheries that operate in the region are the tinental shelf waters to 200 m depth between 132 E and 139.7 E.

sardine ﬁshery, southern rock lobster, abalone, western king prawn The model domain includes Investigator Strait and the mid-lower

and marine scalefish (MSF) fisheries (Knight and Tsolos, 2010). portions of Gulf St Vincent and Spencer Gulf where the sardine fish-

∼ 2

In recognition of the economic importance of the sardine ﬁshery, ery is centred. The total modelled area was 154,084 km (Fig. 1).

the important role of small pelagic ﬁshes in underpinning ecologi- This area was selected because the distribution and abundance of

cal processes in the EGAB ecosystem, and the high socio-economic sardine and other small pelagic ﬁsh species was well known from

and conservation signiﬁcance of the region’s marine predators, small pelagic ﬁsh ichthyoplankton surveys between 1995 and 2010

the fishing industry and fishery managers identified the need to (Ward et al., 2007, 2009).

manage potential ecological impacts. In response to this need, a As the aims of the model were to investigate the potential

large-scale ecosystem programme was initiated to assess the role impacts of the sardine ﬁshery on high tropic level predators,

of sardines in the EGAB ecosystem and to develop ecological perfor- especially land-breeding seals and seabirds, these groups were dis-

mance indicators and reference points for the ﬁshery. As part of this aggregated into single species where data on diet and population

programme, this study aimed to: (1) develop a food web model for biomass permitted. As we were also interested in the broad ecolog-

the EGAB and describe its temporal dynamics over the period since ical roles and importance of small pelagic ﬁsh in general, including

the sardine ﬁshery established in 1991 using time-series data of sardines, sardines, anchovies, jack mackerel, redbait, and other key

ﬁshing activity and environmental drivers; (2) identify the trophic mid-trophic level species such as arrow squid and calamary, were

interactions and functional groups most sensitive to variability in also examined as single-species functional groups where data per-

sardine biomass; (3) determine the sensitivity of land breeding mitted.

apex predators to changes in sardine biomass and ﬁshery catch, and A total of 40 functional and species groups were devel-

assess their appropriateness as ecological performance indicators oped based on species similarity in terms of diet, habitat,

for the sardine ﬁshery; (4) examine temporal changes to ecosystem foraging behaviour, size, consumption and rates of production

structure using ecosystem indicators and assess their potential as (Supplementary Information A and B). Intrinsic to Ecopath model

ecological performance indicators of ecosystem health; (5) exam- development, each trophic group operates as a single biomass,

ine the trophodynamic changes occurring in response to changes in despite groups often being composed of several species. The aggre-

apex predator biomasses, including recovering fur seal populations gation of species into trophic groups will therefore impact on model

and declining SBT populations and (6) examine how the recovery dynamics in some instances; however, by matching species for

of these groups is likely to impact on the EGAB ecosystem and the diet, consumption, and production rates we attempted to constrain

sardine ﬁshery. the errors and uncertainty of aggregating. The model was para-

Despite global recognition of the need to adopt sustainable meterised for 1991, when the sardine ﬁshery commenced. Model

approaches to the management of ﬁsheries and aquaculture simulations were run over the following 18 years (1991–2008).

(Pikitch et al., 2004), there are still few examples where EBFM For each trophic group, four inputs were derived from the avail-

has been adopted to complement the existing single-species/stock able data: diet, biomass, production per unit of biomass (P/B) and

management paradigm. The principal aim of this study was consumption per unit of biomass (Q/B). A dietary matrix was con-

to provide an ecosystem perspective of the sardine ﬁshery, by structed using empirical data derived within the EGAB ecosystem

placing its establishment and growth in the context of other where possible (Table 1). For marine mammals, seabirds, large and

dynamic changes in the ecosystem, including changes to other small pelagic ﬁshes, arrow squid and calamary, dietary data summ-

ﬁsheries, changes to apex predator populations, and meteorolog- arised by Page et al. (2011) was used (Table 1). For most other

ical and oceanographic changes. Such information is essential to ﬁsh species in the region, data from Currie and Sorokin (2010) was

−2

enhance EBFM of Australia’s largest pelagic ﬁshery by incorporat- used. Where possible, the biomasses (t km ) of functional groups

ing scientiﬁcally-based approaches for assessing and, if necessary, were estimated either from ﬁeld surveys or stock assessments. A

mitigating the ﬁshery’s trophic impacts. detailed description of the functional groups and how estimates of

biomass, P/B and Q/B were derived is presented as Supplementary

2. Materials and methods Information (A and B).

Fishery data on landings, discards and effort between 1991 and

2.1. Ecopath and mass balance approach 2008 were obtained from State and Commonwealth logbook data.

A total of 11 ﬁsheries (ﬂeets) operate within the EGAB ecosystem

We used the Ecopath with Ecosim software v 6.1.0 (Fig. 2, Tables 2 and 3). Six were South Australian (State) managed

(www.Ecopath.org) to develop a trophic mass-balance model ﬁsheries: the South Australian (SA) sardine, SA Marine Scaleﬁsh

S.D. Goldsworthy et al. / Ecological Modelling 255 (2013) 38–57 41 0.0163 0.5799 0.1960 0.0073 0.1841 0.0163 19

0.0137 0.7438 0.1197 0.1164 0.0064 18

0.0076 0.7604 0.1834 0.0292 0.0194 17

0.0303 0.0360 0.0909 0.0375 0.2164 0.0003 0.0909 0.0502 0.3771 0.0147 0.0108 0.0234 0.0092 0.0118 0.0002 16

0.0777 0.0447 0.0356 0.0433 0.5267 0.0370 0.1341 0.0232 0.0777 15

0.0606 0.0720 0.1818 0.0750 0.4288 0.1818 14

0.0045 0.0009 0.2219 0.7727 13

0.1000 0.1187 0.0964 0.0237 0.2790 0.0524 0.2032 0.1264 12

0.0133 0.0064 0.0818 0.0002 0.0288 0.0019 0.0781 0.2298 0.0072 0.0021 0.0004 0.0001 0.1904 0.2166 0.0814 0.0603 0.0012 11

0.0009 0.0586 0.0043 0.0016 0.0141 0.3072 0.2294 0.0783 0.0249 0.0567 0.1612 0.0007 0.0007 0.0527 0.0021 0.0037 0.0002 0.0029 10

0.3850 0.1100 0.0900 0.1600 0.0075 0.0200 0.0375 0.1500 0.0200 0.0200 9 model.

Ecopath 0.0153 0.0002 0.0509 0.0045 0.0044 0.0004 0.0002 0.0161 0.0104 0.0271 0.0004 0.0098 0.0361 0.0082 0.8161 8

EGAB

0.0006 0.0161 0.0441 0.6152 0.0353 0.0406 0.0885 0.0053 0.0075 0.0001 0.1137 0.0273 0.0055 7

balanced

the

0.0004 0.0025 0.0042 0.0954 0.0083 0.0010 0.0025 0.1097 0.0075 0.0022 0.0161 0.0151 0.0475 0.1472 0.1905 0.3029 0.0468 6 in

used

0.0640 0.0536 0.4489 0.3674 0.0029 0.0027 0.0012 0.0048 0.0460 0.0034 0.0051 5

0.0015 0.0010 0.0712 0.0011 0.0611 0.1186 0.0055 0.0109 0.0003 0.0145 0.0630 0.0375 0.0021 0.0043 0.0301 0.0050 0.2697 0.0022 0.0008 0.0013 0.0004 0.2979 4 contribution

prey

0.0862 0.0032 0.1137 0.4328 0.2082 0.0063 0.0170 0.0208 0.0019 0.0095 0.0124 0.0602 0.0248 0.0029 3

proportional

0.0406 0.0004 0.0153 0.0209 0.0013 0.0087 0.2326 0.0140 0.0467 0.0007 0.1337 0.2004 0.2846 2

showing

0.0250 0.4750 0.5000 1

matrix

1 2 3 4 5 6 7 8 9 10 20 30 40 22 36 27 24 37 16 34 29 35 Group 11 12 13 14 15 17 18 19 23 25 28 31 32 33 38 39 41 26 diet

their

and

piscs invert

ruffs

(infauna dolphin

sharks dolphin

skates

groups

and demersal demersal

lion

feeders

production seal

grazer small

sharks

whales

squid seal

name

tunas-kingﬁsh squids

demersal demersal demersal zooplankton bentho-pelagic zooplankton feeders

penguin

and

fur sea mackerel

mackerel

fur

planktivores (megabenthos) feeders piscs invert macrobenthos) piscs (carnivores) omnivore (herbivores) Group Baleen Gannets Pelagic Import Demersal Large Bottlenose Common NZ Aust Aust Little Terns Petrels Rays SBT Other Small Medium Arrow Small Salmons Jack Redbait Anchovy SardineInshore 21 Mesopelagics Calamary Octopus Large Small Other Blue Medium Small Benthic Detritivore Filter Primary Detritus Table Functional

42 S.D. Goldsworthy et al. / Ecological Modelling 255 (2013) 38–57 0.8000 0.2000 38

0.1000 0.4000 37

0.4000 0.5500 36

35 1.0000

0.2000 0.8000 34

0.0807 0.0050 0.0538 0.0538 0.6992 0.1076 33

0.0500 0.0600 0.0020 0.0080 0.8800 32

0.0990 0.3940 0.1120 0.1050 0.0140 0.1430 0.0270 0.0050 0.0160 0.0850 31

0.1032 0.0400 0.0016 0.0744 0.0371 0.1213 0.0075 0.0088 0.0031 0.0109 0.2202 0.0112 0.0095 0.0381 0.2626 0.0086 0.0407 0.0012 30

0.0001 0.1684 0.0024 0.6602 0.0479 0.0106 0.1104 29

0.0020 0.0600 0.0080 0.9300 28

0.0377 0.0118 0.9163 0.0342 27

0.0300 0.0427 0.1310 0.0040 0.6292 0.1574 0.0018 0.0039 26

0.0033 0.0003 0.1129 0.0347 0.1036 0.0815 0.0710 0.5926 25

0.0035 0.0150 0.0091 0.0115 0.0693 0.0056 0.0825 0.1864 0.4419 0.1752 24

0.0420 0.1920 0.0980 0.3251 0.0245 0.0442 0.2205 0.0245 23

0.8652 0.1348 22

0.0296 0.6748 0.2883 0.0049 0.0023 21

0.4938 0.5062 20

2 3 5 9 30 40 22 36 27 0.0093 24 37 16 34 2935 0.0200 Group 14 17 21 23 25 28 31 33 38 39 41 26

) piscs invert

ruffs

(infauna dolphin

sharks 12 dolphin

skates 13

and demersal demersal

lion 6 feeders production seal

grazer small

sharks 11

whales 1

squid Continued seal 4 name

tunas-kingﬁsh 15 squids 32

demersal demersal demersal zooplankton ( bentho-pelagic zooplankton feeders

penguin 7

and

fur sea mackerel

mackerel 18

fur

planktivores (megabenthos) feeders piscs invert macrobenthos) piscs (carnivores) omnivore (herbivores) Rays Large Aust Bottlenose Group Baleen Demersal Little SBT PetrelsGannets 8 Other Import Common NZ Aust TernsPelagic 10 Jack AnchovyInshore Salmons 20 Calamary Other Medium Small Mesopelagics Octopus Detritivore Primary Small Benthic Detritus Blue RedbaitSardine Medium 19 Small Arrow Large Small Filter Table

S.D. Goldsworthy et al. / Ecological Modelling 255 (2013) 38–57 43

catch and catch per unit-effort (CPUE) were estimated for 18 and

16 functional groups, respectively. A time series of annual ﬁsh-

ing mortality (F) was used for sardines instead of CPUE because

marked changes in vessel size in the ﬂeet between 1991 and 2008

confounded CPUE estimates (Supplementary Information C).

There were few data on protected species bycatch in most

ﬁsheries; however, estimates were available for common dolphin

and Australian sea lion bycatch in the sardine ﬁshery and demersal

gillnet shark ﬁshery, respectively (Goldsworthy et al., 2010; Hamer

et al., 2008). Sea lion bycatch was included as discards, as the

ﬁshery overlaps with the foraging distribution of sea lions across

the model region (bycatch scaled to 2008 estimated bycatch

relative to historic effort); estimates of dolphin bycatch in the

sardine ﬁshery were available between 2005 and 2008 (based

on bycatch rates per unit of ﬁshing effort) (Hamer et al., 2008),

and were estimated for the period between 1991 and 2004 using

ﬁshing effort. The sardine ﬁshery impacts dolphins only in part of

their range, hence bycatch was estimated as ﬁshing mortality (F)

by running the model without bycatch mortality, then estimating

F directly from the reconstructed bycatch time-series. The model

was then re-run including F. Some common dolphin bycatch is

also known to occur in the demersal gillnet shark ﬁshery, but no

quantitative data were available.

The mixed trophic impacts routine in the network analysis tools

within Ecopath was used to evaluate critical trophic interactions

between groups in the ecosystem (Supplementary Information, Fig.

S1). The routine is based on the method developed by Ulanowicz

and Puccia (1990), and allows the computation of direct and

indirect impacts which a change in biomass of a predator group

will have on other groups in the system, assuming that the diet

matrix remains unchanged, and may thus be viewed as a tool for

sensitivity analysis.

2.3. Model ﬁtting

Model ﬁtting using the ‘ﬁt to time series’ procedure was

run in Ecosim using the time-series estimates (1991–2008) of

biomass and ﬁshing mortality (F) (sardines only), catch and CPUE

for functional groups with available data. Different numbers of

predator–prey interactions within the dietary matrix were selected

(10–90) within this procedure to identify the most sensitive and

optimal number of predator–prey interactions, and their vulner-

ability values that would minimise the model sum of squares (SS)

−1

Fig. 2. Trends in the total landings (catch t y ) from eight main ﬁsheries in the and produce the best ﬁt to the time series data (a table with the esti-

EGAB ecosystem between 1991 and 2008. (A) All ﬁsheries combined (Total catch),

mated vulnerabilities is provided in Supplementary Information D).

the SASF (Sardine catch) and all ﬁsheries minus sardine catch (Other catch); (B)

Some of the default Ecosim parameters were then adjusted to

marine-scaleﬁsh line (MS-line); marine-scaleﬁsh net (MS-net); Spencer Gulf, Gulf

further decrease the model SS. This included adjusting the max-

St Vincent, West Coast prawn ﬁsheries (Prawn); demersal shark (Shark gillnet); GAB

trawl fishery (GABT); South-east Trawl fishery (SET); and Southern bluefin tuna pole imum relative feeding time of marine mammals and seabirds

and line and purse seine ﬁshery (SBT).

from 2.0 (default) to 10.0, and their feeding time adjustment

rates to 0.5 (0 for all other groups), to account for modiﬁca-

line, SA Marine Scaleﬁsh net, and three prawn ﬁsheries (Spencer tions to their search feeding times in response to changes in

Gulf; Gulf St Vincent; West Coast). Another ﬁve ﬁsheries are man- prey availability (Christensen et al., 2008). Similarly, we adjusted

aged by the Australian Government (Commonwealth): Southern density-dependent predator–prey switching power of the dolphin

Blueﬁn Tuna (SBT) purse seine, SBT pole and bait, South East trawl, and seal groups from 0 to 2.0, to account for their capacity to

Great Australian Bight (GAB) trawl, and the gillnet demersal shark opportunistically adjust their diet in response to changes in prey

ﬁshery (part of the Gillnet Hook and Trap Fishery). Fleet data availability (Piroddi et al., 2010). We also explored improvements

from the SA abalone and southern rock lobster ﬁsheries were not to model ﬁts by adjusting values of density-dependent changes in

included because the EGAB ecosystem model was primarily devel- catchability for pelagic schooling ﬁsh such as sardines and tuna

oped to be a pelagic model. (Christensen et al., 2008; Piroddi et al., 2010), but these did not

Retained and discarded catch (landings and discards, respec- produce improvements to model ﬁtting.

tively) data were typically only available for between 1 and 3 years The ﬁnal step of the model ﬁtting procedure was to link the

for each ﬁshery, and were estimated for 1991 based on their propor- best combination of vulnerability values and the time-series data

tion to landed catch (Currie et al., 2009; Fowler et al., 2009; Roberts to an estimated trend in primary productivity (PP) within the

and Steer, 2010). All landed and discarded species were assigned EGAB ecosystem. The importance of seasonal upwelling in the

their functional group, and summed (catch) at the functional group EGAB to enhancing primary, secondary and ﬁsh production has

−2

level (t km ) (Tables 2 and 3, respectively). Time series of annual been established (Ward et al., 2006). As such, time-series of mean

44 S.D. Goldsworthy et al. / Ecological Modelling 255 (2013) 38–57 3 2 4 2 2 3 7 5 3 3 6 5 5 3 8 3 2 6 7 7 − − − − − − − − − − − − − − − − − − − − 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10

× × × × × × × × × × × × × × × × × × × ×

Total 1.62 2.92 2.16 1.38 3.42 1.95 1.09 5.72 4.78 6.21 8.47 1.18 6.00 6.27 1.87 3.25 1.00 2.16 7.87 10 9 9 − − − 10 10 10

× × ×

prawn

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1.48 2.11 2.26 ﬁshery WC 7 6 6 − − − 10 10 10

prawn × × ×

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 GSV ﬁshery 1.26 1.80 1.93 4 3 3 − − − 10 10 10

× × ×

prawn

00 0 0 0 0 00 0 0 0 00 0 0 0 8.22 0 0 0 ﬁshery 1.51 2.15 2.30 SG 5 3 4 4 4 3 6 7 7 7 7 7 − − − − − − − − − − − − 10 10 10 10 10 10 10 10 10 10 10 10

× × × × × × × × × × × ×

0 0 0 0 0 0 0 0 1.54 6.28 2.42 2.51 1.00 5.00 1.83 3.30 6.00 1.00 3.00 6.98 shark 5 6 7 4 7 8 8 8 6 3 3 5 − − − − − − − − − − − − ﬁshery.

10 10 10 10 10 10 10 10 10 10 10 10

trawl Demersal × × × × × × × × × × × ×

0 0 0 0 0 0 0 2.26 2.23 1.95 3.36 1.95 6.49 1.05 1.09 3.25 3.25 1.45 1.42 sardine

5 5 3 4 6 6 5 3 − − − − − − − − 10 10 10 10 10 10 10 10

Australian × × × × × × × ×

trawl GAB

0 0 0 0 0 0 0 0 0 0 0 2.16 1.38 5.95 8.47 8.47 5.18 1.97 SE South

6 5 6 4 − − − − SASF

10 10 10 10

× × × ×

bait pole

model.

0 0 0 0 0 0 0 0 0 0 0 0 0 0 9.23 9.17 1.03 1.02 and SBT 2 2 2 − − − Ecopath

10 10 10

× × ×

purse

EGAB

0000 0 0 00 0 0 0 00 0 0 1.27 0 0 0 0 0 0 SBT 2.14 1.35 3.48 seine 3 3 4 3 3 4 2 5 balanced

− − − − − − − − 10 10 10 10 10 10 10 10

the

× × × × × × × ×

0 0 0 0 0 0 0 0 0 0 0 SAMS-net ﬁsheries 8.11 8.21 6.00 4.47 4.69 1.73 7.49 2.40 used

5 3 4 3 3 4 5 3 − − − − − − − − group

10 10 10 10 10 10 10 10

× × × × × × × ×

0 0 0 0 0 0 0 0 0 ﬁsheries 1.66 2.29 9.05 9.66 7.06 functional

5 5 ) − − 2 − 10 10

× × km

0 0 0 0 0 0 0 0 0 000 0 0 2.65 0 1.37 5.72 (catch

piscs invert landings

ruffs

ﬂeet

sharks

skates

and demersal demersal

feeders

grazer

sharks 0 9.13

squid 0 name SASF SAMS-line

tunas-kingﬁsh squids

demersal demersal bentho-pelagic

and mackerel 0

mackerel 0 0

(megabenthos) feeders piscs invert piscs Group Pelagic Demersal Rays SBTOther Large Blue Jack SardineSalmons Medium 0Small Medium Small 5.72 0 Arrow Calamary Other Octopus Benthic Sum Table Summary

S.D. Goldsworthy et al. / Ecological Modelling 255 (2013) 38–57 45 5 5 4 3 7 4 7 7 5 3 5 4 3 4 4 2 3 6 6 7 3 7 3 − − − − − − − − − − − − − − − − − − − − − − − 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10

× × × × × × × × × × × × × × × × × × × × × × ×

2.17 4.49 7.57 1.08 8.40 2.80 2.56 2.22 2.58 2.88 3.79 3.09 4.85 2.08 3.12 1.94 1.99 1.98 4.10 4.69 2.20 1.11 1.51 Total 10 10 13 13 14 10 10 10 10 10 9 10 9 13 9 9 11 − − − − − − − − − − − − − − − − − 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10

× × × × × × × × × × × × × × × × ×

prawn

0 0 0 0 0 0 ﬁshery 6.33 9.04 1.05 1.84 2.82 3.71 3.02 6.51 6.94 3.04 1.71 1.95 3.57 4.59 2.04 9.80 9.82 WC 7 − 7 7 7 10 10 10 11 7 7 7 6 8 6 7 6 7 − − − − − − − − − − − − − − − − 10

10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10

prawn × × × × × × × × × × × × × × × ×

0 0 0 0 0 0 GSV 5.40 7.72 8.96 1.57 2.41 3.17 2.58 5.56 5.93 2.60 1.461 1.66 3.05 3.92 1.74 8.37 8.39 ﬁshery 4 4 4 7 7 8 3 4 3 4 3 7 4 3 3 4 2 − − − − − − − − − − − − − − − − − 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10

× × × × × × × × × × × × × × × × ×

prawn

0 0 0 0 0 0 SG ﬁshery 6.46 9.22 1.07 1.88 2.88 3.79 3.09 6.64 7.08 3.10 1.74 1.99 3.64 4.68 2.08 1.00 1.00 5 5 6 6 5 7 7 − − − − − − − 10 10 10 10 10 10 10

× × × × × × ×

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Demersal shark 2.2 4.4 8.4 1.4 4.0 1.0 7.6 6 5 7 6 5 5 4 5 9 6 7 − − − − − − − − − − − 10 10 10 10 10 10 10 10 10 10 10

× × × × × × × × × × ×

ﬁshery.

0 0 0 0 0 0 0 0 0 0 0 0 GAB trawl 8.79 2.09 3.70 2.23 2.22 3.73 6.39 5.20 4.10 1.13 1.37 sardine

5 5 5 4 6 6 − − − − − − 10 10 10 10 10 10

× × × × × ×

Australian

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 SE trawl 1.52 1.40 7.84 5.83 6.04 1.59 South

bait pole

SASF

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 SBT and

model.

seine 5 5

− − 10 10

Ecopath

× ×

purse

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 SBT 3.00 3.00 EGAB

6 7 5 5 3 5 3 4 3 6 balanced

− − − − − − − − − − 10 10 10 10 10 10 10 10 10 10

the

× × × × × × × × × ×

0 0 0 0 0 0 0 0 0 0 0 0 0 SAMS-net ﬁsheries 4.63 2.33 5.28 4.84 1.11 1.14 1.01 1.61 1.24 2.96 used

group

5 4 3 5 3 6 4 − − − − − − − 10 10 10 10 10 10 10

× × × × × × ×

functional

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 SAMS-line ﬁsheries 5.33 1.35 1.34 8.20 2.05 1.23 1.75 by

) 2 −

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 SASF (catch

piscs invert discards

ruffs

ﬂeet

sharks

skates

and demersal demersal

lion feeders

of grazer small

sharks

squid name

tunas-kingﬁsh

demersal demersal demersal bentho-pelagic feeders

and sea mackerel

mackerel 0

omnivore planktivores (megabenthos) feeders piscs invert piscs Group Aust Pelagic Demersal Rays SBT Other Large Blue Jack AnchovySardineInshore Salmons Medium 0 Small Medium 0 Small Small Arrow Calamary Benthic Filter Sum 0 Table Summary

46 S.D. Goldsworthy et al. / Ecological Modelling 255 (2013) 38–57

monthly upwelling anomalies, calculated from the alongshore increase in catch, and conversely for increasing trophic level (Pauly

component of wind stress at South Neptune Island (Middleton and Palomares, 2005). In general, the index increases if the underly-

et al., 2007), were considered as potential PP forcing functions ing ﬁshery expands beyond its traditional ﬁshing area or ecosystem,

(FF) in the EGAB ecosystem. Wind stress values between 1991 and and decreases if the geographic area contracts, or if the underlying

2008 were scaled to positive values, and then converted to values food web is collapsing (Pauly and Palomares, 2005).

relative to that of January 1991. Using the anomaly search function

within Ecosim, we set the PP variance to 50 to enable the model to 2.5. Model scenarios

capture changes in the magnitude of ‘spikes’. The number of spline

We used the ﬁtted Ecosim EGAB model to explore the

points was set to 18, to track annual anomalies in the time series.

species/group responses (increase/decrease in biomass) to reduc-

Model-generated time series were compared to the upwelling

tions in sardine biomass (to 0.75, 0.50 and 0.25 of 2008 biomass).

index time series for agreement.

The ﬁshery effort time series was extended to year 2040, main-

taining the ﬁshing effort of all ﬂeets except sardine beyond 2008

2.4. Ecosystem indicators at 2008 levels, and increasing the sardine ﬁshery effort to drive

reductions in sardine biomass. The time series of sardine ﬁshing

After the model ﬁtting procedure in Ecosim, we examined four mortality was deselected in these procedures. In these scenarios,

ecosystem indictors that can be used to evaluate changes in the both NZ and Australian fur seal biomass was forced to increase

marine ecosystem. (1) total catch; (2) Kempton’s index of biodiver- between 2008 and 2040 (in line with observed increases between

sity (Q), which expresses biomass species diversity of functional 1991 and 2008), so that population abundances in the EGAB were

groups with a trophic level (TL) of three or higher (Ainsworth and about 1.5 and 7.0 times present levels (2008), respectively. This is

Pitcher, 2006; Kempton and Taylor, 1976); (3) the mean trophic equivalent to an increase from ∼73,000 to ∼111,000 for NZ fur seals

∼ ∼

level of the catch (mTLC) which is calculated as the weighted aver- and 2800 to 20,000 for Australian fur seals between 2008 and

age of the TL of ﬁshery targeted species (Pauly et al., 1998); and (4) 2040. In addition, simulations with and without ﬁshing effort on

the Fishing in Balance Index (FIB index), which assesses whether SBT were performed by adjusting effort in the purse seine ﬁshery

catch rates are in balance with ecosystem trophic production due beyond 2008. Scenarios where arrow squid biomass was reduced

to catch at a given TL being related to the assimilation efﬁciency by 50% and 75% were also examined. For all scenarios, we compared

of the ecosystem (Coll et al., 2009). The FIB index will remain con- the relative change in biomass between 2008 and 2040 with and

stant if a decline in mTLC is matched by an ecologically appropriate without PP forcing.

Table 4

Biological parameters by functional group of the balanced EGAB Ecopath model. Parameters in bold were estimated by the model. P/B = production/biomass;

Q/B = consumption/biomass; EE = ecotrophic efﬁciency.

−2 −1 −1

Group name Trophic level Biomass (t km ) P/B (year ) Q/B (year ) EE

1 Baleen whales 3.01 0.0389 0.020 5.097 0.000

2 Bottlenose dolphin 4.61 0.00611 0.080 16.566 0.000

3 Common dolphin 4.66 0.0039 0.090 20.511 0.000

4 NZ fur seal 4.80 0.00453 1.184 47.526 0.944

5 Aust fur seal 4.53 0.00047 1.157 28.819 0.983

6 Aust sea lion 4.91 0.00422 0.792 29.445 0.150

7 Little penguin 4.71 0.000698 1.250 85.600 0.994

8 Petrels 4.09 0.00306 1.000 147.100 0.070

9 Gannets 5.01 0.0000308 1.000 138.300 0.000

10 Terns 4.52 0.00000635 1.000 89.900 0.000

11 Pelagic sharks 4.92 0.0459 0.200 1.200 0.900

12 Demersal sharks 3.92 0.307 0.180 1.800 0.326

13 Rays and skates 3.68 0.459 0.350 2.700 0.014

14 SBT 4.52 0.145 0.200 1.600 0.900

15 Other tunas-kingﬁsh 4.50 0.0769 0.200 1.200 0.900

16 Large bentho-pelagic piscs 4.68 0.452 0.338 3.315 0.959

17 Blue mackerel 3.23 0.219 0.370 3.500 0.857

18 Jack mackerel 3.22 0.919 0.470 3.300 0.900

19 Redbait 3.38 0.561 0.740 2.800 0.900

20 Anchovy 3.63 1.272 0.700 5.040 0.555

21 Sardine 3.36 1.517 1.600 5.040 0.330

22 Inshore small planktivores 3.93 0.489 1.010 7.300 0.900

23 Salmons and ruffs 4.51 0.246 0.440 5.400 0.900

24 Medium demersal piscs 3.47 0.302 0.485 5.400 0.844

25 Small demersal piscs 2.66 1.467 0.853 5.367 0.412

26 Medium demersal invert feeders 4.00 0.0786 0.860 5.400 0.960

27 Small demersal invert feeders 3.53 0.149 1.090 5.500 0.900

28 Mesopelagics 3.07 0.106 1.005 6.673 0.900

29 Small demersal omnivore 3.77 0.170 0.840 16.000 0.957

30 Arrow squid 4.18 0.341 1.950 3.900 0.900

31 Calamary 4.50 0.0837 1.950 3.900 0.900

32 Other squids 3.14 0.111 2.500 5.850 0.900

33 Octopus 4.16 0.294 2.500 5.850 0.900

34 Large zooplankton (carnivores) 2.20 1.287 20.000 70.000 0.800

35 Small zooplankton (herbivores) 2.00 35.119 5.000 32.000 0.800

36 Benthic grazer (megabenthos) 3.24 11.013 1.600 6.000 0.800

37 Detritivore (infauna - macrobenthos) 2.52 30.983 1.600 6.000 0.800

38 Filter feeders 2.80 1.581 1.600 6.000 0.800

39 Primary production 1.00 14.900 745.000 0.000 0.108

40 Detritus 1.00 10.0 0.009

S.D. Goldsworthy et al. / Ecological Modelling 255 (2013) 38–57 47

3. Results feeders, pelagic sharks and sea lions negatively; and sea lions

affected rays and skates and little penguins negatively; NZ fur

3.1. Trophic structure and ﬂow seals affected little penguins and petrels negatively (Fig. S1). Of the

fisheries, the SA marine scalefish net fishery affected pelagic and

The balanced model parameters of the 40 functional groups demersal sharks negatively; the SBT purse seine ﬁshery affected

within the Ecopath model are presented in Table 4. The balanc- SBT, other tuna and kingﬁsh negatively; the demersal shark ﬁshery

ing procedure required adjustment to the diets of some groups affected sea lions and demersal sharks negatively, and the Spencer

where ecotrophic efﬁciencies (EE) were initially >1. EE is the pro- Gulf prawn ﬁshery affected rays and skates negatively (Fig. S1).

portion of production that is either harvested or predated upon Based on this analysis, the sardine ﬁshery has negligible impacts

by higher trophic levels and cannot exceed 1. The main dietary on other groups. However, as a steady-state analysis, all these

adjustments included reduction in the contribution of little pen- assessments do not take into account the changing abundances or

guins and petrels in the diets of NZ fur seals, and of petrels in the diets of groups. Such dynamics are explored in Ecosim scenarios

diets of Australian sea lions; reduction in the contribution of large below.

bentho-pelagic ﬁsh in the diet of arrow squid; reduction in the con- The proportional breakdown of the consumption by predators of

tribution of medium demersal invertebrate feeders in the diets of sardines and of all combined small pelagic ﬁsh groups is presented

demersal sharks and octopus; and reductions in the contribution in Fig. 4. The key predators of sardines in ranked order were large

of small demersal omnivores in the diets of salmon and ruffs and of bentho-pelagic ﬁsh, arrow squid, salmons and ruffs, SBT, other tuna

medium demersal piscivorous fish. The trophic flows between the and kingfish, common dolphins and pelagic sharks. For all small

functional groups in the EGAB ecosystem estimated by Ecopath, are pelagic ﬁsh, the key predators in ranked order were salmons and

summarised in Fig. 3. ruffs, arrow squid, SBT, calamary, other tuna and kingﬁsh, common

Results from the mixed trophic impacts routine indicate the dolphins, little penguins, NZ fur seals, petrels and pelagic sharks

positive effect of primary production on small and large zoo- (Fig. 4). The total consumption of sardines estimated by the Ecosim

−1

plankton, the positive effects of these groups on small pelagic model was 123,369 t y , representing about a third (31%) of the

−1

ﬁshes which in turn have a positive effect on dolphin, seal and total combined consumption of small pelagic ﬁsh (396,129 t y ) in

seabird groups (Supplementary Information, Fig. S1). Groups con- the EGAB ecosystem.

taining commercially targeted species inﬂuenced their respective

fishing fleets positively, and most groups affected themselves 3.2. Time-series fitting

negatively (Fig. S1). Cephalopod groups affected small demersal

invertebrate feeders and meso-pelagic fish negatively; salmons Ecosim model fits to fishery time series and model-derived

and ruffs affected medium and small demersal piscivorous ﬁsh wind-stress anomaly forcing functions (Fig. S2) are presented in

and inshore small planktivores negatively; and bentho-pelagic Fig. 5 There was a high degree of variability in the degree to which

piscivorous ﬁsh affected small pelagic ﬁsh and octopus groups Ecosim reproduced the CPUE (biomass) and yield (catch) trends

negatively (Fig. S1). SBT affected other tunas and kingﬁsh nega- of various functional groups (Fig. 5). Trends in modelled biomass

tively; demersal sharks affected medium demersal invertebrate ﬁtted observed trends reasonably well for pelagic sharks, demersal

Fig. 3. Food web diagram of the Ecopath model of the EGAB ecosystem. Functional groups are indicated by circles, with size proportional to their biomass. The trophic links

between groups are indicated by lines. Ovals (dashed) encircle major trophic groups including marine mammals, seabirds, pelagic sharks, large pelagic ﬁsh and cephalopods.

Small Pelagic ﬁsh group are encircled by a solid oval.

48 S.D. Goldsworthy et al. / Ecological Modelling 255 (2013) 38–57

Fig. 4. Estimated proportional breakdown of total annual consumption of sardines and of all small pelagic ﬁsh (sardine, anchovy, blue mackerel, jack mackerel, redbait and

inshore planktivores) by their predators based on the Ecopath model of the EGAB ecosystem. Total consumption of sardines and of all small pelagic ﬁshes is estimated to be

−1 −1

123,369 t y and 396,129 t y , respectively.

sharks, large bentho-pelagic piscivorous ﬁsh, sardine, medium functional groups composed of species targeted by ﬁsheries, such

demersal piscivorous ﬁsh, and calamary (Fig. 5). Trends in modelled as demersal sharks (gummy and school shark), SBT, large bentho-

catch fitted observed trends reasonably well for pelagic sharks, pelagic fish (snapper), sardine, medium demersal piscivorous fish

demersal sharks, rays and skates, SBT, other tuna and kingﬁsh, large (King George whiting), calamary and benthic grazers (western king

bentho-pelagic piscivorous ﬁsh, jack mackerel, sardine, medium prawn); and poorer for non-targeted (byproduct) species such as

demersal piscivorous fish, small demersal piscivorous fish, arrow blue and jack mackerel and small demersal piscivorous fish (Fig. 5).

squid and benthic grazers (Fig. 5). In many instances the ﬁt of mod- A summary of the estimated changes in the biomass of the

elled trends to observed trends was substantially better for either EGAB ecosystem between 1991 and 2008 summarised into nine

biomass or catch. For example for SBT, jack mackerel, sardine and basic groups, with and without PP forcing in the Ecosim model,

arrow squid, the ﬁt to catch was much better than the ﬁt to biomass; is presented Table 5. With no change in PP, the observed increase

whereas for pelagic sharks, medium demersal piscivorous ﬁsh and in high trophic predators (fur seals) over the period occurs to the

calamary, the fit to biomass was much better than the fit to catch detriment of large fish (SBT and other tuna and kingfish mainly

(Fig. 5). The latter instances were predominantly for functional due to over ﬁshing) and of medium and small ﬁsh. However, the

groups caught across multiple ﬁshing ﬂeets, and because Ecosim CPUE/biomass trends for many functional groups (pelagic shark,

uses only one ﬂeet’s CPUE time series to estimate biomass (but demersal shark, large bentho-pelagic ﬁsh, sardine, salmons and

uses all fleet effort data to estimate catch), such variability in fits ruffs, medium demersal piscivorous fish, arrow squid, calamary and

is not surprising. For SBT, the capacity for Ecosim to ﬁt to changes benthic grazers, Fig. 5) suggest that changes in ﬁshing effort alone

in biomass was confounded by the transition from pole and bait as are not enough to capture the observed biomass trends in these

the main ﬁshing method to purse seining, with the pole and bait groups, and that the best model ﬁts with minimum SS resulted

ﬁshery ending in 2000. CPUE from the purse seine ﬁshery was used from PP forcing, suggesting that an overall increase in PP is also

to drive biomass trends for this group. The congruence between required to support the observed biomass increases in many of the

modelled and observed trends in biomass and catch was best for groups between 1991 and 2008 (P < 0.0001, Table 5 and Fig. 5).

S.D. Goldsworthy et al. / Ecological Modelling 255 (2013) 38–57 49

Fig. 5. Time series ﬁts of the EGAB Ecosim model (thin line) to observed biomass (CPUE) and catch data (dots) for 16 functional groups between 1991 and 2008. The modelled

trend lines (dashed) are provided, together with values of the slope and coefﬁcient of variation (r ) (see overleaf for remaining plots).

3.3. Temporal changes in group biomass fur seals, Australian sea lions, and bottlenose dolphins (linear

regression, P < 0.0001) but there were no signiﬁcant changes in

The sardine ﬁshery grew signiﬁcantly between 1991 and 2008, the biomass of little penguins and petrels (Fig. 6A). Pelagic and

with the major growth period occurring since 2000 (Fig. 2). Land- demersal shark biomass increased signiﬁcantly (linear regression,

ings of SBT increased by 75% between 1991 and 2008 (linear P < 0.0001) when ﬁshing mortality was reduced as a result of reduc-

regression, P = 0.007), while landings from the marine scalefish net tions in effort in the marine scalefish net fishery and the demersal

and demersal shark ﬁsheries declined by 88% and 35%, respec- shark ﬁshery (Fig. 6B). Rays and skates also increased but pre-

tively (linear regression, P < 0.001 and P = 0.0015, respectively). dicted trends are at odds with CPUE data, especially between 2002

There has been little change in the landings from the marine and 2008 (Fig. 5). Biomass of large bentho-pelagic piscivorous

scalefish line fisheries (+7%, linear regression, P = 0.1750) and west- fish was also predicted to increase (linear regression, P < 0.0001),

ern king prawn (−1%, linear regression, P = 0.741, three regions while the biomass of SBT and other tuna and kingﬁsh groups

combined); although GAB trawl ﬁshery landings declined by 35%, declined (linear regression, P < 0.0001), principally in response to

the decrease was not significant (linear regression, P = 0.085) high fishing mortality. All the small pelagic fish groups (blue

(Fig. 2). mackerel, jack mackerel, redbait, anchovy, sardine, inshore small

The most signiﬁcant increases in population sizes of apex preda- planktivores, salmon and ruffs) and squids (arrow squid, calamary)

tors between 1991 and 2008 were for NZ fur seals, Australian were estimated to increase in biomass between 1991 and 2008

Table 5

Change of estimated relative biomass of key taxa groups based on Ecosim simulations of the EGAB ecosystem between 1991 and 2008, without and with primary production

(PP) forcing; and between 2008 and 2040 with no PP forcing, with SBT ﬁshery catch removed and with a 50% reduction in arrow squid biomass.

Summary groups Relative biomass change of groups

1991–2008 1991–2008 2008–2040 2008–2040 2008–2040

No PP forcing PP forcing No PP forcing No PP forcing No PP forcing

No SBT ﬁshery No SBT ﬁshery

<50% squid biomass

Marine mammals, birds, pelagic sharks 54% 87% 62% 85% 80%

Demersal sharks and rays 4% 35% 3% 3% 4%

Large piscivorous ﬁsh −13% 38% 2% 90% 96%

Cephalopods 4% 95% −7% −7% −23%

Medium-small ﬁsh −4% 78% 1% 1% 1%

Small and meso-pelagic ﬁsh 25% 25% −27% −27% −3%

Benthic grazers/ﬁlter feeders/detritovores 0% 30% 1% 1% 1%

Zooplankton 0% 37% 1% 1% 1%

Primary production 0% 16% 0% 0% 0%

50 S.D. Goldsworthy et al. / Ecological Modelling 255 (2013) 38–57

Fig. 6. Estimated changes in the biomass of Ecosim EGAB model groups between Fig. 7. Ecosystem indicators calculated from the Ecosim EGAB model for the period

1991 and 2008: (A) marine mammals and birds (biomass change in NZ and Aus- 1991 to 2008. (A) Kempton’s Q biomass diversity index; (B) Mean trophic level of the

tralian fur seals is forced in the model as these estimates are based on empirical catch and (C) Fishing in balance (FIB) index. Estimated trends are given by dashed

data for these species in the EGAB ecosystem); (B) sharks, rays and skates, tunas and lines (regression), with their coefﬁcient of variation (r ) and level of signiﬁcance (P).

kingﬁsh; and (C) small pelagic ﬁsh, arrow squid and calamary.

S.D. Goldsworthy et al. / Ecological Modelling 255 (2013) 38–57 51

(linear regression, P < 0.0001) (Fig. 6C). Common dolphins were 2008 (Fig. 7A), commensurate with increasing biomasses of marine

estimated to have declined between 1991 and 2004, with some mammals, sharks, and some large piscivorous ﬁsh and squid (Fig. 6).

recovery occurring since 2004 when management measures were The mTLC decreased signiﬁcantly between 1991 and 2008 (linear

introduced to mitigate bycatch in sardine ﬁshery (Hamer et al., regression, P < 0.001) (Fig. 7B), as a consequence of growth in the

2008). small pelagic ﬁshery for sardines. The ﬁshing in balance (FIB) index

between 1991 and 2008 generally increased but not signiﬁcantly

3.4. Ecosystem indicators and all values were <0.02 (Fig. 7C). There was a temporary spike in

FIB in 2005 that corresponds to the peak in sardine catch in that

The ecosystem indicators identiﬁed signiﬁcant changes in the year (40,000 t, Fig. 2A), but it then declined back to similar levels

EGAB ecosystem between 1991 and 2008 (Fig. 7A–C). Total catch to between 2002 and 2004 (Fig. 7C). An FIB index <0 occurs where

of the combined ﬁsheries showed a 4.6-fold increase, attributed ﬁshing impacts are so high that the ecosystem function is impaired,

to growth in the sardine ﬁshery (Fig. 2A). The total catch of all or where discarding occurs and it is not considered in the analysis

other ﬁsheries combined showed a slight (0.89) but non-signiﬁcant (Christensen, 2000). An FIB index = 0 indicates high production at

reduction over the same period (Fig. 2A). Kempton’s Q biodiversity lower trophic levels with ﬁshing in balance; and an FIB index >0

index usually increases with growing biomass of high trophic level indicates an expansion of ﬁshing and/or where bottom-up effects

species, and decreases with increased ﬁshing impacts. The index are occurring, resulting in more catch than expected (Coll et al.,

for the EGAB ecosystem increased signiﬁcantly between 1991 and 2009).

Fig. 8. Predicted change in the biomass of functional groups in the Ecosim EGAB model in 2040 relative to 2008 with sardine biomass reduced to 0.75, 0.50 and 0.25 of 2008

biomass. In this simulation, NZ fur seal and Australian fur seal groups were forced to increase between 2008 and 2040 (in line with observed increases between 1991 and

2008), so that population abundances in the EGAB were about 1.5 and 7.0 times present (2008) levels, respectively (with no change in sardine biomass). Note: the break in

the scale of the x-axis.

52 S.D. Goldsworthy et al. / Ecological Modelling 255 (2013) 38–57

3.5. Model scenario results whose biomass declined by 6%, 17%, 27%, respectively (Fig. 8).

Little penguin decline was less affected by sardine reductions with

Functional groups that declined below their 2008 biomass declines of 12.0%, 12.5% and 12.9% in response to 25%, 50% and 75%

as a result of reductions in sardine biomass included: common reductions in sardine biomass, respectively. Relative biomasses of

dolphins, little penguins, gannets, terns, SBT, other tunas and king- NZ fur seals (65%, 61%, and 56%) and Australian sea lions (28%, 20%

ﬁsh, small demersal invertebrate feeders, mesopelagics, and arrow and 14%), were lower, respectively in response to 25%, 50% and 75%

squid (Fig. 8). For some declining groups, their decline was lessened reductions in sardine biomass, due mainly to indirect interactions

as ﬁshing on sardines increased (e.g. petrels and jack mackerel) reducing the biomass of other key prey taxa (arrow squid and large

(Fig. 8). For some groups with increasing biomass, the increase was bentho-pelagic piscivorous ﬁsh, respectively) (Fig. 8).

lessened (e.g. NZ fur seals, Australian sea lions, pelagic sharks, and Our simulations of continuation of the current (2008) purse

salmon and ruffs), or enhanced (e.g. bottlenose dolphins, Australian seine ﬁshing effort on tuna beyond 2008 resulted in a 21% decline

fur seals, redbait, anchovy, small demersal omnivores, other squids in biomass by 2040, on top of the estimated 51% decline up to 2008.

and octopus) as sardine biomass was reduced (Fig. 8). Simulations showed SBT biomass increased when ﬁshing effort

Of the land-breeding marine predators, those most directly was reduced by 50%, 75% and 100% from 2008 levels, resulting

impacted by reductions in sardine biomass were terns, whose in increases in SBT biomass of 45%, 148% and 615%, respectively

biomass declined by 9%, 20% and 35% in response to 25%, 50% between 2008 and 2040 (Fig. 9). They also resulted in marked

and 75% reductions in sardine biomass, respectively; and gannets increases in the biomass of the other tuna and kingﬁsh group (58%,

Fig. 9. Predicted change in the biomass of functional groups in the Ecosim EGAB model in 2040 relative to 2008 with biomass increases of SBT. Biomass increases in SBT

were simulated by reducing effort in the purse seine ﬁshery by adjusting time series values between 2008 and 2040 under different scenarios of ﬁshing effort (current [2008]

levels; 50% 2008 levels; 25% 2008 levels and no ﬁshing effort). In these simulations, NZ fur seal and Australian fur seal groups were forced to increase between 2008 and

2040 (in line with observed increases between 1991 and 2008), so that populations abundances in the EGAB were about 1.5 and 7.0 times present (2008), respectively.

S.D. Goldsworthy et al. / Ecological Modelling 255 (2013) 38–57 53

199% and 1159%, respectively). Recovery of SBT was coincident with The potential role of reduced competition for small pelagic ﬁsh

increases in the biomass of pelagic sharks, but does not have major by a reduction in biomass of arrow squid was explored by gradu-

positive or negative effects on any other groups (Fig. 9). Although ally increasing ﬁshing mortality in the time series between 2008

the consequences are not examined here, the global quota of SBT and 2040, while excluding SBT ﬁshing effort and enabling fur seals

was coincidentally cut by 20 per cent for the 2010 and 2011 ﬁshing to recover as above. Results from scenarios where arrow squid

seasons since completion of this study. biomass was reduced by 50% and 75% are presented in Fig. 10, and

Simulations with and without ﬁshing effort on SBT, and with and relative changes in the biomass of the EGAB ecosystem summari-

without PP forcing indicated that the recovery of apex predators sed into nine basic groups between 2008 and 2040 are presented

(marine mammals, birds and pelagic sharks) and of large pelagic in Table 5. Results indicate that for some high trophic-level preda-

ﬁsh such as SBT is supported through consumptions of low and tor groups that increased in biomass over the 2008–2040 period

mid-tropic species, especially small pelagic ﬁsh and cephalopods and were important predators of arrow squid (NZ fur seals, pelagic

(Table 5). The main small pelagic ﬁsh group impacted is jack mack- sharks, SBT, and other tunas and kingﬁsh), rates of increase were

erel, with negligible change in other small pelagic species, while reduced commensurate with reductions in arrow squid biomass.

the most negatively impacted cephalopods include arrow squid and However, most others, including common dolphins, Australian

calamary (Fig. 10). fur seals, Australian sea lions, little penguins, petrels, gannets,

Fig. 10. Predicted change in the biomass of functional groups in the Ecosim EGAB model in 2040 relative to 2008 with different scenarios of arrow squid biomass reduction

and with no SBT ﬁshery. Biomass reduction in arrow squid were simulated by adjusting time series values between 2008 and 2040 under different scenarios of ﬁshing effort

(current [2008] levels; 50% biomass reduction of 2008 levels; 75% biomass reduction of 2008 levels). In these simulations, NZ fur seal and Australian fur seal groups were

forced to increase between 2008 and 2040 (in line with observed increases between 1991 and 2008), so that populations abundances in the EGAB were about 1.5 and 7.0

times present (2008), respectively.

54 S.D. Goldsworthy et al. / Ecological Modelling 255 (2013) 38–57

terns, and demersal sharks, responded positively to reductions in when catches were very low, and does not take into account the

arrow squid biomass (Fig. 10). Small pelagic ﬁsh species (with the substantial increases in catch and the changing abundances or

exception of inshore small planktivores), large bentho-pelagic pis- diets of groups. In contrast, dynamic assessment using Ecosim

civorous ﬁsh and salmon and ruffs also responded positively to indicated that many groups were sensitive to changes in sardine

reductions in arrow squid biomass (Fig. 10). Comparison between biomass.

the scenarios of increasing fur seal biomass with removal of SBT Of the land breeding marine predators, crested tern popula-

ﬁshing effort, and the same scenario where arrow squid biomass tions demonstrated the greatest sensitivity to reduction in sardine

was reduced by 50% (last two columns of Table 5) highlight the biomass, both in direction (negative) and magnitude, followed by

signiﬁcant predation pressure that cephalopods (especially arrow Australasian gannets. The latter species only breeds at one site off

squid) probably place on small pelagic ﬁsh, and how with reduced Cape Jaffa some distance from the centre of the sardine ﬁshery. In

arrow squid biomass, greater production of small pelagic ﬁsh can contrast, there are at least 10 breeding colonies of crested terns

be directed into higher trophic levels (in this instance, the increased situated adjacent to the sardine ﬁshery in southern Spencer Gulf

production of small pelagic ﬁsh was directed into large piscivorous and Investigator Strait (McLeay et al., 2010). Demographic stud-

ﬁsh and other apex predator species (Table 5)). ies of crested terns found that they were physically smaller and

had lower survival rates in years following the two sardine mass

mortality events, in 1995 and 1998 (McLeay et al., 2009b). Their

4. Discussion dependency on small pelagic ﬁsh, including sardines which they

take from waters near colonies during a short breeding season

This study presents the ﬁrst trophic model of the EGAB ecosys- (McLeay et al., 2009a, 2010), gives this species the greatest potential

tem. Ecopath with Ecosim was used to resolve the trophodynamics to provide ecological performance indices for the sardine ﬁshery,

of the EGAB ecosystem, to improve our understanding of the through foraging, reproductive and population response variables;

trophic interactions of the major functional groups and to assess the and further research to assess their suitability is warranted.

impacts of temporal changes in ﬁshing activity and apex predator Little penguins also demonstrated a slight reduction in biomass

biomass between 1991 and 2008. The model results suggest that in response to reduced sardine biomass, although the magnitude

most apex predator populations have increased over this period, of this response was small. In Victoria, the reproductive success of

including baleen whales, bottlenose dolphins, fur seals, pelagic little penguins decreased coincident with a reduction in the con-

sharks, large bentho-pelagic piscivorous ﬁsh, small pelagic ﬁsh tribution of sardines in their diet due to a sardine mortality event

and cephalopods. Fur seal recovery is likely to have been driven (Chiaradia et al., 2003; Dann et al., 2000). The Ecosim model identi-

by a demographic response to reduced mortality from the 1970s ﬁed that the biomass increase of New Zealand fur seals reduced in

onwards that enabled remnant populations to overcome popula- response to a reduction in sardine biomass. The Ecosim model also

tion reductions from colonial sealing that occurred 140–170 years identiﬁed common dolphins, pelagic sharks, SBT, and other tuna

earlier (Ling, 1999). In contrast, the recovery of pelagic and demer- and kingﬁsh as sensitive to biomass reductions in sardines, but as

sal sharks, large bentho-pelagic piscivorous ﬁsh and some other some are subject to their own ﬁshery related mortality, are less

(non-tuna) ﬁshes indicated by the model, appears primarily to be suitable as indicator taxa compared to the land breeding marine

driven by reductions in ﬁshing mortality. This may partially be predators.

related to reductions in domestic tuna fishing TACs since poling Ecosystem indicators identified significant changes in the EGAB

ended, and the expulsion of the Japanese/international longlining ecosystem between 1991 and 2008, the most signiﬁcant of which

tuna ﬂeets from within Australia’s EEZ including the GAB where was the 4.6-fold increase in total catch, which was entirely

they ﬁshed through the late 80s and early 90s. However, the Ecosim attributable to growth in the sardine ﬁshery within southern

models suggest that positive PP forcing over the period improves Spencer Gulf and the Investigator Strait (Figs. 2A and 7A–C). Not

model ﬁts, and therefore may have underpinned uniform increases surprisingly, this led to a signiﬁcant reduction in the mTLC between

in small pelagic ﬁsh and cephalopod biomass that have contributed 1991 and 2008. Usually such reductions demonstrate increased

to the broad scale increase in these higher trophic levels (Fig. 9). A ecosystem impact as a consequence of a reduction in high trophic

study by Brown et al. (2010) simulated positive increases in PP to level relative to lower trophic level organisms (Coll et al., 2009).

examine the ecosystem responses to climate change scenarios in a However, the signiﬁcant increase in Kempton’s Q biodiversity index

range of marine ecosystems in Australia. As with the EGAB model, over the period indicates increased growth in high trophic level

they found that such increases in PP also generally led to a posi- species, suggesting that reduction in the mTLC is attributable to

tive increase to most functional groups and to increased biomass growth in the sardine ﬁshery, and not a reduction in high trophic

of high trophic species (Brown et al., 2010). level biomass. Furthermore, FIB index values generally close to zero

In contrast, the projected decline in SBT and other tunas and suggest high production at low trophic levels with ﬁshing in bal-

kingﬁsh biomass in the EGAB ecosystem appear to be driven by ance. The increasing trend in FIB index over the study period, may

increases in fishing effort. Southern bluefin tuna are a highly migra- reflect geographic expansion of fishing effort and/or more catch

tory species and the purse seine ﬁshery in the EGAB targets juvenile than expected due to bottom-up effects such as increased primary

ﬁsh in the 3–5-year-old age classes (Wilson et al., 2009). The extent productivity (Coll et al., 2009). Values above zero indicate ﬁshing

to which modelled changes in the EGAB reﬂect changes in the in balance, whereas values below zero suggest high ﬁshing impacts

broader population, or are compounded by impacts in other juris- that are impairing ecosystem function (Christensen, 2000). The FIB

dictions and ﬁsheries (High Seas long-line ﬁsheries) is unclear, but index was developed in part to address the situation where a reduc-

should be investigated further. For example, the pelagic sharks and tion in the mTLC occurs as a consequence of deliberate targeting of

petrels cross several management jurisdictions within time-scales lower trophic level species, rather than due to ﬁshing down marine

of <1 y. food webs. Another potential impact when a low trophic level ﬁsh-

The growth of the sardine ﬁshery since its establishment in ery expands rapidly is the replacement of predation mortality with

1991 has been rapid, and its catch now exceeds that of all other ﬁshing mortality, while overall total mortality remains relative con-

ﬁsheries in the region by a factor of three. Despite this, sensitiv- stant. Ecosim results for the sardine ﬁshery suggest this has not

ity analyses based on mixed trophic impacts detected negligible occurred in the EGAB ecosystem. Instead predation mortality has

impacts of the ﬁshery on other predators. However, this steady- increased as ﬁshing mortality and total mortality has increased

state analysis was based on the establishment years of the ﬁshery (Supplementary Information, Fig. S3), with predation mortality as a

S.D. Goldsworthy et al. / Ecological Modelling 255 (2013) 38–57 55

proportion of total mortality increasing signiﬁcantly between 1991 control (Cury et al., 2000), by restricting energy ﬂow to competi-

and 2008 (linear regression, P < 0.001, r = 0.616). tors at similar or higher trophic levels, although typical wasp-waist

In combination, the above indices are useful because they inte- species are highly mobile low-trophic level species, such as small

grate many aspects of ﬁshing impacts and trophodynamic change plankton feeding pelagic ﬁsh (Bulman et al., 2010; Cury et al., 2000;

to provide measures of ecosystem health. For the EGAB ecosystem, Freon et al., 2009).

all these indices suggest that despite the large scale expansion of the There are growing concerns over the ecosystem impacts that are

sardine ﬁshery between 1991 and 2008 and reduction in the mTLC, resulting from increased human dependence on ﬁsheries targeting

most functional groups from cephalopods to small pelagic ﬁsh and low-trophic level species (Ainley and Blight, 2009; Branch et al.,

high trophic level predators have been increasing in biomass over 2010; Cury et al., 2011; Smith et al., 2011). Most research on the

this period. This suggests that the current ﬁshery management impacts of these ﬁsheries has focused on high trophic level species,

strategy is sufﬁciently conservative to ensure that the ﬁshery is which are increasingly being seen to provide robust ecological per-

being managed according to the principles of ecological sustain- formance indicators of ecosystem system health, as they are often

able development (ESD) (Fletcher et al., 2002). However, the extent sensitive to subtle changes in the abundance and distribution of

to which this positive assessment reﬂects management of the sar- the lower trophic level species on which they prey (see Boyd et al.,

dine ﬁshery is uncertain, given that much of the positive changes 2006 for review). Other studies have shown how these ﬁsheries

estimated by the model reﬂect other changes in the ecosystem, also impact on other parts of the marine ecosystem, including other

including reductions in ﬁshing effort and mortality in some ﬂeets commercially targeted species (Smith et al., 2011). The growth of

(SA marine scalefish net and Commonwealth demersal gillnet shark the sardine fishery since 1991 to become Australia’s largest fishery

ﬁshery), and a positive trend in PP over the study period. How has raised concerns over its potential ecological impacts on other

the current or alternate management strategies of the sardine ﬁsh- parts of the marine ecosystem, and the need to develop an EBFM

ery would perform under alternate oceanographic conditions (such approach. The current harvest strategy in the ﬁshery is to maintain

∼

as more variable upwelling), and/or in response to management a baseline total allowable commercial catch (TACC) of 30,000 t,

changes in other ﬁsheries in the region, may be useful to explore. while estimates of the spawning biomass fall between 150,000 and

One of the key dynamics in the EGAB ecosystem is the vari- 300,000 t, corresponding to an exploitation rate of between 20%

able trends in biomass of some of the high trophic level species. and 10%, respectively (Ward et al., 2009).

Most notable is the recovery of fur seal populations over the last A recent study examined the impacts of low trophic level

25 years to numbers not seen for more than 150 years. This recov- (forage ﬁsh) depletion on global seabird populations, and identi-

ery is continuing and it is unclear at what level populations will ﬁed a threshold prey abundance below which breeding success

stabilise. Fishing pressure on populations of SBT in the GAB and consistently declined (Cury et al., 2011). This threshold was approx-

Southern Ocean south of Australia over the last 30 years has seen imately one-third of the maximum observed prey abundance, with

these stocks reduced to a fraction of their pre-exploited levels, and the authors suggesting that a general rule of “one-third for the

they are subject to continued over ﬁshing (Wilson et al., 2009). birds” could be applied as a guiding principal to EBFM of low-

Other important pelagic predators, such as pelagic sharks have also trophic level ﬁsheries, by ensuring that exploitation rates maintain

been targeted by some ﬁsheries and are subject to bycatch, and have target species above one-third of their maximum observed long-

seen historic declines. How such depletions in populations of key term biomass (Cury et al., 2011). Similarly, Smith et al. (2011)

high-trophic level predators over the last 200 years (a ‘predator- showed that broader ecosystem impacts from ﬁshing low trophic

gap’) has affected the EGAB ecosystem is unclear, but this study level species could be substantially reduced by halving exploita-

has provided some interesting insights, in particular hypotheses tion rates from typical (∼60%) maximum sustainable yield levels to

about the dynamics between cephalopods and their predators and ∼30% exploitation rates. Based on the ﬁndings of both these stud-

competitors, and the importance of these interactions in regulating ies, the current exploitation rates in the sardine ﬁshery (10–20%

the ﬂow of small pelagic ﬁsh production to high trophic levels. of estimated spawning biomass and ∼24% of the total sardine con-

Ecosim scenarios that explored the ecosystem response to sumption biomass estimated by the EGAB ecosystem model) would

recovering fur seal and SBT populations out to 2040, indicated that appear conservative, and results from trophodynamic modelling

such recoveries were supported through reductions in the biomass would suggest they presently do not signiﬁcantly impact ecosys-

of small pelagic ﬁsh (mainly jack mackerel) and cephalopods (espe- tem function, or high trophic level species. However, it is important

cially arrow squid). Scenarios investigating the response to reduced to highlight that most of sardine ﬁshery catch comes from a rela-

arrow squid biomass as a consequence of predation and com- tively small (∼10,000 km ) area centred on southern Spencer Gulf.

petition pressure exerted by apex predators, suggest this may This area is ∼20% of the estimated spawning area of sardines in

enable greater production of small pelagic ﬁsh to be directed into the EGAB (∼54,000 km , Ward et al., 2009), which makes up about

higher trophic levels, in this case to large piscivorous ﬁsh and apex 7% of the total modelled area. The current estimated exploitation

predator species. This hypothesis suggests that ‘predator gaps’ that rates of sardines in the sardine ﬁshery assumes a high degree of

resulted from reduced biomass of long-lived predator species such connectivity between the sardine population in the main ﬁshery

as fur seal, SBT and shark, may have been quickly ﬁlled by semel- area, and other parts of the estimated spawning area within the

parous species, such as cephalopods (squids) which can build up EGAB. There currently is no data on the movements of sardines

biomass quickly in response to increased small pelagic ﬁsh avail- from the broader EGAB into the ﬁshery to substantiate this assump-

ability and reduced predation pressure. A build-up in cephalopods tion. As such, it is possible that exploitation rates are higher within

may reduce trophic ﬂows to high trophic levels, with their short the region of the ﬁshery and that localised depletion cannot be

generation times and reduced predation pressure resulting in much discounted as a meso-scale issue. The model developed and pre-

of their biomass being returned to detritus. A study of the role of sented in this study covered an extensive geographic area with

small pelagic ﬁsh in southern Australian ecosystems identiﬁed that diverse habitats and may not be appropriate to examine regional

these ecosystems were largely bottom-up forced, but that differ- impacts from ﬁsheries, such as localised depletion. This will require

ent parts of the these food webs could exert both bottom-up and the development of spatially explicit regional ecosystem models,

top-down control (Bulman et al., 2010). Furthermore, switching preferably in conjunction with appropriate ecological performance

between these states may occur in response to ﬁshing and climate indicators (reproductive and foraging success) from land-breeding

change pressures (Bulman et al., 2010). In this respect, it is possible marine predators (e.g. seabirds and seals that forage in proximity to

that cephalopods may be able to exert some degree of ‘wasp-waist’ the ﬁshery), to assess and identify issues of localised depletion, and

56 S.D. Goldsworthy et al. / Ecological Modelling 255 (2013) 38–57

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Brown, C.J., Fulton, E.A., Hobday, A.J., Matear, R.J., Possingham, H.P., Bulman, C., Chris-

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We thank the Fisheries Research and Development Corporation Christensen, V., Walters, C.J., Pauly, D., Forrest, R., 2008. Ecopath with Ecosim version

6 User Guide, November 2008. Lenfest Ocean Futures Project 2008, p. 154.

(FRDC) for support of this project (FRDC projects 2003/072, and

Coll, M., Santojanni, A., Palomera, I., Arneri, E., 2009. Food-web changes in the Adri-

2005/031), and FRDC staff for their support with project manage-

atic Sea over the last three decades. Marine Ecology Progress Series 318, 17–37.

ment, especially Crispin Ashby and Caroline Stewardson. We thank Copley, P.B., 1996. The status of seabirds in South Australia. In: Ross, G.J.B., Weaver,

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National Seabird Workshop. Biodiversity Group, Environment Australia, Can-

and Christian Pike project support. We thank Topa Petit (Univer-

berra, pp. 139–180.

sity of South Australia), Jeremy Austin, Sean Connell (Adelaide

Currie, D.R., Dixson, C.D., Roberts, S.D., Hooper, G.E., Sorokin, S.J., Ward, T.M., 2009.

University), Mike Steer (SARDI Aquatic Sciences) who provided co- Fishery-independent by-catch survey to inform risk assessment of the Spencer

Gulf Prawn Trawl Fishery. Report to PIRSA Fisheries. South Australian Research

supervisory support to students who assisted in this project. We

and Development Institute (Aquatic Sciences), Adelaide. SARDI Publication No.

thank Alex Ivey and Richard Saunders (SARDI Aquatic Sciences)

F2009/000369-1. SARDI Research Report Series No. 390, p. 121.

who provided additional project support, and Charles James and Currie, D.R., Sorokin, S.J., 2010. A preliminary evaluation of the distribution and

trophodynamics of demersal ﬁsh from Spencer Gulf. Report to the South

John Middleton (SARDI Aquatic Sciences) for providing wind stress

Australian Department for the Environment and Heritage. South Australian

data. Tom Okey provided help and direction during the conceptu-

Research and Development Institute (Aquatic Sciences), Adelaide. SARDI Publi-

alisation of the ecosystem modelling components of the project. cation No. F2010/000088-1. SARDI Research Report Series No. 424, p. 179.

Cury, P., Bakun, A., Crawford, R.J.M., Jarre, A., Quinones, R.A., Shannon, L.J., Verheye,

We thank Peter Gill and Margie Morrice (Blue Whale Study Inc.)

H.M., 2000. Small pelagics in upwelling systems: patterns of interaction and

for providing diet data for blue whales and Cath Kemper and Sue

structural changes in “wasp-waist” ecosystems. ICES Journal of Marine Science

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