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RESEARCH ARTICLE
Rapid declines across Australian fishery stocks indicate global
sustainability targets will not be achieved without an expanded
network of ‘no‐fishing’reserves
Graham J. Edgar
1
|Trevor J. Ward
2
|Rick D. Stuart‐Smith
1
1
Institute for Marine and Antarctic Studies,
University of Tasmania, Hobart, Tasmania,
Australia
2
School of Life Sciences, University of
Technology Sydney, PO Box 123, Broadway,
New South Wales 2007, Australia
Correspondence
Graham J. Edgar, Institute for Marine and
Antarctic Studies, University of Tasmania,
GPO Box 252‐49, Hobart, Tasmania, 7001
Australia.
Email: g.edgar@utas.edu.au
Funding information
Australian Research Council
Abstract
1. A continuing debate between environmental scientists and fisheries biologists
on the sustainability of fisheries management practices, and the extent of
fishing impacts on marine ecosystems, is unlikely to be resolved without fishery‐
independent data spanning large geographic and temporal scales. Here, we compare
continental‐and decadal‐scale trends in fisheries catches with underwater reef
monitoring data for 533 sites around Australia, and find matching evidence of
rapid fish‐stock declines.
2. Regardless of a high global ranking for fisheries sustainability, catches from
Australian wild fisheries decreased by 31% over the past decade. The biomass of
large fishes observed on underwater transects decreased significantly over the
same period on fished reefs (36% decline) and in marine park zones that allow
limited fishing (18% decline), but with a negligible overall change in no‐fishing
marine reserves. Populations of exploited fishes generally rose within marine
reserves and declined outside the reserves, whereas unexploited species showed
little difference in population trends within or outside reserves.
3. Although changing climate and more precautionary fisheries management contrib-
ute to declining fish catches, fisheries‐independent transect data suggest that
excessive fishing also plays a major role.
4. The large number of fishery stocks that remain unmanaged or have poor data,
coupled with continuing declines in the stock biomass of managed fish species,
indicate that Aichi Target 6 of the Convention on Biological Diversity (i.e. ‘by
2020, all fish and invertebrate stocks and aquatic plants are managed and
harvested sustainably’) will not be achieved in Australia, or elsewhere.
5. In order to maintain some naturally functioning food webs supported by large pred-
ators and associated ecosystem services in this era of changing climate, a greatly
expanded network of effective, fully protected marine protected areas is needed
that encompasses global marine biodiversity. The present globally unbalanced
situation, with >98% of seas open to some form of fishing, deserves immediate
multinational attention.
Received: 19 December 2017 Revised: 4 April 2018 Accepted: 7 April 2018
DOI: 10.1002/aqc.2934
Aquatic Conserv: Mar Freshw Ecosyst. 2018;1–14. Copyright © 2018 John Wiley & Sons, Ltd.wileyonlinelibrary.com/journal/aqc 1
KEYWORDS
Convention on Biological Diversity, fish stocks, fisheries management, jackass morwong, marine
protected area, marine reserve, overfishing, Reef Life Survey, reef monitoring, stock status
1|INTRODUCTION
Effective marine management is needed now, more critically than
ever. Coastal and offshore ecosystems are changing rapidly (McCauley
et al., 2015), at a time when the history of fisheries management
includes some successes and some highly publicized failures
(Beddington, Agnew, & Clark, 2007; Pinsky, Jensen, Ricard, & Palumbi,
2011; Worm et al., 2009). The global wild fish catch peaked in the
1990s and is now declining (Pauly & Zeller, 2016; Watson & Tidd,
2018). Addressing these issues potentially involves both improved
fisheries management and the application of ‘no‐take’marine
protected areas (MPAs), i.e. ‘marine reserves’(Costello et al., 2012;
Edgar et al., 2014; Hilborn, 2016; Pendleton et al., in press). A single
marine reserve can provide insurance against population declines for
hundreds of species and improved fisheries outcomes, as long as it is
well designed and regulated (Edgar et al., 2014; Ward, 2004). Yet
despite the public desire and expectation for a greatly expanded and
effective MPA network (Hawkins et al., 2016), marine reserves pres-
ently cover less than 2% of global marine waters (Boonzaier & Pauly,
2016).
Here, decadal time series were used to estimate the net benefit of
marine reserves in enhancing the biomass of large reef fishes, relative
to both marine parks with limited fishing permitted and to open‐
access waters where normal fisheries regulations apply. We integrate
outputs from three broad‐scale reef fish monitoring programmes
(Stuart‐Smith et al., 2017), which together span temperate and tropical
waters around Australia.
Outcomes of field monitoring are compared with trends in fishery
catches to test claims that Australian fisheries are managed sustain-
ably using ecosystem‐based approaches (Fletcher, 2006). Australia's
fisheries encompass arguably the most complex and expensive
management systems worldwide on a per unit catch‐weight basis.
Management practices ranked second for sustainability in a global
marine performance assessment of 53 countries (Alder et al., 2010),
with frequent praise from fisheries experts worldwide (e.g. Hilborn,
2016). Australia's approach to sustainability embraces the ratification
of the Convention on Biological Diversity (CBD), which includes the
obligation (Aichi Target 6) that ‘By 2020, all fish and invertebrate stocks
and aquatic plants are managed and harvested sustainably, legally and
applying ecosystem based approaches, so that overfishing is avoided,
recovery plans and measures are in place for all depleted species, fish-
eries have no significant adverse impacts on threatened species and
vulnerable ecosystems, and the impacts of fisheries on stocks, species
and ecosystems are within safe ecological limits’(https://www.cbd.
int/sp/targets/rationale/target‐6/). Given that Australia rates higher
for fisheries sustainability than nearly all other CBD parties (which
include all UN members other than the USA), a necessary condition
for the achievement of Aichi Target 6 globally is that Australia's fisher-
ies comply.
Clearly, the extent to which Aichi Target 6 is achieved will be dif-
ficult to measure, given an absence of data relating to the ‘safe ecolog-
ical limit’aspect of the sustainability for most fisheries. Furthermore,
fishery sustainability can only be recognized amongst the small frac-
tion of fisheries that are actively managed. Because of high manage-
ment costs relative to fishery value, quantitative stock assessments
involving population modelling and the collection of life‐history infor-
mation and fishing effort (including growth, size distribution, and
maturity) cover <1% of species (Costello et al., 2012), and very few
of these include annual fishery‐independent assessments of popula-
tion trends (including larval settlement and egg production proxies).
Most stock assessments rely solely on trends in catch per unit effort
(CPUE) or catch history (representing 52% of the 233 ‘key’Australian
marine stocks reported by Flood et al., 2014).
2|METHODS
2.1 |Ecological survey methods
Underwater visual surveys were conducted by divers along
5 m × 50 m transect blocks through three reef monitoring
programmes: the Australian Institute of Marine Science Long Term
Monitoring programme (Emslie, Cheal, Sweatman, & Delean, 2008;
276 sites); the Reef Life Survey (Edgar & Stuart‐Smith, 2014; 127
sites); and the Australian Temperate Reef Collaboration programme
(Edgar & Barrett, 2012; 119 sites). Data analysed are the same as
those integrated for the 2016 Australian State of the Environment
Report, and are plotted at the regional level in Figure 3 of Stuart‐Smith
et al. (2017), other than that sites surveyed on two or less occasions
were excluded. Fish length and abundance estimates were converted
to biomass using species‐specific length–weight coefficients obtained
from FishBase (www.fishbase.org), as applied in previous analyses
using Reef Life Survey (RLS) data (Duffy, Lefcheck, Stuart‐Smith,
Navarrete, & Edgar, 2016; Edgar et al., 2014; Soler et al., 2015).
2.2 |Trends in total fish community biomass
The mean total biomass of all fishes ≥20 cm in length on transects at
each site each year was standardized for temporal comparisons across
sites, by dividing by the maximum biomass recorded at each site in any
year (= 1). To remove spatial autocorrelation associated with clumped
site distribution, site means were then calculated within 1
0
×1
0
grid
cells (latitude × longitude), and continent‐wide means were calculated
from the grid‐cell means for each year. Sites were distinguished by
local fishing regulation as ‘reserve’(no fishing), ‘limited fishing’(located
within multi‐zoned marine parks, where fishing with some gear types
is allowed but where other gear types are prohibited), and ‘open
access’(outside MPAs, with general fishing regulations). Data were
2EDGAR ET AL.
available for 36 1
0
×1
0
grid cells, including 33 cells with reserve data,
24 cells with limited‐fishing data, and eight cells with open‐access
data. No open‐access sites were surveyed in tropical waters, where
long‐term tropical surveys were restricted to the large multi‐zoned
Great Barrier Reef and Ningaloo marine parks. Generalized linear
models with a quasi‐binomial distribution were fitted to time‐series
data, and 95% confidence intervals calculated.
2.3 |Trends in species'abundances
The densities of common species were standardized amongst years by
dividing by the maximum annual density of the species observed at
each site from 2005 to 2015. Common species were those recorded
in at least four years at 10 sites. A total of 190 common species were
included, of which 11 were commercially exploited (Appendix 1).
Decadal trends in mean standardized densities were calculated sepa-
rately for reserve and fished sites, using the same procedures as for
trends in fish biomass (see section 2.2 above). Fished sites were
located in both limited fishing zones and open‐access waters, given
that there were insufficient open‐access sites for this treatment to
be analysed separately. In order for reserve and non‐reserve trends
to be directly compared, proportion data in plots were standardized
to 1 for the year 2005.
2.4 |Continental analysis of fishery catches
The total Australian catches for all 213 reported fisheries for the
years 1992–2014 were calculated using catch data distributed by
the Australian Bureau of Agricultural and Resource Economics and
Sciences (available at http://www.agriculture.gov.au/abares/publica-
tions/pubs?url=http://143.188.17.20/anrdl/DAFFService/pubs.php?
searchphrase = fisheries). Catches for each fishery in each year were
divided by the catch from the year of the maximum catch (= 1), and
then the means of these annual standardized catches were calcu-
lated across all fisheries for different jurisdictions. In order for trends
to be directly compared in plots, data for jurisdictions were stan-
dardized to 1 for the year 1992.
Following Pinsky et al. (2011), the number of ‘collapsed’stocks
was also calculated using a conservative definition of ‘collapse’
(<10% of mean catches in a 2‐year period relative to the 5‐year
period with highest catches). The 90% decline threshold for collapse
exceeds the magnitude of population decline required to classify spe-
cies in unmanaged populations as ‘critically endangered’, the highest
category of threat on the International Union for Conservation of
Nature (IUCN) Red List (i.e. >80% decline over three generations;
IUCN, 2006).
A caveat associated with the analysis of collapsed stocks is that
because of the increasing span of data used for calculating the peak
catch, the number of ‘collapsed’stocks will statistically increase
through time, even when stocks show random fluctuations about a
stable mean (Branch, Jensen, Ricard, Ye, & Hilborn, 2011). Such a sta-
tistical artefact was assessed and found to be minor: e.g. in fisheries
modelled with a 30% annual mortality, recruitment as a proportion
of biomass, with a randomized annual error term added for variability
and a stable biomass when averaged through time across 5000 stocks,
only 0.5% of stocks (i.e. 1 of 213) would be incorrectly classified as
having collapsed after 20 years.
2.5 |Case study: Eastern jackass morwong
(Nemadactylus macropterus)
In order to better understand relationships between fishery model
outputs, management decision making, trends in catches, and in‐water
outcomes, stock indicators associated with the eastern jackass
morwong (Nemadactylus macropterus) fishery are considered in some
detail. Jackass morwong, along with flathead (Platycephalidae spp.),
was once the co‐dominant target species in the largest multispecies
Australian trawl fishery (Tuck, 2016). The management of this fishery
is highlighted because decisions are supported by the most transpar-
ent documentation amongst Australian fisheries. Along with the bight
redfish (Centroberyx gerrardi), the jackass morwong fishery is evaluated
through the only comprehensive quantitative (i.e. Tier 1; Australian
Fisheries Management Authority, 2009) stock assessment that we
are aware of, where the modelled virgin stock biomass (B
0
) and current
stock biomass (B) are both provided in accessible public‐domain docu-
ments for multiple recent years. Other Tier‐1 assessments typically
provide only the modelled ratio of current (B)/virgin (B
0
) biomass, pre-
cluding an understanding of whether the modelled estimates of B
0
,B,
or both are changing.
3|RESULTS
3.1 |Trends in total fish community biomass
The total biomass of large fishes ≥20 cm in total length, a key indicator
of fishing pressure (Stuart‐Smith et al., 2017), declined significantly
(P< 0.05) on transects both in limited fishing zones (with a mean
decline of 18%) and in reef sites that were open to fishing (with a
mean decline of 36%) for the period from 2005 to 2015 (Figure 1).
No significant overall trend in large fish biomass was apparent across
sites in marine reserves (mean 4% rise).
3.2 |Trends in species'abundances
In order to assess the likelihood that large fish biomass declined at the
fished sites as a result of broad‐scale environmental change rather than
fishing, population trends in the exploited and unexploited subsets of
species were compared (Appendix 1), assuming that the latter group
provided a counterfactual control unaffected by fishing. Declining fish
populations of unexploited species were approximately balanced by
the number of species showing increases. Slight, albeit non‐significant
(P> 0.05 for comparison with slope = 0), downward trends were evi-
dent across populations of unexploited species between 2005 and
2015 in reserve (16% decline) and in fished sites (11% decline;
Figure 2), with no significant difference in the rate of change between
these two groups (P= 0.58 for generalized linear model (GLM) compar-
ison). By contrast, a downward overall population trend in exploited
species at fished sites (with a mean decline of 33%) significantly differed
in slope from an upward trend in exploited species within reserves (with
a 25% increase; P= 0.037 for GLM comparison of slopes).
EDGAR ET AL.3
3.3 |Continental analysis of fishery catches
Australian wild fishery catches have fallen rapidly over the past
decade, with the total catch declining 32% from 2005 to 2014
(Figure 3a). Reported catches in different Australian management
jurisdictions for 213 species or species groups show an average
31% decline since 2005 (Figure 3a, c, d). Only 23 fisheries show
catches peaking in the most recent 6‐year period (11% of total;
Figure 3e).
Visual census data from inshore reefs (Figures 1 and 2) and
commercial fishery catches (Figure 3) are not directly comparable
because they encompass different spatial domains, with only a
small overlap (for reefs with water depths of <20 m). Nevertheless,
catch trends for the 36 commercial species that inhabit inshore
reefs (abalone, lobsters, and fishes such as coral trout and luderick;
Figure 3b) show a high degree of congruence with fishery‐indepen-
dent visual census data (r= 0.75 for years 2005–13, n=9,
0.05 > P> 0.01) and with offshore commercial catches (r=0.82
for years 1988–2013, n=26,P< 0.001). Although the underlying
cause of declining inshore biomass includes recreational as well as
commercial fishing effort (the relative contributions of these can-
not be separated), the close correspondence in these trajectories
indicates that falling catches reflect declining fish populations, at
least in part.
Despite steep continuing declines in catches, fishery stocks are
considered to be in good condition by Australian management
authorities. The proportion of Commonwealth Government‐managed
stocks reported as ‘overfished’declined from 19% in 2004 to 12% in
2015, whereas ‘not overfished’stocks increased from 27% to 74%
through the same period (Flood et al., 2016). When state‐and terri-
tory‐managed fisheries are also considered, 30 of 238 stocks (13%)
are now classed as ‘overfished’or ‘transitional–depleting’(Flood
et al., 2014).
In contrast to the declining trend in the numbers of overfished
stocks, an alternative method of classifying fisheries as ‘collapsed’indi-
cates a continuing increase since 1994, to 33 of 213 Australian stocks
in 2014 (15% of total; Figure 3e). Although the rate of collapse is
slowing (Figure 3e), the number of additional fisheries recovering from
collapse each year remains fewer than the number of newly collapsed
fisheries. A total of 48 fisheries (23% of total) were classified as col-
lapsed in at least one year, including 15 that had recovered from a col-
lapsed state by 2014.
3.4 |Case study: Eastern jackass morwong
(Nemadactylus macropterus)
Annual catches of jackass morwong declined by 95% from around
2000 tonnes through the 1960s and 1970s to 109 tonnes in 2015/16
(Figure 4a). All other stock indicators –standardized CPUE (90%
decline from 1990 to 2014; Figure 4b), fishery‐independent survey
results (71–82% decline from 2008 to 2014; Figure 4c), and modelled
stock biomass (87% decline from 1965 to 2015; Figure 4d) –have also
FIGURE 1 Trends in the total biomass of large fishes (≥20 cm in length) observed during underwater transects around Australia. The inset map
shows the distribution of 36 1
0
×1
0
grid cells with survey data, as integrated from three monitoring programmes for the 2016 Australian State of
the Environment Report (Stuart‐Smith et al., 2017). Data for each of 533 sites were standardized relative to the year of maximum biomass (= 1),
and then the means were calculated for each 1
0
×1
0
grid cell, before the calculation of the grand means for each year. Generalized linear models
with a quasi‐binomial distribution were fitted to these proportion data; 95% confidence intervals are shown by shading
FIGURE 2 Trends in the abundance of
unexploited and exploited species at sites
inside and outside no‐fishing reserves. The
mean decadal trend data for 179 unexploited
and 11 exploited species are shown for the
period 2005–15. Generalized linear models
with a quasi‐binomial distribution were fitted;
95% confidence intervals are displayed by
shading; the overall decadal changes are
shown in parentheses
4EDGAR ET AL.
fallen continuously over recent decades. Modelling undertaken in the
years 2007, 2010, and 2016 all identify rising stocks in the year of
assessment, with fish biomass apparently recovering from lows
3–5 years earlier; however, with hindsight, subsequent stock assess-
ments indicate that the turning points of 2007 and 2010 were illusory.
Seven explicit assumptions were recognized during the modelling
process (Tuck, 2016), including natural mortality M= 0.15. The model
output was found to be highly sensitive to this assumption, with B/B
0
decreasing from 36% with M= 0.15 to 21% with M= 0.10 in the 2015
model (Tuck, 2016).
With respect to management decisions (Figure 4e), no change
to the total allowable catch (TAC) was recommended by the rele-
vant Southern and Eastern Scalefish and Shark Fishery Shelf
Resource Assessment Group (ShelfRAG) when modelled B/B
0
FIGURE 4 Trends in stock indicators for the eastern jackass morwong (Nemadactylus macropterus) fishery. (a) Trends in total catch and total
allowable catch (TAC) (Tuck, 2016). (b) Trends in standardized catch per unit effort (CPUE) (Tuck, 2016). (c) Biomass trends obtained from
standardized experimental trawl surveys undertaken in three regions (Commonwealth grounds off New South Wales, south‐eastern Tasmania, and
the Great Australian Bight (GAB)) (Tuck, 2016; Wayte, 2013a). Biomass data are calibrated to 1 for the 2008 survey year. (d) Hindcast (blue, green,
black) and forecast (red) trends in the modelled female spawning biomass for stock assessments reported in 2007 (Ricard et al., 2012), 2010
(Wayte, 2010) and 2016 (Tuck, 2016). (e) Recommended biological catch (RBC), TAC, and total catch for 2007–15, as agreed by the relevant
Southern and Eastern Scalefish and Shark Fishery Shelf Resource Assessment Group (ShelfRAG) in 2013 and 2015 (Australian Fisheries
Management Authority, 2015)
FIGURE 3 Trends in Australian fishery catches. (a) Total Australian catch across all reported fisheries relative to 1992, mean catch across
fisheries relative to 1992 after standardization of each fishery to year of maximum catch (= 1), and modelled stock biomass of 22 Australian
fisheries assessed in the RAM Legacy Stock Assessment Data Base relative to stock size that maximizes sustainable yield (B/B
target
). (b) Mean catch
for inshore and offshore fisheries relative to 1992 after standardization of each fishery to the year of the maximum catch. (c, d) Mean catch across
fisheries in different jurisdictions relative to 1992 after the standardization of each fishery to the year of the maximum catch. (e) Total number of
213 reported Australian fisheries that peaked each year since 1988, and also those regarded as having collapsed according to the criteria described
by Pinsky et al. (2011) (mean catches over a 2‐year period are <10% of the mean catch over the 5‐year period with the highest mean catch)
EDGAR ET AL.5
declined below the limit reference point of 0.2 in 2007, 2008, and
2009. This should have automatically triggered a recommended
biological catch (RBC) of 0 tonnes (Wayte, 2013a); however, con-
trary to the downward catch and recruitment trends that lacked
inflection, and to a precautionary approach, ShelfRAG agreed in
2011 that a ‘climate‐induced recruitment shift’(Wayte, 2013b)
had occurred in 1988. The RBCs for 2008 and 2009 were retro-
spectively changed from 0 tonnes in the 2013 report (Wayte,
2013a) to 410 and 370 tonnes in the 2015 report (Australian Fish-
eries Management Authority, 2015). Only 17% of the jackass
morwong TAC was caught in 2015.
4|DISCUSSION
4.1 |Linkages between fish population declines and
overfishing
Most fish populations, both exploited and unexploited, declined
around Australia through the period 2005–15, probably largely as
a negative consequence of recent warming and heatwaves experi-
enced in south‐eastern and south‐western Australia (Day, Stuart‐
Smith, Edgar, & Bates, 2018; Last et al., 2011; Wernberg et al.,
2013). Fishing apparently exacerbated the declines in population
numbers amongst the exploited species, with a mean overall down-
ward trend of 33%, compared with 16% and 11% for unexploited spe-
cies outside and inside marine reserves, respectively. Marine reserves
generally offset the continental‐scale declines, with the population
numbers of commercially exploited species increasing by an average
of 25% in no‐fishing zones. Thus, although regional change other than
fishing was partly responsible for declining fish populations, fishing
added to the declines for commercial fishes, thereby increasing the
risk of recruitment failure in the absence of reserves to safeguard
spawning stock.
Regardless of its reputation for sustainable fishery management,
overfishing has apparently contributed to the field observations of
the declining biomass of large fishes on Australian reefs. The overall
declines in catches began 7 years later for offshore stocks compared
with inshore stocks (in 2003 rather than 1996; Figure 3b), presumably
because of the expansion of fisheries into progressively deeper off-
shore fishing grounds through the 1990s that counterbalanced the
catch declines in the mature inshore fisheries. The issue of catch
hyperstability, where total catch and CPUE are maintained at constant
levels through improved technical efficiency and progressive expan-
sion into more distant fishing grounds, appears to characterize
Australian fisheries. Underlying stocks of the 24 mature Australian
fisheries assessed in the RAM Legacy Stock Assessment Data Base
(http://www.ramlegacy.org) –the largest synthesis of data for global
fisheries –declined precipitously through the 1990s, during a period
of stable total Australian catches (Figure 3a). These data affirm that
continuing declines in Australian fish catches are linked to declining
fish stocks rather than increasing regulatory precautions that leaves
more fish biomass in the sea. Ironically, the recently announced global
projections predict a 0–20% decline in the total catch for the
Australian region for the period 2000–2050 (Golden et al., 2016), a
level well exceeded already, given the average 31% decline for fish
catches from 2005 to 2015.
Annual catches also systematically fail to achieve the total allow-
able catch (TAC) when applied in most Australian fisheries. For exam-
ple, of the nine species with readily accessible decadal data on TAC
and actual catch in Australia's largest fishery (the Southern and
Eastern Scalefish and Shark Fishery), only two species –the tiger flat-
head (Platycephalus richardsoni) and the pink ling (Genypterus blacodes)
–achieved 50–100% of the allocated TAC in 2015, regardless of the
fact that the TACs are based on stock models, and are regularly
adjusted following analysis of the catch in the previous year (underly-
ing data available at http://www.afma.gov.au/fisheries‐services/
catchwatch‐reports). Catches of eastern school whiting (Sillago
flindersi) were well over the TAC (166%), whereas catches of the other
six species –blue grenadier (Macruronus novaezelandiae), deepwater
flathead (Neoplatycephalus conatus), gemfish (Gempylidae spp.), jackass
morwong, bight redfish, silver warehou (Seriolella punctata)–averaged
24% of the TACs. In most cases the TAC therefore appears irrelevant,
declining through time and consistently annually overestimating the
fish biomass available for catch, as in the case of jackass morwong
(Figure 4).
4.2 |Decline of the eastern jackass morwong fishery
Trends in indicators for the Australian fishery with best publicly avail-
able documentation –the Commonwealth eastern jackass morwong
trawl fishery (Figure 4) –illustrate the issues arising from inaccurate
stock assessments and poor associated decision making. Modelling
issues include a large number of statistical assumptions (seven explic-
itly recognized), the high sensitivity of model output to particular
assumptions, and an apparent lack of consideration in models of the
effect of technological improvements (other than changes in fleet
type), the spatial expansion of the fishery footprint through time, or
interactions with other species. All stock indicators have fallen contin-
uously to low levels over recent decades; however, the fishery remains
classed as sustainable.
Perversely, when stock numbers declined below a benchmark,
triggering zero RBC and thus zero TAC, an increase inTAC was agreed
on the grounds of an ‘environmental regime shift’(Figure 4; Wayte,
2013b). The use of 1988 as the year of regime shift, rather than
1915, as the baseline year for assessing B/B
0
reference points (i.e.
B
0
= 4080 tonnes rather than 14 402 tonnes (Tuck, 2016),
representing a 72% reduction) allowed the TAC to be raised from
484 tonnes in 2011 to 601 tonnes in 2012. Thus, although originally
proposed as a precautionary mechanism to address poor recruit-
ment, the climate‐induced recruitment shift theory was used to jus-
tify a management decision to increase the TAC. ShelfRAG minutes
indicate that no member raised the possibility that overfishing could
have contributed to the catastrophic declines in all stock indicators
(minutes for 2009–16 available at http://www.afma.gov.au/),
whereas anecdotal observations related to stock numbers were
reported and presumably contributed to the decision making (e.g.
‘as seen in on‐water observations by industry members’; http://
www.afma.gov.au/wp‐content/uploads/2010/06/Minutes‐ShelfRAG‐
9‐10‐November‐2009.pdf). In the most recent 2015–16 assessment
6EDGAR ET AL.
(Patterson et al., 2016), the eastern jackass morwong fishery was
officially classed as ‘not overfished’because only 17% of the 624‐
tonne TAC was captured, with the inference that the harvest was
therefore well below sustainable rates, regardless of continuing
declines in CPUE and all other indicators.
An alternative explanation, which we consider more parsimonious,
is that the population has declined by >90% and should be categorized
as ‘critically endangered’on the IUCN Red List of Threatened Species
(IUCN, 2006). Such a rating would not be appropriate if the threat was
transitory; however, no amelioration of the threat posed by fishing to
this species is foreseeable given the realpolitik associated with exten-
sive fisheries closures, as would be needed to protect a wide‐ranging
species reduced from dominant to minor by‐catch status within a large
multi‐species trawl fishery.
4.3 |Factors potentially contributing to catch
declines
Considerable debate surrounds the use of catch history, as applied
here, to identify collapsed stocks (Hilborn & Branch, 2013; Pauly,
Hilborn, & Branch, 2013). Many biologists argue that overfishing is
appropriately identified only through modelled stock assessments,
with explicit consideration of confounding factors that influence the
total catch, but are unrelated to stock size, such as changed regula-
tions and fleet dynamics (Branch et al., 2011; Hilborn & Branch,
2013); however, modelled stock assessments depend on numerous
assumptions that compound within the model, are rarely publicly doc-
umented, and are subjective, including the idiosyncratic adjusting of
parameters. Such parameter ‘tweaking’is, characteristically, explicitly
described in only the best stock assessments, such as that of Leigh,
O'Neill, and Stewart (2017) for the Australian east coast tailor
(Pomatomus saltatrix) fishery. They note: ‘a lower bound of (M) was
applied to prevent the population going unrealistically low’,‘we had
to fix rto values that produced sensible results’, and ‘the parameters
μand λalso tended to go very low and we fixed them to the minimum
values that we considered sensible’.
Moreover, the number of published stock assessments in Austra-
lia is so low that an overarching assessment of fisheries management
outcomes is precluded. This was only possible here using catch data.
Annual stock assessments are available for <10% of Australian fishery
species with published catch statistics, relating to <1% of the fished
populations in Australia. We also note that, regardless of the different
perspectives on the use of modelled versus catch data, the estimated
stock biomass provided through the RAM Legacy Stock Assessment
Data Base showed similar or greater declines than the trends observed
in catches (Figure 3a).
Fisheries managers generally offer three explanations for declin-
ing catches: (i) stock biomass is declining as a deliberate policy to
remove large individuals and increase the average growth rates and
productivity of the fishery; (ii) stock numbers are not declining but
management is now more precautionary, undergoing recent structural
reforms that include effort reduction and the declaration of MPAs that
reduce catch; or (iii) populations are declining as a consequence of
changing environmental conditions outside the influence of the
fisheries intervention. These arguments have merit, but raise addi-
tional questions.
The deliberate fishing down of stocks only applies to newly
developing fisheries, so has little relevance to mature fisheries, such
as the inshore fisheries with declining trends depicted in Figure 3b.
Moreover, the removal of large slow‐growing fishes from ecosys-
tems, although potentially useful in terms of maximizing fish produc-
tion, is antithetical to ecosystem‐based management, which requires
the persistence of the full range of ecosystem functions, including
those provided by larger predators and grazers in naturally struc-
tured populations.
Fisheries management in Australia is becoming more precaution-
ary, including the introduction of harvest strategies that set the tar-
get biomass at 40% rather than 20% of the virgin biomass, and, in a
few cases, by considering the maximum economic yield in addition
to the maximum sustainable yield (Gardner, Hartmann, Punt, &
Jennings, 2015). Nevertheless, implicit in the second precautionary
argument is that mistakes were made in the past, with higher fishing
levels than are now considered prudent, but that fisheries are at last
sustainable following the lessons learned. This same argument has
been made throughout history, however, often repeated annually,
raising doubt as to whether this year is the turning point from which
stocks will recover.
Structural reforms to the fishing industry also show little congru-
ence with spatial or temporal trends in Australian catches. Amongst
the states, Queensland fishers lost the most access to resources when
an additional 28% of the Great Barrier Reef Marine Park was
reassigned to no‐fishing zones in 2004 (representing ~14% of the
Queensland sea area; Grech, Edgar, Fairweather, Pressey, & Ward,
2014) and a $A214 million structural adjustment package was imple-
mented (Gunn, Fraser, & Kimball, 2010). Despite this re‐zoning,
Queensland catches have decreased less than catches in other
Australian states during the past decade (Figure 3c, d), with the large
no‐take areas possibly buffering fisheries from decline.
By contrast, catches declined most in Tasmania, despite no addi-
tional marine reserves since 2004 nor any buyout of fishing effort
(Figure 3c), although in one fishery the TAC was lowered because of
a policy change from maximum sustainable to maximum economic
yield (Gardner et al., 2015). As marine reserves comprise only a trivial
proportion (~1%) of Tasmanian coastal waters (Grech et al., 2014), and
are generally located in unproductive areas with few commercial
resources (Devillers et al., 2015), the displacement of fisheries effort
from marine reserves could not have contributed to the 65% decline
in catch across all fisheries from 1994 to 2014.
Changing environmental conditions have undoubtedly promoted
the decline in many fisheries, as is evident in Figure 2, where an over-
arching decline was noted outside reserves, including for species not
targeted by fishers. Declining catches in Tasmania probably also partly
result from a loss of oceanic productivity, as this state is a global
hotspot for warming (Popova et al., 2016).
Regardless, few fisheries models consider changing environmental
conditions, species interactions, or assign adequate leeway for error,
despite the environmental domains of many fisheries now falling out-
side known bounds. Trends in sea temperature, and the increasing
number and resolution of warming projections, should be considered
EDGAR ET AL.7
in modelling and precautionary regulations (Brown, Fulton,
Possingham, & Richardson, 2012; Melnychuk, Banobi, & Hilborn,
2014), rather than temperature anomalies used as post hoc justifica-
tion for overstated catch projections and continuing declines.
For most assessments, a stable CPUE is regarded as indicative of
stable population numbers and sustainable catch rates (Flood et al.,
2014), even though fisheries biologists have long recognized that
serial depletion (i.e. fishers maintaining stable catches by moving fur-
ther afield as stocks close to home decline) and improvements in cap-
ture efficiency can obscure declining stocks. In particular, increased
capture efficiency through improving technology (including GPS,
acoustic sensors, weather forecasting, and boat and trawl design)
and fisher knowledge can conservatively be estimated at 3% annually
(Marriott, Wise, & St John, 2010; Tarbath & Mundy, 2015).
Compounded, this equates to a 34% increase in real effort, and a
26% decline in stock, with stable CPUE in each decade.
4.4 |Towards improved sustainability
With some notable exceptions (Hobday et al., 2011), most recent
attempts at moving fisheries management towards modern precepts
of sustainability continue to face a steadfast focus on biomass produc-
tion. This perspective is evident in the definition of ‘overfished’used
by Australian management authorities, which only covers recruitment
overfishing of a stock (i.e. the reduction in biomass of spawning stock
beyond the point where recruitment is inadequate to prevent stocks
declining further; Flood et al., 2016). Knowing that fisheries are ‘not
overfished’provides little insight into ecological sustainability, includ-
ing ecosystem impacts associated with trawl damage or changes to
trophic structure. Consequently, even the best science underpinning
gold‐standard stock assessments does little to address the cumulative
interactions and impacts of fisheries on biodiversity, including the
many inter‐dependent ecological relationships and consequent com-
plexities that contribute to the structure and function of ecosystems
(Rosenberg et al., 2014), and hence the true sustainability problem.
Once tipping points are passed, hysteresis can make a return
to formerly sustainable levels extremely difficult (Neubauer, Jensen,
Hutchings, & Baum, 2013).
The lack of independent scrutiny in co‐managed fisheries, including
issues associated with industry capture of regulators, and researchers
with grants dependent on fishers' support (Barkin & DeSombre,
2013), may also contribute to the setting of TACs that exceed sustain-
able and catchable limits. Although fisheries are a public resource, fish-
eries management committees in Australia are dominated by members
aligned to, and typically funded by, the fishing industry. As in the case of
the jackass morwong fishery described above, and the orange roughy
(Hoplostethus atlanticus) fishery described by Bax et al. (2005), decisions
on catch quotas consequently include only modest precautionary ele-
ments related to ecological and ecosystem issues, with stakeholders
keen to push quotas as close as possible to the modelled maximum‐sus-
tainable or economic yield. When the knowledge base is limited or dis-
puted, uncertainty is ‘characterized almost uniformly by overly
optimistic interpretations of the present and future states of the fish-
ery’(Bax et al., 2005). Moreover, the underlying metrics for reporting
the status of fish stocks change regularly, precluding accurate time‐
series comparisons amongst stocks that would better inform the esti-
mates of actual trends in fish abundance.
Although focused on Australia, the outcomes reported here are rel-
evant elsewhere, given the country's global leadershiprole in marine con-
servation (particularly MPA management), and the prevalence of
declining and declined stocks worldwide. Fisheries statistics compiled
within the RAM Legacy Stock Assessment Data Base (http://ramlegacy.
org/) indicate two broad regional groupings in stock trends: Australian
fisheries group with a set of regions that also include New Zealand, the
Pacific, the Atlantic, and the US West Coast, exhibiting rapid declines in
stocks from levels well above the maximum sustainable yield (MSY); a
second large set of regions, including the US East Coast, the US
Southeas t, and non‐EU Europe, have passed this phase through historical
overfishing and are near or below the MSY when averagedacross stocks,
albeit with recent signs of improvement in some cases. Alaskan and
South African fisheries are uniquely characterized by rising stocks that
are well above the MSY on average.
Australian fisheries may differ from European, North American,
and Asian fisheries in their comparative recent history and greater
management focus on development (Worm et al., 2009). Compared
with mature Northern Hemisphere fisheries, Australian fisheries lack
an extended time series of data to calibrate models, and possess a rel-
atively low total catch volume that translates to little research funding,
public interest, or scrutiny. Regardless, most of the problems affecting
the management of Australian fisheries (Box 1) probably also apply
elsewhere.
Box 1. Issues affecting fishery management
practices in Australia and elsewhere
Data availability
Problems
•Little or no catch or discard data are available for most
species affected by fishing, including species caught as
by‐catch or that are difficult to identify to species level
and are grouped in logbooks, for analysis or reporting
•Little or no fishery‐independent data are available on
population trends
•Comparable no‐take scientific reference areas are rarely
available for analytical partitioning of the contribution of
fishing to declining stocks relative to impacts of climate
change or other broad‐scale pressures
Potential solutions
•Capitalize on the cost‐effective collection of
fishery‐independent data over large scales through
new technology (e.g. eDNA) and volunteer‐based
programmes, including the integration of existing
citizen‐science data streams into fishery management
processes and the development of new citizen‐science
initiatives
•Establish benchmarks and fishery‐independent trends
in stocks through the investigation of effective marine
protected areas (MPAs). This may require the
establishment of new marine reserves or the better
8EDGAR ET AL.
Just as for Australia, the global community remains as far as ever from
achieving Aichi Target 6 related to fisheries sustainability. Given the
large number of fisheries with declining stocks and the predominance
of fisheries that lack any accounting, an overall global improvement in
fisheries sustainability over the past decade remains debatable,
let alone the hope that fisheries are approaching the 2020 target that
‘all fish and invertebrate stocks and aquatic plants are managed and
harvested sustainably’. This has become an aspirational rather than a
practical target.
An improved understanding of factors affecting fisheries sustain-
ability, particularly biases associated with stock assessment, could be
achieved by retrospective analysis of the best‐practice stock assess-
ments on the RAM Legacy Stock Assessment Data Base for 331
fisheries stocks worldwide (Ricard, Minto, Jensen, & Baum, 2012).
The difference between the estimated stock size in the last year of
RAM assessment and the stock size re‐assessed for that year using
more recently updated models provides an index of accuracy.
Individual stock errors can thus be aggregated to identify any
consistent regional and global assessment biases. Although such a
enforcement of existing MPAs to provide effective
fishery exclusion controls on a region‐by‐region basis
Stock assessments
Problems
•Detailed stock assessments are too expensive for
widespread application, so are generally applied only in
a few high‐value fisheries
•Assessments are generally conducted with weak
documentation and with assumptions that preclude
replication and independent scrutiny
•Models generally ignore interspecific interactions,
regardless that fisheries are increasingly framed within
ecosystem‐based management systems
•Models and quota‐setting processes are rarely subjected
to independent audit or scrutiny, and details are often
withheld from the public domain
•With changing climate and habitat, models extrapolate
outside the known environmental bounds
•Technological improvements that incrementally alter
fishery characteristics and increase capture efficiency,
biasing the catch‐per‐unit‐effort (CPUE) calculations,
are often ignored in models
•Fishery metrics used for reporting frequently change
through time, complicating longitudinal comparisons
Potential solutions
•Establish transparent and publically accessible stock
reporting tools that use consistent metrics and detailed
documentation of methodology
•Allocate adequate resourcing to ecologists at research
institutions mandated with fisheries science to
contribute to stock assessments and decision‐making
support systems, including in the public domain
•Allocate adequate resourcing for the development of
ecologically sensitive stock assessment systems able
to be applied for all fished species, irrespective of
catch value
•Develop empirical indices of stock status for all fished
species that reflect direct and indirect ecological
interactions, and are applied with high levels of
precaution to reflect ecological and environment
domain uncertainties
Decision making
Problems
•Decisions prioritise short‐term catch maximization over
precaution
•Modellers and managers both tend towards optimism
when dealing with uncertainty
•Decisions in co‐managed fisheries are generally made by
committees dominated by industry‐aligned members
•Scientists with ecological expertise contribute little to
committees and decisions
•Benchmarks (e.g. total allowable catch) are often set at
irrelevant levels
•Lessons learned from poor decision making can be
obscured by revisionary history
•Large‐bodied individuals of target species are
deliberately fished down as a specific management
goal, contrary to ecological sustainability goals
•Wider effects of fishing on ecosystems are overlooked
Potential solutions
•Mandate decision making that is explicitly
precautionary, recognizing the ecological uncertainties,
and provide for public domain contestability
•Formalise a ‘red team’approach to data analysis,
through the consideration of pessimistic as well as
optimistic scenarios
•Increase the input from independent voices on
management fora. Consistent under‐catches of total
allowable catches should trigger a detailed
investigation of stock trends by an independent and
public‐domain audit process
•Expand targeted food‐web modelling and ecological
studies to investigate the system‐specific ecological
importance of targeted species and large individuals
•Develop management models and decision support
based on age/size cohort objectives to facilitate
the ecosystem‐based management of target species
that explicitly reflects the population‐level ecological
structure and function of target species
•Integrate fishery and biodiversity conservation
management processes, including the expanded
application of no‐fishing reserves
EDGAR ET AL.9
retrospective audit is beyond our resources, we note that stock
biomass in 2007 in the two Australian fisheries with sufficient pub-
licly accessible data to allow such a test was overestimated by 93%
(jackass morwong) and 63% (bight redfish), according to 2015 stock
assessments (Tuck, 2016).
The implementation of a relatively small number of solutions
could make substantial progress towards addressing issues with
current fisheries management practices (Box 1). The key issue of
the availability of independent data can be partially covered for
inshore systems through the expansion of citizen‐science monitoring
programmes, as has been achieved in Australia through the Reef Life
Survey (RLS) (Edgar & Stuart‐Smith, 2014; Stuart‐Smith et al., 2017).
Diver‐and recreational fisher‐based citizen science provides a direct
cost‐effective strategy for assessing key aspects of the sustainability
of shallow‐water stocks. Following appropriate selection and training,
volunteer divers can generate data of scientific research quality (Edgar
& Stuart‐Smith, 2009) across geographic and temporal scales that are
orders of magnitude larger than scientific teams can cover (Edgar,
Stuart‐Smith, Cooper, Jacques, & Valentine, 2017).
4.5 |Need for an expanded marine reserve network
Despite myriad complexities in the socio‐ecological system that con-
trols the human use of marine habitats (Fulton, Smith, Smith, & van
Putten, 2011), improvement in both fisheries and conservation out-
comes is possible (Ward, 2004; Ward, Heinemann, & Evans, 2001).
Developing an adequate safety net of effective marine reserves,
increasing the input from independent voices on management fora,
considering pessimistic scenarios using a ‘red team’approach (Burkus,
2017), and applying a more ecologically sensitive precautionary
approach when regulating fishing effort all offer the prospect of
achieving a win–win outcome for both fishers and the oceans. If man-
aged more conservatively, fish stocks could expand in the future to
help meet human food needs (Costello et al., 2012). Unfortunately,
substantial change towards ecological sustainability within fisheries
policy is unlikely to happen rapidly, other than through an expanded
network of no‐fishing marine reserves, which is a management tool
with widespread public interest and support (Hawkins et al., 2016).
Notwithstanding the limited current extent of marine reserves,
additional spatial restrictions on fishing for conservation purposes
are opposed by many fisheries practitioners on the grounds that the
removal of fish within well‐managed fisheries has little impact on bio-
diversity (Kearney, Buxton, & Farebrother, 2012; Pendleton et al., in
press). This contention profoundly affects government policies on
marine conservation in Australia, a nation that has pioneered the
development of multi‐use MPAs (Day & Dobbs, 2013), and with a
widely acknowledged global leadership role in this field. The current
national roll‐out of Australian Marine Parks, the largest national MPA
network globally, is specifically designed to avoid fisheries operations
(Buxton & Cochrane, 2015; Devillers et al., 2015; Edgar, 2017). Conse-
quently, no‐fishing zones are almost completely lacking in the
proposed network in water depths of <500 m, where threats are
concentrated. As one example, the eastern region, which extends
1600 km from Victoria to southern Queensland, includes only two
small pre‐existing marine reserves (of 1 and 2 km in diameter) on the
continental shelf (Devillers et al., 2015). Our study refutes the central
assumption underlying this zoning strategy: that MPA zones with
selective fishing allowed provide adequate biodiversity safeguards,
including for fish stocks (Figure 1). Issues similar to those identified
here (Box 1) affect other nations and their fisheries to various extents.
Marine reserves should be viewed as a core management tool, even
in locations with intensely managed fisheries. Due to much greater con-
servation effectiveness, ‘no‐fishing’marine reserves should also be con-
sidered separately from marine parks that allow limited fishing when
accounting towards national and multinational MPA area targets (e.g.
Aichi Target 11 of the CBD; https://www.cbd.int/sp/targets/). Unfor-
tunately, because of idiosyncratic reporting by governments, the cur-
rent global extent of marine reserves is unknown. The primary global
MPA resource, the World Database on Protected Areas (https://
www.protectedplanet.net/marine), currently (19 December 2017) lists
2.3% of the marine domain as ‘no‐take’; however, this total includes
many large areas with fishing allowed or with management plans not
yet enacted. We conclude that further declines in stocks and catches
across the oceans are inevitable unless a greatly expanded global safety
net of representative marine reserves is developed.
ACKNOWLEDGEMENTS
Bob Pressey provided us with the opportunity to consider and concep-
tualize this analysis. Vital support for field surveys and analyses was pro-
vided by the Australian Research Council, the Australian Institute of
Marine Science, the Institute for Marine and Antarctic Studies, The Ian
Potter Foundation, and the Marine Biodiversity Hub, a collaborative
partnership supported through the Australian Government's National
Environmental Science Programme. We thank the many colleagues
and Reef Life Survey (RLS) divers who participated in data collection,
the leadership of Hugh Sweatman and Neville Barrett in the Australian
Institute of Marine Science and University of Tasmania field monitoring
programmes, Russell Thomson and German Soler for statistical support,
and Nic Bax, Sue Baker, Caleb Gardner, and anonymous reviewers for
comments that greatly improved the article. The authors declare no
potential conflicts of interest.
ORCID
Graham J. Edgar http://orcid.org/0000-0003-0833-9001
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SUPPORTING INFORMATION
Additional supporting information may be found online in the
Supporting Information section at the end of the article.
Source data on fisheries catches are available through the Australian
Bureau of Agricultural and Resource Economics (ABARES) at
their website http://www.agriculture.gov.au/abares/publications/
pubs?url=http://143.188.17.20/anrdl/DAFFService/pubs.php?search
phrase=fisheries, and for Reef Life Survey ecological monitoring data
at https://reeflifesurvey.com/reef‐life‐survey/survey‐data/
How to cite this article: Edgar GJ, Ward TJ, Stuart‐Smith RD.
Rapid declines across Australian fishery stocks indicate global
sustainability targets will not be achieved without an expanded
network of ‘no‐fishing’reserves. Aquatic Conserv: Mar Freshw
Ecosyst. 2018;1–14. https://doi.org/10.1002/aqc.2934
APPENDIX 1
FISH SPECIES INVESTIGATED IN THE ANALYSES OF TRENDS IN FISH ABUNDANCE.
Temperate exploited species
Acanthopagrus australis
Achoerodus viridis
Cheilodactylus fuscus
Choerodon rubescens
Chrysophrys auratus
(Continued)
Girella tricuspidata
Notolabrus fucicola
Notolabrus tetricus
Tropical exploited species
Coris bulbifrons
12 EDGAR ET AL.
(Continued)
Lethrinus miniatus
Plectropomus leopardus
Temperate unexploited species
Acanthaluteres vittiger
Aplodactylus lophodon
Apogon limenus
Apogon victoriae
Atypichthys strigatus
Austrolabrus maculatus
Cheilodactylus nigripes
Chelmonops curiosus
Chelmonops truncatus
Chromis hypsilepis
Coris auricularis
Coris picta
Dinolestes lewini
Diodon nicthemerus
Enoplosus armatus
Epinephelides armatus
Eupetrichthys angustipes
Halichoeres brownfieldi
Heteroscarus acroptilus
Hypoplectrodes maccullochi
Kyphosus cornelii
Kyphosus sydneyanus
Labracinus lineatus
Latropiscis purpurissatus
Mecaenichthys immaculatus
Meuschenia flavolineata
Meuschenia freycineti
Meuschenia galii
Meuschenia hippocrepis
Notolabrus gymnogenis
Notolabrus parilus
Olisthops cyanomelas
Ophthalmolepis lineolatus
Parma mccullochi
Parma microlepis
Parma occidentalis
Parma unifasciata
Parma victoriae
Parupeneus spilurus
Pempheris affinis
Pempheris compressa
Pempheris klunzingeri
Pempheris multiradiata
Pictilabrus laticlavius
Pomacentrus milleri
Pseudocaranx georgianus
Pseudolabrus biserialis
Pseudolabrus guentheri
Pseudolabrus luculentus
(Continued)
Pseudolabrus mortonii
Schuettea scalaripinnis
Scorpaena cardinalis
Scorpis georgiana
Scorpis lineolata
Trachinops brauni
Trachinops noarlungae
Trachinops taeniatus
Trachurus novaezelandiae
Upeneichthys lineatus
Upeneichthys vlamingii
Tropical unexploited species
Acanthochromis polyacanthus
Acanthurus blochii
Acanthurus dussumieri
Acanthurus lineatus
Acanthurus nigricans
Acanthurus nigrofuscus
Acanthurus olivaceus
Amblyglyphidodon curacao
Amblyglyphidodon leucogaster
Amphiprion akindynos
Cephalopholis cyanostigma
Cetoscarus ocellatus
Chaetodon aureofasciatus
Chaetodon auriga
Chaetodon baronessa
Chaetodon citrinellus
Chaetodon ephippium
Chaetodon flavirostris
Chaetodon kleinii
Chaetodon lineolatus
Chaetodon melannotus
Chaetodon ornatissimus
Chaetodon pelewensis
Chaetodon plebeius
Chaetodon rainfordi
Chaetodon tricinctus
Chaetodon trifascialis
Chaetodon trifasciatus
Chaetodon unimaculatus
Chaetodon vagabundus
Cheilinus fasciatus
Chelmon rostratus
Chlorurus microrhinos
Chlorurus sordidus
Choerodon fasciatus
Chromis atripectoralis
Chromis atripes
Chromis lepidolepis
Chromis margaritifer
Chromis nitida
EDGAR ET AL.13
(Continued)
Chromis ternatensis
Chromis weberi
Chromis xanthura
Chrysiptera rex
Chrysiptera rollandi
Chrysiptera talboti
Ctenochaetus spp.
Dascyllus reticulatus
Dischistodus melanotus
Dischistodus prosopotaenia
Epibulus insidiator
Forcipiger flavissimus
Gomphosus varius
Halichoeres hortulanus
Hemigymnus fasciatus
Hemigymnus melapterus
Hipposcarus longiceps
Labroides dimidiatus
Lutjanus bohar
Lutjanus carponotatus
Lutjanus fulviflamma
Lutjanus gibbus
Lutjanus lutjanus
Macolor spp.
Monotaxis grandoculis
Naso lituratus
Naso tuberosus
Naso unicornis
Neoglyphidodon melas
Neoglyphidodon nigroris
Neoglyphidodon polyacanthus
Neopomacentrus azysron
Neopomacentrus bankieri
Parma polylepis
Plagiotremus tapeinosoma
Plectorhinchus flavomaculatus
Plectroglyphidodon dickii
Plectroglyphidodon johnstonianus
Plectroglyphidodon lacrymatus
Pomacentrus adelus
Pomacentrus amboinensis
Pomacentrus bankanensis
Pomacentrus brachialis
Pomacentrus coelestis
Pomacentrus grammorhynchus
Pomacentrus lepidogenys
Pomacentrus moluccensis
Pomacentrus nagasakiensis
Pomacentrus philippinus
Pomacentrus vaiuli
Pomacentrus wardi
Prionurus microlepidotus
Scarus altipinnis
(Continued)
Scarus chameleon
Scarus flavipectoralis
Scarus forsteni
Scarus frenatus
Scarus ghobban
Scarus globiceps
Scarus niger
Scarus oviceps
Scarus psittacus
Scarus rivulatus
Scarus rubroviolaceus
Scarus schlegeli
Scarus spinus
Siganus corallinus
Siganus doliatus
Siganus puellus
Siganus punctatus
Siganus vulpinus
Stegastes apicalis
Stegastes fasciolatus
Stegastes gascoynei
Thalassoma lunare
Thalassoma lutescens
Zanclus cornutus
Zebrasoma scopas
Zebrasoma veliferum
14 EDGAR ET AL.
