Download Assessing the adequacy of current fisheries

ICES Journal of Marine Science (2011), 68(6), 1305–1317. doi:10.1093/icesjms/fsr049
Assessing the adequacy of current fisheries management under
changing climate: a southern synopsis
Éva E. Plagányi 1*, Scarla J. Weeks 2, Tim D. Skewes 1, Mark T. Gibbs 1, Elvira S. Poloczanska 3,
Ana Norman-López 3, Laura K. Blamey 4, Muri Soares 4, and William M. L. Robinson 4
1
CSIRO Wealth from Ocean Flagship, PO Box 2583, Brisbane, QLD 4001, Australia
Centre for Spatial Environmental Research and Coral Reef Ecosystems Laboratory, University of Queensland, QLD 4072, Australia
3
CSIRO Climate Adaptation Flagship, CMAR, PO Box 2583, Brisbane, QLD 4001, Australia
4
Department of Mathematics and Applied Mathematics, University of Cape Town, Private Bag X3, Rondebosch 7701, South Africa
2
*Corresponding Author: tel: +61 738 335955; fax: +61 738 335508; e-mail: [email protected].
Plagányi, É. E., Weeks, J. S., Skewes, T. D., Gibbs, M. T., Poloczanska, E. S., Norman-López, A., Blamey, L. K., Soares, M., and Robinson,
W. M. L. 2011. Assessing the adequacy of current fisheries management under changing climate: a southern synopsis. – ICES Journal of
Marine Science, 68: 1305– 1317.
Received 30 June 2010; accepted 6 March 2011; advance access publication 12 May 2011.
Climate change is likely to have a significant impact on both target and non-target marine stocks worldwide, with the concomitant
need for management strategies capable of sustaining fishing in future. We use several southern hemisphere fisheries to highlight the
likely impacts of climate change at a range of levels, from individual to population responses, as well as ecosystem ramifications.
Examples span polar (Antarctic krill fishery), temperate (west coast pelagic fishery, abalone and rock lobster), and tropical (Torres
Strait rock lobster) commercially important fisheries. Responses of these fisheries to either past observed environmental changes
or projected future changes are used to deduce some anticipated implications of climate change for fisheries management, including
economic impacts and governance considerations. We evaluate the effectiveness of current single-species assessment models, management strategy evaluation approaches and multispecies assessment models as future management tools to cope with likely climaterelated changes. Non-spatial stock assessment models will have limited ability to separate fishery effects from the impacts of
climate change. Anthropogenic climate change is occurring at a time-scale relevant to current fisheries management strategic planning
and testing. Adaptive management frameworks (with their feedback loops) are ideal for detecting and adapting to changes in
target stocks.
Keywords: adaptive management, climate change, fisheries economics, fisheries management, management procedure.
Introduction
There is increasing evidence worldwide that global climate change is
affecting both terrestrial and marine ecosystems, and this change is
likely to continue in future (Karl and Trenberth, 2003;
Hoegh-Guldberg et al., 2007; IPCC, 2007; Cheung et al., 2009a, b).
Research to date has focused on terrestrial impacts, although major
changes in temperature, acidity, ocean currents, and productivity
are predicted to occur in the oceans (Behrenfeld et al., 2006; IPCC,
2007). Climate change is likely to have a significant impact on both
target and non-target marine stocks worldwide, with the concomitant need for management strategies capable of sustaining future
fishing. Fisheries scientists and managers will have to grapple with
a number of pertinent questions, including the following.
(i) What are the likely fishery responses expected under changing climate?
(ii) Are these responses likely to occur on time-scales relevant to
short-term, tactical management decisions?
(iii) How will strategic decision-making benefit from prior
understanding of potential changes?
# 2011
(iv) How should we adjust and adapt our single-species and
ecosystem-based assessment tools and models?
(v) How should we adapt fisheries management?
We use several southern hemisphere fisheries (Figure 1) to highlight the likely impacts of climate change at a range of levels, from
individual to population responses, as well as ecosystem ramifications. Examples are drawn from polar (Antarctic krill fishery and
dependent predator species), temperate (South African pelagic
fishery, abalone, and rock lobster), and tropical (Torres Strait
rock lobster) fisheries. Responses of these fisheries to either past
observed environmental changes or projected future changes are
used to deduce some anticipated implications of climate change
for fisheries management, including economic impacts and governance considerations. We cannot always conclusively link
observed changes with anthropogenic climate change (rather
than decadal environmental variability, for example). However,
we have included examples of responses to environmental
changes to the extent that they might be useful in informing on
likely future responses to climate change. We evaluate the effectiveness of current single-species assessment models, management
International Council for the Exploration of the Sea. Published by Oxford Journals. All rights reserved.
For Permissions, please email: [email protected]
1306
É. E Plagányi et al.
Figure 1. Map of Australia, Antarctica, and South Africa illustrating case study sites.
Figure 2. Strategic approaches to complement tactical fisheries
assessment under changing climate.
strategy evaluation approaches, and multispecies assessment
models as future management tools to cope with likely
climate-related changes.
Case studies
We provide an overview of a broad range of southern hemisphere
fisheries as demonstrations of the likely impacts of climate change
on stocks at all levels, from individual to ecosystem, and seek
common lessons to be drawn from these examples regarding
implications for fisheries management. The case studies are used
to reinforce a range of strategic approaches that could be used to
complement tactical fisheries assessment under changing climate
(Figure 2). Although there is increasingly a move towards an ecosystem approach to fisheries management, conventional targetspecies assessment models are nonetheless predominantly used
to provide management recommendations to achieve sustainability of key fishery stocks. A range of approaches could be used to
complement current fisheries management in response to changing climate (Figure 2).
We selected four case studies that collectively illustrate the
impacts of environmental variability at all levels, from population
to ecosystem, and simultaneously serve as examples of ways to
modify tactical fisheries assessment methods to account for the
kinds of variability to be expected under climate change. The
first case study evaluated the performance of a traditional stock
assessment model that was developed for the South African
abalone (Haliotis midae) fishery. This case study highlights the
need for spatial disaggregation to detect environmentally mediated
species range extensions or contractions (Figure 2); in this case by
the lobster Jasus lalandii. Our second case study evaluated the
utility of modifying a stock assessment model for Torres Strait
rock lobster (Panulirus ornatus) to test plausible physiological
impacts of climate change on population parameters, as well as a
method for examining the related economic consequences
(Figure 2). Our third case study elucidated the information that
could be gained from using an MSE approach for the South
African purse-seine fishery. The fourth case study highlights
some of the pros and cons of using ecosystem models for assessment of climate change impact on Antarctic krill and its predators
(Figure 2).
Given the broad range of fishery types and locations selected,
we could not compare model performance across case studies
and concede that different model types might have performed
better if applied to the various case studies. This analysis uses a retrospective approach to evaluate the performance of different
assessment tools as applied to manage commercially valuable
target species.
The four case studies identify some of the issues that
should be integrated into an actively adaptive management
framework for guiding fisheries management under changing
climate (Figure 3). These examples include assessments and
operating models that have been broadened to consider
environmental, economic, and ecosystem factors in a
simulation-testing framework. MSE models test alternative
model formulations, including scenarios where the user considers different drivers and their implications for management,
and they quantify uncertainties in predicting the implications
of climate change.
Fisheries management under changing climate in the southern hemisphere
1307
Figure 3. Schematic summary of an actively adaptive feedback loop forming an outer loop around a management strategy evaluation testing
feedback loop, as a framework for embedding fisheries management when affected by changing climate. Management procedure frameworks
(with their feedback loops) are predicted to be more successful regarding detecting and stalling fishery downturns.
Figure 4. Illustration of the importance of incorporating spatial
structure in an assessment model challenged with separating
environmentally induced impacts from the impacts of overfishing
because of high levels of illegal, unregulated, and unreported (IUU)
catches. The example uses the spatial and age-structured assessment
model for South African abalone (H. midae) and it indicates the total
spawning biomass (relative to 1980) in selected Zones A (subject to
IUU fishing, but not invaded by lobsters) and D (subject to both
impacts).
Case study 1. Stock assessment and multispecies
extensions: abalone– rock lobster interactions
in temperate latitudes
The West Coast rock lobster J. lalandii and abalone H. midae fisheries are two of South Africa’s major fisheries. Whereas the bulk of
the lobster catches are taken off the West Coast, the abalone fishery
is centred largely on the southeast coast.
An eastward shift in the West Coast rock lobster took place in
the early 1990s along the southwest coast of South Africa, in an
area known as East of Cape Hangklip (EOCH; Cockcroft et al.,
2008; Figure 1). Reasons for the shift are unknown, but it might
be linked to changes in environmental conditions. Roy et al.
(2007) and Rouault et al. (2009) observed that cooling of
inshore waters took place on the south coast of South Africa
during the 1980s/1990s. The EOCH area coincides with what
was once the heart of the commercial abalone fishery. The shift
in West Coast rock lobster happened during a period of intense
illegal fishing of abalone from the mid-1990s on (Hauck and
Sweijd, 1999; Plagányi et al., 2011) and a lobster-induced period
of decline in urchins, Parechinus angulosus (Tarr et al., 1996;
Mayfield and Branch, 2000). Juvenile abalone have a close association with the urchin, whereby they take shelter beneath urchin
spines, receiving both nourishment and protection (Day and
Branch, 2000a, b). West Coast rock lobsters are voracious predators that feed on a variety of prey (Mayfield et al., 2000a, b,
2001; van Zyl et al., 2003). They have the ability to alter ecosystem
structure completely (Barkai and Branch, 1988a, b; Barkai
and McQuaid, 1988).
The abalone resource in the EOCH area is assessed using a
spatial and age-structured production model (Plagányi and
Butterworth, 2010). The model simultaneously assesses five population components in five adjacent areas as a means of reducing
potential confounding between different mortality factors
(natural mortality, environmentally induced mortality effect, and
additional mortality because of illegal catches). Output from this
model illustrates the importance of correctly attributing declines
to fishing impacts compared with environmental factors (which
might be the result of anthropogenic climate change; Figure 4).
Resource abundance indices indicated a steep decline in abalone
in both the two western areas invaded by lobsters, as well as the
two eastern areas without lobsters (Figure 4). Separating these
two impacts was facilitated in this case by the spatial structure of
the assessment model (fitted to population size-structure data
available for contrasting areas), which revealed a relatively
steeper overall decline in the lobster-invaded areas (Figure 4).
Case study 1 provides an example of a replacement of one commercially valuable fishery with another, namely South African
abalone with West Coast rock lobster (Figure 5). The environmental
changes resulted in complex, non-linear ecosystem responses, which
1308
were not predicted beforehand and are incorporated in an indirect
way only in the abalone and rock lobster assessment models. An
intermediate complexity multispecies model of urchin–lobster–
abalone interactions (Blamey, 2010) was used to simulate the
lobster increase (Figure 5) and proved valuable in increasing the
understanding of the underlying mechanisms and potential reversibility of the ecosystem change. A better strategic planning of management responses might have ameliorated subsequent social and
economic implications of the species replacement.
Case study 2. Stock assessment extensions and economic
impacts: Torres Strait rock lobster in tropical latitudes
The Torres Strait tropical rock lobster (TRL), P. ornatus, fishery is the
most important commercial fishery to Torres Strait Islanders and
provides significant financial independence for island communities
in the region. In addition, the fishery provides significant income
for non-indigenous fishers living in and outside Torres Strait. The
fishery is managed by the Protected Zone Joint Authority (PZJA),
comprising representatives from the Australian and Queensland governments under Article 22 of the Torres Strait Treaty (February 1985)
between Australia and Papua New Guinea.
Figure 5. Illustration of the replacement of one commercially
valuable fishery, South African abalone H. midae (solid line), with
another, west coast rock lobster J. lalandii (dashed line) in the east of
Cape Hangklip region. The upper trajectory plotted on the left-hand
axis indicates the total spawning biomass (t) (from Plagányi and
Butterworth, 2010), whereas the lower trajectory on the right-hand
axis is the simulated lobster biomass from a minimally realistic
ecosystem model (Blamey, 2010).
É. E Plagányi et al.
This case study investigates the possible biological and socioeconomic effects of climate change to the Torres Strait TRL
fishery. Hypothesized responses of lobster growth, mortality, distribution, and migration in each fishing sector were gathered
from the literature, unpublished experimental studies, and
expert consultation. Impacts were projected at three different life
stages (juveniles defined as pre-maturation moult, adults, and
larvae) under climate change scenarios. Responses were assessed
in an impact-likelihood framework to identify the overall risk to
the lobster population. The hypothesized high risk (.5%
change in a lobster production parameter; scenario I) and high
plus moderate risk (scenario II) effects under emission A1B
(IPCC, 2007) were implemented through modifications to the
lobster stock assessment model (Plagányi et al., 2009), as described
in the following section.
Many climate change impacts can be tested readily with simple
modifications to key parameters in commonly applied assessment/operating models. For example, variations in age-dependent
natural mortality rates are easily accommodated. Many models
already represent growth as year-dependent; or changes to the
von Bertalanffy growth parameters (as in this example) could be
used as a proxy.
One of the biggest challenges is modifying the stock –recruit
relationships in more classic stock assessment models (Hollowed
et al., 2009; Schirripa et al., 2009). This is confounded to some
extent, because estimated or assumed stock –recruit relationships
represent an integrated composite of a number of effects.
Environmental impacts on fish recruitment are typically
accounted for by estimating annual residuals or deviations about
a stock –recruit curve, such as a Beverton –Holt formulation.
However, if climate change results in a change in the underlying
carrying capacity of a stock, it might be preferable to accommodate this by incorporating a shift to a new curve, rather than a
gradual change in the fitted relationship as new data are added
each year (Figure 6). As another example, assuming there is a
decrease in stock resilience because of a climate-mediated range
contraction, this might result in many serially correlated recruitment observations that suggest lower than average expected
recruitment. In such a case, refitting the stock– recruit relationship
would result in a lower steepness estimate (Figure 6), whereas
ignoring such a change to the underlying S –R formulation
might overestimate resilience to fishing.
Figure 7a shows changes to projected Torres Strait TRL spawning biomass (t) assuming a constant future fishing mortality and
when comparing the base-case scenario with climate change
Figure 6. Schematic of considerations affecting assumed stock– recruit formulations under changing climate. The upper plot is an example
where climate change causes an increase (star symbols and upper curve) or decrease (lower curve) in the underlying carrying capacity K of a
stock. The lower plot is an example of a climate-mediated range contraction mediating a decrease in stock resilience (star symbols and new
curve).
Fisheries management under changing climate in the southern hemisphere
1309
Figure 8. Summary of the projected impact on employment of
Torres Strait islanders and non-islanders working in sectors as
illustrated. The two hypothetical climate change scenarios are
simulated as described in the text.
Figure 7. (a) Summary of changes to projected P. ornatus spawning
biomass (t), assuming a constant future fishing mortality and when
comparing the base-case scenario with climate change scenarios
I and II, as described in the text. (b) Economic impact on Torres
Strait islander and non-islander sectors, of hypothetical climate
change scenarios I and II.
scenarios I and II. Torres Strait TRL is a highly variable,
fast-growing species, and changes to individual growth and survival are translated into changes in spawning biomass and sustainable catch (based on a target fishing mortality level). These
results suggest that there could be positive as well as negative consequences in response to resource dynamics changes driven by
climate change.
Projected catches (Figure 7b) were input to an Input– Output
model of the Australian economy (Norman-López and Pascoe,
2010) to determine the income and employment flow-on effects
of climate change impacts affecting the lobster population
(Figures 7b and 8). A necessary assumption in estimating these
impacts was that management and regulation of the fisheries
would operate in the same way in 2030 as it does today. Hence,
we present future impacts based on no adaptation to climate
change.
Results indicate that climatic changes to Torres Strait TRL are
likely to have economic effects on islander and non-islander
fisheries in the region. This in turn will have subsequent flow-on
effects to other intermediate and final demand sectors in the
local (Torres Strait) and national economy. The income and
employment effects for fishers, intermediate sectors, final
demand, and overall net effects sectors are summarized in
Figure 7b. The estimated income and employment effects vary
with respect to the base scenario, depending on how total
catches are likely to change with climate change. Hence, income
and employment effects increase with higher catches (scenario I)
and vice versa (scenario II). Furthermore, from the estimated
income effects in Figure 7b, the flow-on income effects (intermediate and final demand sectors) in the islander fisheries are
higher than those for the non-islander fisheries, despite the
islander sector generating lower wages and profits. This highlights
the sensitivity of the Torres Strait economy to changes in the
islander sector relative to the non-islander sector, given that
islander fishers spend their income in the Torres Strait economy.
The employment effects are presented in Figure 8. Direct and
intermediate employment effects are the same for all the scenarios.
The reason is that this study assumed the capacity in the fishery
remains the same up to 2030. Conversely, the employment
effects for final demand sectors vary with the different climate
change scenarios. The reason for this is that changes to islanders
and non-islanders income effects (in Figure 7) will change the
demand for goods and services from other sectors, which in
turn will have to adjust production and employment levels to
satisfy this demand.
Case study 2 demonstrates a pragmatic method for evaluating
the overall impacts on stock productivity and economic outcomes
of climate effects operating on individual growth and survival. The
net effects could be positive or negative, depending on the severity
of the climate impacts, and has a relatively greater effect on the
traditional fisheries sector.
1310
Case study 3. Linking population models and MSEs:
African penguins and pelagic fish
The South African purse-seine fishery targets anchovy Engraulis
encrasicolus and sardine Sardinops sagax, with the two stocks
jointly managed using an operational management procedure
(OMP—analogous to an MSE; de Moor and Butterworth, 2008).
The use of this adaptable management procedure has demonstrable advantages in responding rapidly (without increasing
risk) to major changes in resource abundance, as happened
when both species peaked concurrently around the turn of the
century (de Moor and Butterworth, 2008). It consequently rates
highly as a tool for dealing with changes in resource abundance
as might be expected under changing climate.
A complicating factor in this fishery is that there had recently
been an eastward shift in the distribution of sardine, although
the underlying causative mechanisms are as yet not fully understood (Roy et al., 2007; Coetzee et al., 2008). The shift was possibly
environmentally mediated, with an abrupt change in environmental forcing influencing the relative favourability of eastern
and western spawning locations (Roy et al., 2007). The shift in
the distribution of sardine away from the west coast region,
where fish-processing facilities are located, has had major economic and logistical implications for both the fishery and its management (Coetzee et al., 2008). This also has linked implications
for the status and management of the African penguin
Spheniscus demersus (Crawford et al., 2006), which motivated
development of a penguin population dynamics model that
could be linked to the pelagic OMP to take account of the relationship between the breeding success of African penguins and the
abundance of both fish species.
An increase in penguin numbers during 2000– 2004 happened
simultaneously with a period of high pelagic fish abundance
(Figure 9). Following poor recruitment to the fishery in
2004–2008, the total sardine biomass dropped substantially (de
Moor and Butterworth, 2007). In addition, sardine shifted eastwards, out of reach of penguins based at the major colonies at
Robben Island and Dassen Island (Figure 1). During the same
period, the number of penguin breeding pairs at those colonies
decreased by 75% (Crawford et al., 2008). A lack of available
food is considered the main cause of higher adult mortality and
lower breeding success in recent years.
Figure 9. Biomass estimates for sardine Sardinops sagax near South
African West Coast penguin colonies displayed alongside model
estimates of total abundance of African penguin Spheniscus
demersus at Robben and Dassen Islands.
É. E Plagányi et al.
A feasibility study was therefore undertaken to assess the
power of a long-term experiment aimed at identifying the effects
on penguins of prohibiting fishing in areas next to colonies.
Data collected include GPS foraging tracks, diet composition,
reproductive success, and chick condition. A confounding factor
with experiments such as this pertains to the low power to
detect direct negative impacts of fishing on a dependent predator.
Case study 3 exemplifies the need to separate the role of fishing
vs. environmental effects in driving changes in a dependent predator. Clearly local declines should be interpreted in a broader
spatial context that accounts for species range shifts. Preliminary
simulations suggested that a major reduction in overall pelagic
fish catch hardly benefits penguins (Robinson et al., 2008); other
management measures such as closed areas might be preferred.
Rather than developing a full ecosystem model, the approach of
linking a population model of a non-targeted dependent predator
species to the management procedure for a highly variable target
species constitutes a pragmatic method for assessing the risks
under changing climate to both fisheries and dependent predators.
Case study 4. Ecosystem considerations: Polar region
krill and predators
Although future climate predictions for the Southern Ocean are
highly uncertain, recent IPCC assessments consistently indicate
decreases in sea ice around Antarctica (IPCC, 2007). There is evidence of particularly rapid climate change affecting the Antarctic
Peninsula region, regarding both warming and decreases in
winter sea ice duration (Nicol, 2006; Murphy et al., 2007;
Stammerjohn et al., 2008a, b). These changes are affecting the
Antarctic marine ecosystem at all levels from primary production
to apex predators (Ducklow et al., 2007). Based on net tow data,
Atkinson et al. (2004) suggested a long-term decline in krill abundance in the southwest Atlantic over the period 1976–2004,
although acoustic time-series do not reflect the same trends
(Hewitt et al., 2004). Recent studies, such as that of Brown et al.
(2010), should be useful in further informing regarding the net
effect of temperature on krill growth and reproduction.
Predictions of climate change impacts on krill are confounded,
because of the inherent variability in krill abundance and recruitment. Given strong linkages between krill and the advance and
extent of sea ice, it could be a key indicator of ecosystem responses
to climate change (Ducklow et al., 2007).
In the southwest Atlantic sector, krill is very important as a
food source for predators and is simultaneously the target of an
expanding fishery. Penguins are potentially highly sensitive to
climate change (SST warming and sea ice loss) with recorded
responses, including poleward shifts in geographic distribution,
range contractions or expansions, changes in phenology, and
in predator–prey interactions (Forcada and Trathan, 2009;
Chapman et al., 2010).
A spatial multispecies operating model (SMOM) of krill –
predator–fishery dynamics has been developed by Plagányi
and Butterworth (2008) as a tool for advising on the subdivision
of the precautionary catch limit for krill (Euphausia superba)
among 15 small-scale management units (SSMUs) in the Scotia
Sea, to reduce the potential impact of fishing on predators.
SMOM is spatially structured and it simulates predation on krill
as a key forage species by four predator groups, namely penguins,
seals, fish, and whales.
To illustrate ecosystem model considerations under changing
climate, SMOM was used to project predator populations to
Fisheries management under changing climate in the southern hemisphere
1311
Figure 10. Illustrative projection using SMOM of the numbers of
penguins at South Georgia East under scenarios assuming constant
future krill compared with a 1 and 3% annual decrease. The dark
lines are medians, whereas the shaded area displays the 90%
Hessian-based confidence interval for the 1% krill decline scenario.
2030 under a range of hypothetical climate change scenarios, with
a focus on penguins, given the posited sensitivity of this group.
Rather than explicitly modelling climate impacts on krill, for
illustrative purposes, projections assumed that there would be an
overall negative effect on krill and the following two simulations
were run: (i) a more conservative climate scenario under which
krill in each SSMU decreased by 1% per annum, and (ii) a more
extreme scenario with krill decreasing by 3% per annum for all
years from base-year 2005. The predator populations in each of
the 15 SSMUs were projected forward under these two scenarios.
Given a subset of results is sufficient to illustrate the points being
made here, results are presented for two SSMUs only—a more
northern South Georgia location (South Georgia East) and a
more southern Antarctic Peninsula location (Drake Passage East;
Figures 10 and 11).
Model projections are displayed as the median of 120 replicates that account for major parameter uncertainty and
some, but not all, model structural uncertainty (in particular,
simulations assume that there is no movement of krill
between SSMUs). The 90% confidence interval is illustrated
for a single scenario only (for ease of viewing) to highlight
the difficulty of distinguishing a relatively large climate-induced
impact, when confounded by additional uncertainty regarding
individual species population dynamics and trophic interactions
(Figure 10).
Under the conservative projection scenario, it is difficult to
differentiate between the relative depletion after 25 years at the
South Georgia vs. Antarctic Peninsula sites (Figure 11a). The
more extreme scenario suggested a relatively greater impact on
penguins at the more northern South Georgia location
(Figure 11b), although the outcome was reversed for krilldependent fish (represented by myctophids and perciforms;
Figure 11c). The spatial structure of SMOM is clearly advantageous in simulating potential multispecies responses to climate
change, but nonetheless the simple simulations trialled here highlight a number of shortcomings of this and equally many other
Figure 11. Illustrative projections using SMOM of the numbers
(relative to the 2005 base-year) of (a and b) penguins and (c) fish at
South Georgia East (dashed line) and an Antarctic Peninsula site
(solid line) under conservative and extreme projection scenarios
(which assume a 1 and 3% annual decrease in krill abundance,
respectively).
ecosystem approaches regarding realistically predicting climate
change impacts.
The model has been tuned to represent continuous rather
than threshold changes; therefore, although this particular modelling framework is flexible enough to simulate large migrations
of species groups between areas, as well as prey switching, there
is currently insufficient biological understanding to parametrize
accurately these responses. Nonetheless, decreases in krill populations in response to anthropogenic climate change are a strong
possibility and clearly will have marked and differential impacts
on different species groups at different locations. In addition,
this is likely to have significant impacts on the krill fishery
(Kawaguchi et al., 2009); this is particularly so given that a
fishery that depends on fishing dense krill concentrations
would naturally track changes in abundance of the target
species, with such compensation for reduced abundance in
some areas confounded by spatial management allocation constraints. Therefore, the robustness of spatial management allocations for the krill fishery should be assessed under a range
of climate change scenarios. This is facilitated by having an ecosystem model embedded in a management procedure
framework.
1312
Change in spatial
distribution of fleet
Likely decreasing krill
abundance; shift
in distribution
of predators
Costly changes in spatial
distribution of fleet
African penguin Benguela
Environmental: eastward Change in distribution, but not
Stock assessment models;
upwelling
shift in pelagic fish
necessarily overall abundance of
OMP with coupled
system, South
distribution
pelagic fish; local declines in
penguin population
Africa
penguin abundance
dynamics model
Penguins, seals, South Georgia,
Climate: decreasing krill Krill and predator changes in
Ecosystem model (SMOM)
fish, whales
Antarctica
abundance and distribution
Single-species stock
assessment model
Warmer water, changed acidity,
altered circulation
Torres Straits,
Climate: increasing
Australia, and
temperature
PNG
Environmental change System response
Environmental: eastward Increasing lobsters and declining
encroachment of
abalone
lobsters
Fishery management tools
used for predictions
Single-species stock
assessment models;
multispecies model
Dominant (biological)
effect on fishery
Abalone fishery closed;
lobster fishery
commenced in new
area
Change in individual
growth, survival,
productivity, and
settlement
Change in centre of
distribution
Pelagic fish
(sardine
and
anchovy)
Krill
There are several examples of short-term changes, e.g. spatial shifts
in the distribution of sardine stocks (Coetzee et al., 2008) and the
rapid decline in urchin populations, closely followed by decreases
in abalone recruitment modelled in our first example. Fisheries
managers might dismiss the importance of engaging with
Torres Straits TRL
rock lobster
fishery
Are these responses likely to occur on time-scales
relevant to short-term, tactical management decisions?
System
South Coast,
South Africa
Responses to environmental change at all levels from individual to
community should be integrated into all levels of fisheries management. The Torres Straits lobster example most clearly indicated
how changes at the individual physiological level might ultimately
translate into changes in overall population abundance and productivity, with this in turn affecting the relative fishery take and
profitability of different sectors. This underscored that an integrated understanding of the entire process is necessary to plan
adaptive management and governance responses effectively.
Our pelagic fish– penguin case study highlighted that environmentally induced changes in a fishery could be mirrored by
changes in dependent species. Analyses of these interactions
should separate the role of fishing vs. environmental effects in
driving changes in a dependent predator. However, as in this
South African example, there is often low power to detect direct
negative impact of fishing on dependent predators
Dependent/
related species
Lobsters
What are the likely fishery responses to expect under
changing climate?
Fishery
Abalone
Our study has attempted an overview of potential climate change
impacts on fisheries at all levels: (i) individuals (carrying capacity,
reproductive potential, larval settlement, spatial distribution)
(ii) population (productivity, spatial distribution); (iii) multispecies
(replacement of one fishery by another), and (iv) ecosystem
(dependent predator species, changes in community composition;
Table 1). Examples span a range of latitudes within the southern
hemisphere, from tropical to temperate and polar. We selected
four case studies that collectively illustrate the impacts of environmental variability on fisheries and simultaneously serve as examples
of ways to modify tactical fisheries assessment methods (Table 2) to
account for the kinds of variability to be expected under climate
change.
We recognize that many other approaches could have been
applied to address each of the case studies and that it would be
useful to consider alternative approaches through a formal
model selection process. Hollowed et al. (2009) outline methods
for addressing the uncertainty associated with model selection,
as well as other significant process and measurement errors.
However, that is beyond the scope of our paper and we have
focused instead on selecting examples that are modifications or
extensions to the models currently used for the management of
these resources. We allude to both advantages and disadvantages
of the various approaches, given that they collectively span a
wide range of fisheries modelling tools (from single-species to ecosystem models and MSE approaches) as well as serve as examples
of potential climate change impacts on fisheries across the spectrum from individual to population level effects, as well as
broader ecosystem considerations.
Based on the lessons learned from the case studies presented,
we summarize below preliminary responses to the fisheries –
climate questions posed in the introduction.
Table 1. Summary of four case studies used as examples of system responses to environmental changes, as a means of informing on likely future biological and economic responses to
climate change.
Discussion
Dominant (economic)
effect on fishery
Local fishery closed;
partial offsets through
new lobster fishery in
this area
Small effect nationally,
but large impact
locally
É. E Plagányi et al.
Fishery
Abalone
Torres
Straits
rock
lobster
fishery
Operating
model used
in an MSE
approach?
No
Maximum
likelihood
estimation
or Bayesian
MLE
Fishery assessment
Age
tool used
structure?
Yes
Single-species stock
assessment models;
multispecies model
Spatial
structure?
Yes
Interspecies interactions
and dependencies?
Represented using proxy in
assessment model and
explicitly in a related
multispecies model that
includes lobsters, urchins,
and fish
Single-species stock
assessment model
Yes
No
No
No, but under
development
Yes
No
Assesses impacts of changes
in pelagic fish on
dependent penguin
population
Yes
Research survey indices of
abundance and catch taken
before recruitment survey
Bayesian
No
Yes
Four predator groups
(penguins, seals, whales,
fish) explicitly modelled
as dependent on krill
Yes, under
development
Population biomass estimates in
each spatial area, krill and fish
catches
–
Pelagic fish Stock assessment
models; OMP with
(sardine
coupled penguin
and
population
anchovy)
dynamics model
Krill
Ecosystem model
(SMOM)
Key data inputs
Model fitted to extensive cpue and
survey indices of abundance,
catch-at-age information, legal
catches, and illegal abalone
confiscation records, abalone
recruitment index, lobster
indices of abundance
Model fitted to survey indices of
abundance, catch-at-age
information, catches, fishery
economic information
MLE
Key assumptions in context
of this paper
Rock lobsters invaded part of
range during the 1990s and
consumed all the urchins,
thereby reducing shelter for
juvenile abalone and affecting
abalone recruitment
negatively
Climate change could result in
increases in water
temperature that affects
lobster growth positively, but
other changes might operate
in the opposite direction
Eastward shift in centre of
distribution of sardine reduces
local availability of prey for
penguin populations
References for
models
Blamey (2010),
Plagányi and
Butterworth
(2010), Plagányi
et al. (2011)
Climate change could result in
substantial reductions in local
densities of krill, thereby
affecting dependent predators
negatively
Plagányi and
Butterworth
(2008)
Plagányi et al.
(2009)
Fisheries management under changing climate in the southern hemisphere
Table 2. Summary of key features of the models used to assess the case study fisheries, dependent predators, and system responses to environmental changes.
de Moor and
Butter worth
(2008), Robinson
et al. (2008)
1313
1314
climate change issues under the impression that such impacts are
likely to occur on a much longer time-scale than that relevant to
the provision of short-term, tactical management advice.
However, the examples presented here indicate that responses to
environmental changes can affect resources on a time-scale relevant to the fisheries assessment and management time-scale.
This is both regarding interpretation of data used to inform assessments, as well as the testing of harvest strategies in management
procedure frameworks. Given the difficulties in forecasting such
rapid changes, a pragmatic solution resides in formally setting
up an actively adaptive feedback cycle (Figure 3).
How will strategic decision-making benefit from prior
understanding of potential changes?
Prediction of species shifts and replacements might be possible
using fishery models and would allow a better strategic adaptation
and planning of management responses. Models can play an
important proactive role in trying to predict changes on the
horizon, rather than relying solely on a more reactive management
style.
The abalone case study is a clear demonstration of environmental changes resulting in replacement of one fishery by
another commercially valuable fishery, although models are generally limited in their ability to predict such species replacements. As
demonstrated by the pelagic fish example, changes in the distribution of a fishery could have a major impact on the economic
efficiency and governance of a fishery. Adaptable management
systems that allow trading of fishery rights might provide solutions
in some contexts.
How should we adjust and adapt our single-species
and ecosystem assessment tools and models?
Single-species assessment models
Regarding assessing how well current fisheries management performs under climate change, it was clear from the abalone
example that spatial structuring is often essential to separate the
effects of fishing and environmental change (Figure 4). Stock
assessment models classically assume a single homogenous stock
and they are consequently predicted to fail in their ability to
separate fishery effects from the impacts of climate change.
Single-species management procedure frameworks (with their
feedback loops) are predicted to be more successful at detecting
and stalling downturns in a target stock, but will still be limited
in their longer-term ability to manage stocks sustainably under
changing climate, unless they include spatial structure, environmental forcing, or a broader ecosystem perspective (Figure 3).
Climate impact proxies can be used in assessment and operating models. Further investigations, such as those of Maunder and
Watters (2003) and Schirripa et al. (2009), are required to test
different methods of incorporating environmental variability
into stock assessments. Steele and Gifford (2010) enunciate the
need in providing advice to management to bridge the gap
between short-term, individual-stock forecasts, and longer-term
assessments of community production and resilience. The robustness of management decision rules could be tested using MSE
approaches (Figure 3).
Ecosystem models
Despite considerable progress in the development of ecosystem
models that can potentially be useful to inform fisheries management, they are nonetheless still subject to considerable uncertainty
É. E Plagányi et al.
(Plagányi, 2007). This is compounded in the current context by
the need to drive these models with anthropogenic climate
change scenarios, themselves uncertain, and project changes in
low- to high-trophic level species and communities. In reality,
ecosystem responses are both complex and usually non-linear.
Thus far, there has been reasonable success in modelling environment –plankton relationships, and very limited success in establishing environment –fish recruitment correlations (see Myers,
1998, for a review) so predicting fish and higher trophic level
responses to environmental change remains a challenge. As
demonstrated by the krill –penguin simulation, uncertainties in
ecosystem models (such as parameter and model structural uncertainty) could confound distinguishing climate impacts.
We presented two (intermediate complexity) ecosystem modelling examples only, respectively, applied to the abalone –lobster–
urchin system and Antarctic krill ecosystem. Models such as
these could be valuable in increasing understanding of the underlying mechanisms and potential reversibility of system changes.
However, both models have reinforced the understanding that
environmental changes could result in complex non-linear ecosystem responses that are difficult to predict (e.g. Figures 5 and 11).
An adaptive management approach that permits rapid response
to short-term changes might therefore be a better strategy to
adopt for management than explicit predictive modelling of
environmental –fisheries relationships.
Correctly representing trophic interactions in ecosystem
models with climate forcing might require an explicit spatial structure (given differential effects with latitude, e.g. Figure 11),
accounting for changes in carrying capacity and testing across a
range of potential non-linear responses. Ecosystem models are
typically better designed to represent continuous rather than
threshold effects. Responses to changing climate, such as sudden
movements of penguins to more southern breeding locations,
are difficult to accommodate (and predict) in most current ecosystem model structures. Moreover, there is increasing uncertainty as
we move far from equilibrium conditions (Figure 10); for example,
in the Antarctic system modelled, as krill populations decline, seals
might switch from feeding on krill to icefish (Agnew et al., 1988).
Despite the challenges outlined above, there is clearly a need for
ecosystem models as strategic tools for exploring possible
responses to climate change. Nonetheless, model results and
interpretations should be accompanied by statements regarding
the associated degree of uncertainty and where possible, the
robustness of any management conclusions drawn should be
assessed under a range of plausible scenarios. To strengthen confidence in climate-forced ecosystem model predictions, there is a
need for monitoring as part of an adaptive learning feedback
process (Figure 3).
Management procedure frameworks
Management procedure frameworks (with their feedback loops)
are useful tools for detecting and adapting to changes in target
stocks (Figure 3). Because there are practical limitations to including ecosystem effects explicitly in fisheries models and management procedures, an interim solution resides in implementing
potential effects in management procedure evaluation exercises
implicitly only (Plagányi et al., 2007). For example, rather than
developing complicated multispecies testing models to contribute
to its revised management procedure development process, the
IWC Scientific Committee adopted a simpler approach of
allowing for time-dependence in the intrinsic growth-rate and
Fisheries management under changing climate in the southern hemisphere
carrying-capacity parameters of the single-species operating model
for the population under harvest (Punt and Donovan, 2007).
Similarly, MP testing procedures for fisheries can use simplified
surrogates for climate change impacts. A’mar et al. (2009) examined the effect of climate change on the performance of the management strategy for walleye pollock (Theragra chalcogramma).
Their study demonstrates how the MSE approach could be used
to identify alternative management strategies that display
improved robustness to the effects of climate change.
Our schematic adaptive management under changing climate
framework (Figure 3) proposes a broadening of components
that might have to be included in an operating model. This
includes economic and socio-cultural factors, which are key concerns under changing climate (see also Table 1). Full ecosystem
or coupled oceanographic –biological models could be used as
operating models, or realistic climate drivers could simply be
input to test the sensitivity of model predictions to likely scenarios.
Given the uncertainty associated with ecosystem responses to
climate forcing, management models should ideally include a
monitoring component and harvest strategies evaluated across a
range of biological, economic, and social indicators to the extent
possible. Our schematic includes an additional actively adaptive
management loop as an outer loop around a management strategy
evaluation testing loop to accommodate regular updates in
scientific understanding of climate change impacts affecting each
individual fishery.
How should we adapt fisheries management?
Retrospective analysis suggests that the main impact of changes in
the distribution and species composition of stocks is on economic
efficiency (Table 1); clearly, there is a need for adaptable and
strategic management systems.
For the first time in human history, through climate science,
humanity has the ability to predict possible and likely scenarios
for key environmental parameters out to at least 100 years
(McCarthy et al., 2001). Although there is clearly a level of uncertainty in climate projections, as time goes by the evidence that at
least some of the projections might be borne out increases. A
clear signal evident from climate science is that the variability of
environmental conditions might increase in coming decades and
this is likely to result in changes to the productivity and in some
cases distribution of marine biota. Many argue that this is
already happening. An increasing number of studies seek to understand how these changes might influence both the biophysical and
socio-economic implications for capture fisheries, as presented
here. However, the other obvious question also arises: how
should the governance and management systems for fisheries
change to manage through changes associated with climate
variability and change?
Interestingly, fishers, fishing communities, and resource managers are already accustomed to variability in resource productivity
and in some cases distribution, because substantial stock variability is inherent in almost all fished stocks. Therefore, it is reasonable
to expect that current management systems are already adept at
managing with this inherent uncertainty. However, it may also
be argued, and often is, that in many cases, rather than managing
these stocks, fisheries go through a process of fishing down stocks
to commercial extinction, then moving onto new stocks.
The counter argument to this is that through scientific stock
assessment and management approaches, such as MSE, we now
have the ability to manage single stocks sustainably. Therefore, if
1315
we follow this argument, then even in the face of climate change
we should have the ability to manage stocks effectively; if the
rate of change of the environment will not increase to a point
where the current approaches cannot respond to change rapidly
enough. The South African pelagic fish case study serves as an
example of the ability of a well-tested MSE approach to respond
rapidly (without increasing risk) to major changes in resource
abundance (de Moor and Butterworth, 2008; de Moor et al.,
2008).
Often, it is clear that the current management system cannot
adequately manage through major stock fluctuations or prevent
irreversible overfishing and overcapitalization and in such cases,
it is conceivable that increased variability resulting from climate
variability and change might make these management systems
less effective, if not dysfunctional. It is also conceivable that
some management systems that are currently only just able to
cope might also become dysfunctional in the face of increased
variability (Gibbs, 2007).
It can therefore be argued that the key attributes of a management system, which in effect is a system of managing property
rights (Gibbs, 2009), that can manage through climate variability
and change are actually the same set of attributes that any
robust fishery management system must display, as identified by
Goodin (1996), for example.
Looking ahead, dealing with inherent uncertainty will remain
one of the greatest challenges for management, as it is today.
Hence, regarding governance and management systems, looking
forward to an era of increased variability, the following two
drivers are critical: reducing the cost per observation and analysis
and simplifying and streamlining dispute resolution processes.
Interestingly, both could be achieved through the collection and
appraisal of more informative and higher resolution data
streams and this can only be achieved through the development
and application of science and technology.
Acknowledgements
Funding to attend the International Symposium on Climate
Change Effects on Fish and Fisheries was provided by ICES to
AN-L and to ÉEP by Hokkaido University Global Center of
Excellence programme (HUGCOE). This research was funded by
CSIRO, Australia, and the National Research Foundation of
South Africa. We thank Sean Pascoe for his helpful comments
on the economic analyses. Two referees and the editor provided
many helpful comments.
References
Agnew, D. J., Everson, I., Kirkwood, G. P., and Parkes, G. B. 1998.
Towards the development of a management plan for the mackerel
icefish (Champsocephalus gunnari) in Subarea 48.3. CCAMLR
Science, 5: 63 – 77.
A’mar, Z. T., Punt, A. E., and Dorn, M. W. 2009. The evaluation of two
management strategies for the Gulf of Alaska walleye pollock
fishery under climate change. ICES Journal of Marine Science,
66: 1614– 1632.
Atkinson, A., Siegel, V., Pakhomov, E., and Rothery, P. 2004.
Long-term decline in krill stock and increase in salps within the
Southern Ocean. Nature, 432: 100– 103.
Barkai, A., and Branch, G. M. 1988a. Contrasts between the benthic
communities of subtidal hard substrata at Marcus and Malgas
Islands: a case study of alternative stable states? South African
Journal of Marine Science, 7: 117 – 137.
1316
Barkai, A., and Branch, G. M. 1988b. The influence of predation and
substratal complexity on recruitment to settlement plates: a test of
the theory of alternative states. Journal of Experimental Marine
Biology and Ecology, 124: 215 – 237.
Barkai, A., and McQuaid, C. 1988. Predator– prey role reversal in a
marine benthic ecosystem. Science, 242: 62 – 64.
Behrenfeld, M. J., O’Malley, R. T. O., Siegel, D. A., McClain, C. R.,
Sarmiento, J. L., Feldman, G. C., Milligan, A. J., et al. 2006.
Climate-driven trends in contemporary ocean productivity.
Nature, 444: 752 – 755.
Blamey, L. K. 2010. Ecosystem effects of a rock-lobster ‘invasion’:
comparative and modelling approaches. PhD thesis, University of
Cape Town.
Brown, M., Kawaguchi, S., Candy, S., and Virtue, P. 2010. Temperature
effects on the growth and maturation of Antarctic krill (Euphausia
superba). Deep Sea Research, 57: 672– 682.
Chapman, E. W., Hofmann, E. E., Patterson, D. L., and Fraser, W. R.
2010. The effects of variability in Antarctic krill (Euphausia
superba) spawning behavior and sex/maturity stage distribution
on Adélie penguin (Pygoscelis adeliae) chick growth: a modeling
study. Deep Sea Research, 57: 543– 558.
Cheung, W. W. L., Lam, V. W. Y., Sarmiento, J. L., Kearney, K.,
Watson, R., and Pauly, D. 2009b. Projecting global marine
biodiversity impacts under climate change scenarios. Fish
and Fisheries, 10: 235– 251.
Cheung, W. W. L., Lam, V. W. Y., Sarmiento, J. L., Kearney, K.,
Watson, R., Zeller, D., and Pauly, D. 2009a. Large-scale redistribution of maximum fisheries catch potential in the global ocean
under climate change. Global Change Biology, 16: 24 – 35.
Cockcroft, A. C., van Zyl, D., and Hutchings, L. 2008. Large-scale
changes in the spatial distribution of South African West Coast
rock lobsters: an overview. African Journal of Marine Science, 30:
149– 159.
Coetzee, J. C., van der Lingen, C. D., Hutchings, L., and Fairweather, T.
P. 2008. Has the fishery contributed to a major shift in the distribution of South African sardine? ICES Journal of Marine Science,
65: 1676– 1688.
Crawford, R. J. M., Barham, P. J., Underhill, L. G., Shannon, L. J.,
Coetzee, J. C., Dyer, B. M., Leshoro, T. M., et al. 2006. The influence of food availability on breeding success of African penguins
Spheniscus demersus at Robben Island, South Africa. Biological
Conservation, 132: 119– 125.
Crawford, R. J. M., Underhill, L. G., Coetzee, J. C., Fairweather, T.,
Shannon, L. J., and Wolfaardt, A. C. 2008. Influence of the abundance and distribution of prey on African penguins Spheniscus
demersus off western South Africa. African Journal of Marine
Science, 30: 167– 175.
Day, E. G., and Branch, G. M. 2000a. Relationships between recruits of
abalone Haliotis midae, encrusting corallines and the sea urchin
Parechinus angulosus. South African Journal of Marine Science,
22: 137– 144.
Day, E. G., and Branch, G. M. 2000b. Evidence for a positive relationship between juvenile abalone Haliotis midae and the sea urchin
Parechinus angulosus in the South-Western Cape, South Africa.
South African Journal of Marine Science, 22: 145– 156.
de Moor, C. L., and Butterworth, D. S. 2007. Base case assessment of
the South African sardine resource. Marine and Coastal
Management Document, MCM/2007/SEP/SWG-PEL/06: 30pp.
de Moor, C. L., and Butterworth, D. S. 2008. Proposed Final OMP-08.
Marine and Coastal Management Document, MCM/2008/
SWG-PEL/09: 1 – 42.
de Moor, C. L., Butterworth, D. S., and Coetzee, J. C. 2008. Revised
estimates of abundance of South African sardine and anchovy
from acoustic surveys adjusting for echosounder saturation in
earlier surveys and attenuation effects for sardine. African
Journal of Marine Science, 30: 219 – 232.
É. E Plagányi et al.
Ducklow, H. W., Baker, K., Martinson, D. G., Quetin, L. B., Ross, R. M.,
Smith, R. C., Stammerjohn, S. E., et al. 2007. Marine pelagic ecosystems: the West Antarctic Peninsula. Philosophical Transactions of
the Royal Society, Series B, 362: 67 –94.
Forcada, J., and Trathan, P. N. 2009. Penguin responses to climate
change in the Southern Ocean. Global Change Biology, 15:
1618– 1630.
Gibbs, M. T. 2007. Network governance in fisheries. Marine Policy, 32:
113– 119.
Gibbs, M. T. 2009. Individual transferrable quotas and ecosystembased fisheries management: it’s all in the T. Fish and Fisheries,
10: 470– 474.
Goodin, R. E. 1996. The Theory of Institutional Design. Cambridge
University Press, Cambridge. 249 pp.
Hauck, M., and Sweijd, N. A. 1999. A case study of abalone poaching
in South Africa and its impact on fisheries management. ICES
Journal of Marine Science, 56: 1024 – 1032.
Hewitt, R. P., Watters, G., Trathan, P. N., Croxall, J. P., Goebel, M. E.,
Ramm, D., Reid, K., et al. 2004. Options for allocating the precautionary catch limit of krill among small-scale management units in
the Scotia Sea. CCAMLR Science, 11: 81 – 97.
Hoegh-Guldberg, O., Mumby, P. J., Hooten, A. J., Steneck, R. S.,
Greenfield, P., Gomez, E., Harvell, C. D., et al. 2007. Coral reefs
under rapid climate change and ocean acidification. Science, 318:
1737– 1742.
Hollowed, A. B., Bond, N. A., Wilderbuer, T. K., Stockhausen, W. T.,
A’mar, Z. T., Beamish, R. J., Overland, J. E., et al. 2009. A framework for modelling fish and shellfish responses to future climate
change. ICES Journal of Marine Science, 66: 1584– 1594.
IPCC. 2007. Climate Change 2007: the Physical Science Basis.
Contribution of Working Group I to the Fourth Assessment
Report of the Intergovernmental Panel on Climate Change. Ed.
by S. Solomon, D. Qin, M. Manning, Z. Chen, M. Marquis, K. B.
Averyt, M. Tignor, et al. Cambridge University Press, Cambridge.
996 pp.
Karl, T. R., and Trenberth, K. E. 2003. Modern global climate change.
Science, 302: 1719– 1723.
Kawaguchi, S., Nicol, S., and Press, A. J. 2009. Direct effects of climate
change on the Antarctic krill fishery. Fisheries Management and
Ecology, 16: 424 – 427.
Maunder, M. N., and Watters, G. M. 2003. A general framework for
integrating environmental time series into stock assessment
models: model description, simulation testing, and example.
Fishery Bulletin US, 101: 89 – 99.
Mayfield, S., Atkinson, L. J., Branch, G. M., and Cockcroft, A. C.
2000a. Diet of the West Coast rock lobster Jasus lalandii:
Influence of lobster size, sex, capture depth, latitude and moult
stage. South African Journal of Marine Science, 22: 57– 69.
Mayfield, S., and Branch, G. M. 2000. Interrelations among rock lobsters, sea urchins and juvenile abalone: implications for community management. Canadian Journal of Fisheries and Aquatic
Sciences, 57: 2175– 2185.
Mayfield, S., Branch, G. M., and Cockcroft, A. C. 2000b. Relationships
among diet, growth rate, and food availability for the South African
rock lobster, Jasus lalandii (Decapoda, Palinuridea). Crustaceana,
73: 815– 834.
Mayfield, S., de Beer, E., and Branch, G. M. 2001. Prey preference and
the consumption of sea urchins and juvenile abalone by captive
rock lobsters (Jasus lalandii). Marine and Freshwater Research,
52: 773– 780.
McCarthy, J. J., Canziani, O. F., Leary, N. A., Dokken, D. J., and White,
K. S. 2001. Climate Change 2001: Impacts, Adaptation and
Vulnerability. Contribution of Working Group II to the Third
Assessment Report of the Intergovernmental Panel on Climate
Change (IPCC). Cambridge University Press, Cambridge.
Murphy, E. J., Watkins, J. L., Trathan, P. N., Reid, K., Meredith, M. P.,
Thorpe, S. E., Johnston, N. M., et al. 2007. Spatial and temporal
Fisheries management under changing climate in the southern hemisphere
operation of the Scotia Sea ecosystem: a review of large-scale links
in a krill centred food web. Philosophical Transactions of the Royal
Society, Series B, 362: 113 – 148.
Myers, R. A. 1998. When do environment – recruitment correlations
work? Reviews in Fish Biology and Fisheries, 8: 285 – 305.
Nicol, S. 2006. Krill, currents, and sea ice: Euphausia superba and its
changing environment. BioScience, 56: 111 – 120.
Norman-López, A., and Pascoe, S. 2010. Net economic effects of
achieving maximum economic yield in fisheries. Marine Policy,
35: 489– 495.
Plagányi, É. E. 2007. Models for an Ecosystem Approach to Fisheries.
FAO Fisheries Technical Paper, 477. 108 pp.
Plagányi, É. E., and Butterworth, D. S. 2008. An updated description
and parameterisation of the spatial multi-species operating
model (SMOM). Workshop Document Presented to WG-SAM
subgroup of CCAMLR (Commission for the Conservation of
Antarctic Marine Living Resources), WG-SAM-08/17. 35 pp.
Plagányi, É. E., and Butterworth, D. S. 2010. A spatial and
age-structured assessment model to estimate poaching and ecosystem change impacting the management of South African abalone
Haliotis midae. African Journal of Marine Science, 32: 207 –236.
Plagányi, É. E., Butterworth, D. S., and Burgener, M. 2011. Illegal and
unreported fishing on abalone – quantifying the extent using a fully
integrated assessment model. Fisheries Research, 107: 221 – 232.
Plagányi, É. E., Dennis, D., Kienzle, M., Ye, Y., Haywood, M., Mcleod, I.,
Wassenberg, T., et al. 2009. TAC estimation and relative lobster
abundance surveys 2008/09. Australian Fisheries Management
Authority Torres Strait Research Program Final Report. AFMA
Project Number, 2008/837. 81 pp.
Plagányi, É. E., Rademeyer, R. A., Butterworth, D. S., Cunningham,
C. L., and Johnston, S. J. 2007. Making management procedures
operational—innovations implemented in South Africa. ICES
Journal of Marine Science, 64: 626 – 632.
Punt, A. E., and Donovan, G. P. 2007. Developing management procedures that are robust to uncertainty: lessons from the
International Whaling Commission. ICES Journal of Marine
Science, 64: 603– 612.
1317
Robinson, W., Plagányi, É. E., and Butterworth, D. S. 2008. Illustrative
outputs of the age-structured model of African penguin populations for linking to the pelagic OMP testing process. Document
MCM/2008/SWG-PEL/27.
Rouault, M., Penven, P., and Pohl, B. 2009. Warming in the Agulhas
Current system since the 1980s. Geophysical Research Letters, 36:
L12602, doi:10.1029/2009GL037987.
Roy, C., van der Lingen, C. D., Coetzee, J. C., and Lutjeharms, J. R. E.
2007. Abrupt environmental shift associated with changes in the
distribution of Cape anchovy Engraulis encrasicolus spawners in
the southern Benguela. African Journal of Marine Science, 29:
309– 319.
Schirripa, M. J., Goodyear, C. P., and Methot, R. M. 2009. Testing
different methods of incorporating climate data into the assessment of US West Coast sablefish. ICES Journal of Marine
Science, 66: 1605– 1613.
Stammerjohn, S. E., Martinson, D. G., Smith, R. C., and Iannuzzi, R.
A. 2008a. Sea ice in the western Antarctic Peninsula region: spatiotemporal variability from ecological and climate change perspectives. Deep Sea Research, 55: 2041 –2058.
Stammerjohn, S. E., Martinson, D. G., Smith, R. C., Yuan, X., and
Rind, D. 2008b. Trends in Antarctic annual sea ice retreat and
advance and their relation to El Niño-Southern Oscillation and
southern annular mode variability. Journal of Geophysical
Research, 113: C03S90. doi:10.1029/2007JC004269.
Steele, J. H., and Gifford, D. J. 2010. Reconciling end-to-end and
population concepts for marine ecosystems. Journal of Marine
Systems, 83: 99 – 103.
Tarr, R. J. Q., Williams, P. V. G., and Mackenzie, A. J. 1996. Abalone,
sea urchins and rock lobster: a possible ecological shift that may
affect traditional fisheries. South African Journal of Marine
Science, 17: 319– 323.
Van Zyl, R. F., Mayfield, S., and Branch, G. M. 2003. Aquarium experiments comparing the feeding behaviour of rock lobster Jasus
lalandii on abalone and sea urchins at two sites on the west coast
of South Africa. African Journal of Marine Science, 25: 377 – 382.