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The viability of spatially structured populations depends on the abundance and connectivity between subpopulations of breeding adults. Yet, for many species, both are extremely difficult to assess. The speartooth shark is a critically endangered elasmobranch inhabiting tropical rivers with only three adults ever recorded in Australia. Close-kin mark-recapture models, informed by sibling pairs among 226 juveniles, were developed to estimate adult abundance and connectivity in two Australian river systems. Sixty-eight sibling pairs were found, and adult abundance was estimated at 892 for the Adelaide River and 1128 for the Alligator Rivers. We found strong evidence for female philopatry, with most females returning to the same river to pup. Adelaide River males appear largely philopatric, whereas Alligator Rivers males are highly connected to the Adelaide River. From only 4 years of sampling, our results demonstrate that juvenile-only kin pairs can inform simultaneous estimates of abundance and connectivity in a rare and threatened species.

We review recent approaches and challenges in monitoring and estimating recruitment for the main commercial tuna species managed under the auspices of the five tuna Regional Fisheries Management Organizations (tRFMOs), including: (i) the stock assessment and management context, (ii) fisheries-independent recruitment monitoring successes, failures and future options, (iii) recruitment estimation methods within statistical population models and (iv) recruitment in projections for traditional stock assessment and management strategy evaluation. Despite the diversity in tuna populations and tRFMO scientific processes, there are many common recruitment themes, including: (i) fisheries-independent recruitment monitoring is difficult and rare (the aerial surveys for juvenile southern bluefin tuna, Thunnus maccoyi, and juvenile eastern Atlantic bluefin tuna stocks, T. thynnus, are the only time series used in assessments), (ii) most statistical models estimate lognormal recruitment deviations around a stationary Beverton-Holt relationship using a penalized likelihood approach, (iii) the degree of compensation in the stock-recruitment relationship and the variance is difficult to estimate (steepness is usually fixed at 0.7 ≤ h ≤ 1.0, and the CV is most often fixed with σR = 0.6 for lognormal recruitment deviations), and (iv) estimated recruitment time series often deviate systematically from the mean relationship, but it is unclear the extent to which this reflects reality (e.g. environmental change) or estimation artefacts (e.g. incorrect model assumptions or biased data). There is a trend toward the use of model ensembles to represent recruitment (and other sources of) uncertainty, both in the context of traditional assessments and management strategy evaluation. Recommendations include: i) continued development of fisheries-independent recruitment monitoring methods, including adopting emerging technologies (e.g. genetics-based mark-recapture or abundance monitoring with a network of acoustic FADs), and (ii) the management paradigm should be designed to be robust to future recruitment uncertainties (e.g. recognize that recruitment compensation might be much lower than model-based estimates or assumptions, and be prepared to respond to substantial serially-correlated recruitment deviations, e.g. regime shifts). Following a history of over-exploitation and difficulties in reaching international scientific and management consensus, the CCSBT now provides a leading example of how tuna recruitment issues might be addressed through innovative monitoring, comprehensive modelling of uncertainty, and management with simulation-tested management procedures.

Integrated stock assessments depend on reliable catch and observational data to produce unbiased estimates of fish stock biomass and productivity. However, biases in catch data due to unreported catch are common among many of the world’s fisheries, especially those that are high value and therefore more vulnerable to illegal fishing. Some of these fisheries rely on tag-recapture data to support the estimation of biomass in integrated assessments and set precautionary catch limits intended to safeguard the fish stocks from overexploitation. Tag-recapture data is generally considered to be a more powerful indicator of stock abundance than survey data if the underlying assumptions are met. The effect of unreported catches that include tagged fish on biomass estimates in tag-based integrated assessments is unclear. We used a simulation analysis to determine the impact of under-reported catch on a hypothetical Patagonian toothfish (Dissostichus eleginoides) stock. Several catch scenarios are presented that cover different magnitudes and trend types of under-reported catch. We used the CASAL model (commonly employed to assess toothfish stocks) as both the operating model and the estimation model to evaluate how the various scenarios affected estimation performance of biomass depletion. Biomass depletion was increasingly underestimated as the magnitude of under-reporting increased, regardless of trend in catch. When unreported catch exceeds twice the amount reported combined with unreported tag returns, the estimation model will fail to detect biomass has been depleted below a target reference point of 50 % within 20 years of fishing. The lack of detection will falsely indicate current catch limits are sustainable when in reality they are not. Importantly, these estimates remained largely unchanged among different trends in under-reported catch. For assessments reliant on tag-recapture data, this suggests that it is more critical to estimate the overall quantity of unreported catch and the number of unreported tagged fish than the trend.

Measuring population connectivity is a critical task in conservation biology. While genetic markers can provide reliable long-term historical estimates of population connectivity, scientists are still limited in their ability to determine contemporary patterns of gene flow, the most practical time frame for management. Here, we tackled this issue by developing a new approach that only requires juvenile sampling at a single time period. To demonstrate the usefulness of our method, we used the Speartooth shark (Glyphis glyphis), a critically endangered species of river shark found only in tropical northern Australia and southern Papua New Guinea. Contemporary adult and juvenile shark movements, estimated with the spatial distribution of kin pairs across and within three river systems, was contrasted with historical long-term connectivity patterns, estimated from mitogenomes and genome-wide SNP data. We found strong support for river fidelity in juveniles with the within-cohort relationship analysis. Male breeding movements were highlighted with the cross-cohort relationship analysis, and female reproductive philopatry to the river systems was revealed by the mitogenomic analysis. We show that accounting for juvenile river fidelity and female philopatry is important in population structure analysis and that targeted sampling in nurseries and juvenile aggregations should be included in the genomic toolbox of threatened species management.

Indonesia is a member of three tuna Regional Fisheries Management Organisations (RFMOs), but currently has limited capacity to operationally manage its tuna fisheries to maximise benefits and minimise risks of overfishing. In 2014, the Government of Indonesia initiated discussions on the potential to develop formal harvest strategies for the management of tuna resources within its archipelagic waters. This article summarizes the development of potential empirical tuna harvest strategies for use in Indonesian archipelagic waters (Fisheries Management Areas 713, 714 and 715), using skipjack tuna (Katsuwonus pelamis) and yellowfin tuna (Thunnus albacares) as demonstration case studies. The outputs of area-specific components of Western Central Pacific Ocean stock assessment were used to condition prototype operating models for testing preliminary harvest strategies by management strategy evaluation. The case studies demonstrate the utility of scientific monitoring data to track trends in abundance of adult fish, without requiring complex stock assessment models. They also demonstrate the use of relatively simple, empirical harvest control rules to adjust the levels of fishing intensity of the Indonesian fleet to achieve specific management objectives for archipelagic waters in the context of wider regional management. The approach has a broad applicability to developing coastal nations with multi-gear fisheries and relatively limited data that harvest tuna, as well as participating in RFMOs for internationally managed stocks.

Genetic and demographic analyses indicate good conservation news for southern bluefin tuna., Genetic studies of several marine species with high fecundity have produced “tiny” estimates (≤10−3) of the ratio of effective population size (Ne) to adult census size (N), suggesting that even very large populations might be at genetic risk. A recent study using close-kin mark-recapture methods estimated adult abundance at N ≈ 2 × 106 for southern bluefin tuna (SBT), a highly fecund top predator that supports a lucrative (~$1 billion/year) fishery. We used the same genetic and life history data (almost 13,000 fish collected over 5 years) to generate genetic and demographic estimates of Ne per generation and Nb (effective number of breeders) per year and the Ne/N ratio. Demographic estimates, which accounted for age-specific vital rates, skip breeding, variation in fecundity at age, and persistent individual differences in reproductive success, suggest that Ne/N is >0.1 and perhaps about 0.5. The genetic estimates supported this conclusion. Simulations using true Ne = 5 × 105 (Ne/N = 0.25) produced results statistically consistent with the empirical genetic estimates, whereas simulations using Ne = 2 × 104 (Ne/N = 0.01) did not. Our results show that robust estimates of Ne and Ne/N can be obtained for large populations, provided sufficiently large numbers of individuals and genetic markers are used and temporal replication (here, 5 years of adult and juvenile samples) is sufficient to provide a distribution of estimates. The high estimated Ne/N ratio in SBT is encouraging and suggests that the species will not be compromised by a lack of genetic diversity in responding to environmental change and harvest.

Conservation concerns exist for many sharks but robust estimates of abundance are often lacking. Improving population status is a performance measure for species under conservation or recovery plans, yet the lack of data permitting estimation of population size means the efficacy of management actions can be difficult to assess, and achieving the goal of removing species from conservation listing challenging. For potentially dangerous species, like the white shark, balancing conservation and public safety demands is politically and socially complex, often leading to vigorous debate about their population status. This increases the need for robust information to inform policy decisions. We developed a novel method for estimating the total abundance of white sharks in eastern Australia and New Zealand using the genetic-relatedness of juveniles and applying a close-kin mark-recapture framework and demographic model. Estimated numbers of adults are small (ca. 280–650), as is total population size (ca. 2,500–6,750). However, estimates of survival probability are high for adults (over 90%), and fairly high for juveniles (around 73%). This represents the first direct estimate of total white shark abundance and survival calculated from data across both the spatial and temporal life-history of the animal and provides a pathway to estimate population trend.

Using a management strategy evaluation approach, we compare a range of new and established management procedures (MPs) for setting catch-limits in fisheries. Performance is evaluated with respect to fish life history type, level of stock depletion, data quality, and autocorrelation in recruitment strength. We quantify the robustness of each MP with respect to the various observation processes. Methods using observations of absolute biomass or stock depletion offer the best overall performance and this is consistent across life history types, data qualities, and stock depletion levels. Simple MPs can outperform conventional data-limited methods and data-rich assessments that use time-series of catch and effort data. MP performance is most sensitive to biases in catch data. Our results indicate that often tuning MPs for specific stocks is important, though this may not be viable in data-poor assessment scenarios because of insufficient data and analysis resources.

Standard Brownie mark-recapture models follow tagged cohorts of fish meaning an age-based setting is required, but there are many populations for which length-at-age cannot be characterised. This paper details the derivation of a length-based Brownie mark-recapture model, with specific application to Indian Ocean skipjack tuna. Instead of following cohorts (often tagged a number of times) the model follows the recapture history of animals tagged in a given length class and period. For Indian Ocean skipjack reporting rate uncertainty, related to mixing assumptions, is accounted for using two extreme options. Various mortality model structures were explored and length-specific natural mortality and a separable model for fishing mortality were ultimately selected. Absolute values of fishing and natural mortality depend strongly on the reporting rate assumptions, with total mortality being far more robust to assumptions about reporting rates. Estimates of fishing mortality were highest between mid 2006 and mid 2008, reducing thereafter to levels estimated in late 2005/early 2006.

Density dependent population growth functions are of central importance to population dynamics modelling because they describe the theoretical rate of recruitment of new individuals to a natural population. Traditionally these functions are described with a fixed functional form with temporally constant parameters and without species interactions. The Ricker stock-recruitment model is one such function that is commonly used in fisheries stock assessment. In recent years, there has been increasing interest in semi-parametric and temporally varying population growth models. The former are related to the general statistical approach of using semi-parametric discrepancy functions, such as Gaussian processes (GP), to model deviations of data around the expected parametric function. In the latter, the reproductive rate, which is a key parameter describing the population growth rate, is assumed to vary in time. In this work, we introduce how these existing Ricker population growth models can be formulated under the same statistical approach of hierarchical GP models. We also show how the time invariant semi-parametric approach can be extended and combined with the time varying reproductive rate using a GP model. Then we extend these models to the multispecies setting by incorporating cross-covariances among species with a continuous time covariance structure using the linear model of coregionalization. As a case study, we examine the productivity of three Pacific salmon populations. We compare the alternative Ricker population growth functions using model posterior probabilities and leave-one-out cross validation predictive densities. Our results show substantial temporal variation in maximum reproductive rates and reveal temporal dependence among the species, which have direct management implications. However, our results do not support inclusion of semi-parametric discrepancy function and they suggest that the semi-parametric discrepancy functions may lead to challenges in parameter identifiability more generally.

1. Bioeconomic models are increasingly used to provide benchmarks for harvest levels in wildlife and natural resource management, yet uncertainties related to model structure are underexplored. We investigate the importance of a range of uncertainties with a focus on model structure and life histories when estimating bioeconomic target reference point (TRPs) and assess the policy implications of ignoring these uncertainties. 2. We use three contrasting case studies to investigate the interactions between model, observational and process errors related to life-history parameters: the short-lived Japanese common squid Todarodes pacificus and Pacific saury Cololabis saira, and the slow-growing Patagonian toothfish Dissostichus eleginoides. We developed a simulation framework to test the harvest strategies resulting from bioeconomic TRPs under various assumptions about model structures and parameters. 3. We found the relative importance of different types of uncertainties affecting precision and accuracy of the model outputs varied according to the life-history traits. Little difference in TRP estimates was found between simple vs. complex population models for saury, while large differences were found for toothfish. The assumptions made about stock structure for squid not only resulted in different TRP estimates (generally, smaller for the multistock models), but also different economic outcomes depending on the balance of effort allocation between stocks. 4. Synthesis and applications. We use models similar to those used in the actual management of three case study species to explore the effects of interacting uncertainties on the management advice. We show that the interactions between structural elements of the models lead to very different management advice, depending on the life history of the species concerned. For the long-lived toothfish, life-history and gear selectivity parameters interacted strongly. For the short-lived squid which is managed as two stocks, spatial fishing effort allocation, correlation of environmental drivers between stocks and differential stock productivity interacted, producing very poor economic performance if assumptions about stock structure are incorrect. The key message for model-based natural resource management is that it is vital to investigate the major uncertainties related to model structure, process and estimation errors simultaneously, because they interact to produce non-intuitive results.

There is considerable international concern and scientific debate about the current state and future of tuna stocks worldwide and the capacity of Regional Fisheries Management Organisations to manage the associated fisheries effectively. In some cases, this concern has extended to predictions of imminent collapse with minimal chances of recovery, even under a commercial catch moratorium. As a viable alternative to a full fishery closure, the Commission for the Conservation of Southern Bluefin Tuna (CCSBT) has adopted a scientifically tested, adaptive rebuilding strategy for the depleted southern bluefin tuna (Thunnus maccoyii) stock. The management procedure (MP) adopted involves a harvest control rule that fully specifies the total allowable catch as a function of key indicators of stock status, adjusting future harvest levels every three years so as to meet the rebuilding targets agreed by CCSBT. It was chosen from a subset of candidate MPs selected following extensive simulation testing. This involved first selecting a wide range of plausible scenarios for stock status and input data, ranging from pessimistic to optimistic, against which the alternative candidate MPs were tested to ensure that they were robust to important uncertainties. This is the first time that a comprehensively evaluated MP has been adopted for an internationally managed tuna stock. Both the process and the outcomes have broad applicability to other internationally managed stocks. Fil: Hillary, Richard M.. CSIRO; Australia Fil: Preece, Ann L.. CSIRO; Australia Fil: Davies, Campbell R.. CSIRO; Australia Fil: Kurota, Hiroyuki. Seikai National Fisheries Research Institute; Japón. National Research Institute of Far Seas Fisheries; Japón Fil: Sakai, Osamu. National Research Institute of Far Seas Fisheries; Japón Fil: Itoh, Tomoyuki. National Research Institute of Far Seas Fisheries; Japón Fil: Parma, Ana María. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Nacional Patagónico; Argentina Fil: Butterworth, Doug S.. University of Cape Town; Sudáfrica Fil: Ianelli, James. Alaska Fisheries Science Centre; Estados Unidos Fil: Branch, Trevor A.. University of Washington; Estados Unidos

From their first incarnation within the International Whaling Commission (IWC), management procedures (MPs) were model based, essentially being stock assessment models with associated harvest control rules (HCRs) (de la Mare 1986). The term model based means that observed data are fitted within a statistical framework that assumes a population dynamics model with associated parameters. The outputs of that fitting process (e.g. abundance, productivity, fishing mortality and trends thereof) are then used in an HCR (as either parameters or driving indices). However, more recently there has been a move towards empirical MPs (Geromont et al. 1999, De Oliveira and Butterworth 2004, de Moor et al. 2011) where derived statistics and trends from the raw observations are used in the HCR. In this chapter I will briefly cover the history of modelbased and empirical MPs, in both the literature and actually implemented, as well as the pros and cons of their utility within a full MSE framework. Finally, including worked examples, I will discuss how recent advances in both stock assessment and MSE suggest that a fusion of both approaches has real potential for future MPs.

Reduction of complexity and capacity to evaluate management strategies are important considerations when modelling complex ecosystems. Models of Intermediate Complexity for Ecosystem assessments (MICE) achieve this by representing interactions among a restricted number of crucial species in the ecosystem considered. {MICE} applications are question-driven, heavily dependent on available data for conditioning and aimed at addressing tactical issues. Here we present the development of a {MICE} for the central Adriatic Sea. This area is important ecologically and economically because it supports a commercial stock of Norway lobster (Nephrops norvegicus), and a nursery ground for European hake (Merluccius merluccius), as well as being subjected to high levels of fishing pressure. Here, Italian and Croatian bottom trawl fisheries mainly target Norway lobster while impacting juvenile hake. Single-species stock assessments for the target species indicate fluctuating trends between 2006 and 2013, as do the survey biomass trends of most of their prey, underlining the need for a multispecies management plan. The diet of the target species were examined and prey items partitioned into four groups. Consumption of prey groups by predators was modelled using a Holling Type {II} functional response. A modified biomass dynamic model was used to represent the prey dynamics, projecting them into the future for 10 years (2013-2022) and testing different management strategies, including a discard ban. The most effective management option was the protection of larger individuals, which led to a clear improvement in the stock abundance and spawning stock biomass of both hake and Norway lobster without significant adverse effects on their prey. The discard ban scenario appeared to have knock-on effects on both predators and some of their prey.

Meta-analytic and multi-level stock–recruit analyses have traditionally focussed on the similar stock approach, but for a specific stock–recruit model. For six European herring stocks we embed both the stock and model levels within a fully Bayesian hierarchical framework, thus permitting the consideration of a wider class of models, specifically those that do not admit parameterisation via the steepness and unfished spawning potential. Model and parametric uncertainty is jointly characterised and the challenge of addressing model selection when the model itself is part of the hierarchy is addressed using the deviance information criterion (DIC) and posterior predictive analysis. For the six herring stocks the across-stock posterior evidence in favour of over-compensatory dynamics is fairly strong, with the Ricker and Shepherd models performing the best across the model-selection criteria. For a specific model form we perform a 20 year retrospective analysis (hierarchical and non-hierarchical) to see how temporal information flow occurs in a hierarchical framework, how this can improve our estimates of key parameters, and how this might influence management paradigms (such as Maximum Sustainable Yield) that are based on such estimates.

Stakeholders increasingly expect ecosystem assessments as part of advice on fisheries management. Quantitative models to support fisheries decision-making may be either strategic (‘big picture’, direction-setting and contextual) or tactical (focused on management actions on short timescales), with some strategic models informing the development of tactical models. We describe and review ‘Models of Intermediate Complexity for Ecosystem assessments’ (MICE) that have a tactical focus, including use as ecosystem assessment tools. MICE are context- and question-driven and limit complexity by restricting the focus to those components of the ecosystem needed to address the main effects of the management question under consideration. Stakeholder participation and dialogue is an integral part of this process. MICE estimate parameters through fitting to data, use statistical diagnostic tools to evaluate model performance and account for a broad range of uncertainties. These models therefore address many of the impediments to greater use of ecosystem models in strategic and particularly tactical decision-making for marine resource management and conservation. MICE are capable of producing outputs that could be used for tactical decision-making, but our summary of existing models suggests this has not occurred in any meaningful way to date. We use a model of the pelagic ecosystem in the Coral Sea and a linked catchment and ocean model of the Gulf of Carpentaria, Australia, to illustrate how MICE can be constructed. We summarize the major advantages of the approach, indicate opportunities for the development of further applications and identify the major challenges to broad adoption of the approach.

Short-lived fisheries stocks are subject to large fluctuations in abundance and respond rapidly to many factors including changes in oceanographic conditions, biological interactions and fishery exploitation. Management of such species requires a flexible, adaptive framework that responds rapidly to a changing environment, although such schemes are rarely operationalized. In this article, we develop a set of bioeconomic adaptive management schemes that respond to changes in economic conditions, stock abundance and catchability, using as case studies the fisheries targeting short-lived Japanese common squid (Todarodes pacificus) and Pacific saury (Cololabis saira). We suggest that such adaptive schemes have the potential to support the successful implementation of profit maximizing (MEY-based) harvest policies for borderline profitable fisheries targeting short-lived species.

Deepwater fish populations are often characterized by their life-history as being highly susceptible to overexploitation. Moreover, dependent fisheries often develop rapidly, so overexploitation may occur before resource dynamics are quantified sufficiently to assess safe biological limits. It is therefore crucial to employ assessment methods that make the best use of limited data and management procedures that account for large uncertainties. This review provides a critical synthesis of assessment and management approaches for deepwater fisheries. Given limitations in the data, it is clear that assessments are likely to benefit from the application of derived relationships between life-history characteristics and the sharing of this and other information across stocks. It is important that uncertainty in assessment results is represented adequately, and management methods must in turn ensure that decision mechanisms are robust to an incomplete picture of resource dynamics. This requires construction and ...

The economics of enforcement is traditionally modelled using rational agents assumed to act according to their expected economic utility. In this investigation we derive this expectation by implementing a stochastic simulation model to integrate across associated levels of uncertainty using Monte Carlo. The model is developed for the South Georgia toothfish longline fishery, in which legal catches are strictly managed according to the Commission for the Conservation of Antarctic Marine Living Resources (CCAMLR) conservation measures. Assuming full compliance in the legal fishery, this investigation deals with the role of a fishing patrol vessel (FPV) in excluding illegal fishing vessels. Both legal and illegal fleets are dynamic. For the legal fleet, catch is set by a harvest control rule within the model framework, with vessels leaving if fishing becomes unprofitable. The illegal catch is determined by the number of vessels operating, which predicts catch on the basis of an estimated production function. The exit of illegal vessels is determined by the probability of detection by the FPV, which is a function of days spent on patrol, and estimated profits. The entry of illegal vessels occurs at a fixed mean rate, with the model integrating over uncertainty in this parameter. An obvious trade off exists in that higher levels of illegal activity lead to lower expected returns to the legal fleet. We thus provide a cost-benefit framework for investigating the trade-offs associated with decisions on enforcement in the fishery, and confirm that current enforcement effort levels are well justified.

The fishery for Patagonian toothfish around the island of South Georgia in the Southern Ocean is a profitable operation targeting a high-value, slow-growing species. We substituted the complex Bayesian age-structured model currently used for assessments with a Schaefer production model, which performs equally well as an operating model for management strategy evaluation. Our analysis demonstrated that optimum long-term profitability using a discount rate of 2% would be achieved at a biomass of 59% of initial biomass, which is higher than the target biomass of 50% incorporated into the current management strategy, and at a reduction in effort of approximately 19%. A number of potential effort reduction strategies are investigated, several of which would achieve better conservation objectives and higher future profits from the fishery than those predicted using the current management strategy. JEL Classification Codes: Q22, Q28

Maravelias, C. D., Hillary, R., Haralabous, J., and Tsitsika, E. V. 2010. Stochastic bioeconomic modelling of alternative management measures for anchovy in the Mediterranean Sea. – ICES Journal of Marine Science, 67: 1291–1300. The purse-seine fishery for anchovy in the Aegean Sea consists of two main fleet segments (12–24 and 24–40 m vessels); this paper investigates economically and biologically preferable effort and capacity scenarios for the fishery. Attention is paid to a bioeconomic analysis of fleets composed of segments with varying levels of efficiency (in terms of catch rate) and costs (fixed and variable) and the role this might play in optimal effort allocation at a fleet level. An age-structured stochastic bioeconomic operating model for Aegean anchovy (Engraulis encrasicolus) is constructed. It attempts to account robustly for the multiple uncertainties in the system, including (i) the effort–fishing mortality relationship, (ii) the selectivity, and (iii) the stock–recruit dynamics of the population. A method is proposed for determining the economically optimal level of long-term effort in a fishery such as this, with similar characteristics in terms of stock dynamics, fishery, and markets. Lower values of effort and capacity are predicted to yield greater future profit when viewing the fleet in its entirety, but even lower values may be advisable to maintain the long-term biological integrity of the stock. The results may prove useful in balancing the productivity of the stock with the harvesting capacity of the fleet, while managing to ensure the long-term profitability of the fleet along with the sustainability of the resource.

Fisheries libraries in R (FLR) is an open-source software framework based in the R statistical software environment, with the main purpose of allowing for the efficient simulation and evaluation of fisheries management strategies. This paper details a generic (non-spatial) biological operating model used to simulate populations and their reaction to fishing, and an observation error model and methods for simulating structured sampling/observation error and bias in key fisheries assessment indices. It also contains the details of how the candidate harvest control rules, based on survey-derived information, can be characterised and implemented, and how the processes of management strategy evaluation and stock assessment can be included in the simulations.

Consideration of control rules as part of fisheries management plans is becoming a common practice. Control rules may be simple or complex and utilise model- or observation-based indicators of the status of the stock to control exploitation through limitation of effort or catches. Rules that control harvest (HCR) often utilize commercial fishery data in the calculation of future catches. However, commercial fishery data may be inaccurate and that can compromise the effectiveness of the HCR in maintaining the stock for secure future harvesting. The idea of fishery-independent HCR has arisen because of these problems. Indicators of the status of a stock are derived from standardised fish surveys, commonly trawl surveys repeated annually. A management strategy that relies on such information also requires adoption of appropriate and effective control rules that utilise such information. Here, we draw attention to diverse HCR, including fishery-dependent examples that have been considered, tested or already adopted for fisheries management. Our intention is to stimulate ideas for HCR that are usable with, or adaptable to fishery-independent indicators.

Kell, L. T., Mosqueira, I., Grosjean, P., Fromentin, J-M., Garcia, D., Hillary, R., Jardim, E., Mardle, S., Pastoors, M. A., Poos, J. J., Scott, F., and Scott, R. D. 2007. FLR: an open-source framework for the evaluation and development of management strategies. – ICES Journal of Marine Science, 64: 640–646. The FLR framework (Fisheries Library for R) is a development effort directed towards the evaluation of fisheries management strategies. The overall goal is to develop a common framework to facilitate collaboration within and across disciplines (e.g. biological, ecological, statistical, mathematical, economic, and social) and, in particular, to ensure that new modelling methods and software are more easily validated and evaluated, as well as becoming widely available once developed. Specifically, the framework details how to implement and link a variety of fishery, biological, and economic software packages so that alternative management strategies and procedures can be evaluated for their robustness to uncertainty before implementation. The design of the framework, including the adoption of object-orientated programming, its feasibility to be extended to new processes, and its application to new management approaches (e.g. ecosystem affects of fishing), is discussed. The importance of open source for promoting transparency and allowing technology transfer between disciplines and researchers is stressed.

The crown-of-thorns starfish (COTS) Acanthaster planci is one of the largest causes of coral cover loss on Australia's Great Barrier Reef. Numerous trophic-mediated and anthro- pogenic-related hypotheses, singly or in combination, have been proposed to explain COTS out- breaks, but the evidence remains inconclusive. There is, however, an urgent need for effective control and mitigation strategies. We develop a model of intermediate complexity for ecosystem assessments to describe the trophic interactions between juvenile and adult COTS and 2 groups of coral (fast- and slow-growing corals). By fitting to available data, the impact of prey-switching behaviour by COTS and its effects on the system are quantified. Simulations are used to evaluate the effects of (1) predation by large fish on adult COTS, (2) predation by benthic invertebrates on juvenile COTS, and (3) manual removal of adult COTS. The results highlight the effectiveness of invertebrate predation at reducing juvenile COTS numbers and suggest that manual removal is unlikely to be an effective control method except on a small scale. Our model focuses on the importance of trophic interactions in COTS control and provides an initial platform for future work which foresees the estimation of the effects of key predators, no-take areas, anthropogenic nutrient enhancement, and reef connectivity in mediating the spatio-temporal heterogeneity of COTS outbreaks.