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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. 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