Small islands are highly vulnerable to climate change as rising sea levels, warming temperatures and ocean acidification threaten marine ecosystems, livelihoods and traditional way of life. The Australian Torres Strait Islands are a low-lying archipelago between northern Australia and Papua New Guinea and face existential threats akin to small island developing states in the Pacific. We analyse trends in ocean and atmospheric variables and synthesise changes that occurred in key Torres Strait marine habitats and resources since the 1970 s. We find increasing trends in temperature, marine heatwaves, sea surface height and dry-season wind run. Other variables including solar exposure, rainfall, river discharge and net primary productivity show variability but no trend, and are typically aligned with large El Niño Southern Oscillation (ENSO) events. Habitats such as mangroves, seagrass meadows and coral reefs are naturally variable, but sensitive to compounding climate extremes, including ENSO-related anomalies and sustained ocean warming. Our study further explores the dependence of commercial and cultural fisheries on these foundation habitats, highlighting that habitat fluctuations combined with ocean warming are already impacting some fisheries (e.g. tropical rock lobster). Cultural totemic species such as dugongs and green turtle are also under pressure from climate change. Our synthesis informs efforts to respond and adapt to climate change. Moreover, we highlight that several interconnected initiatives are needed, including long-term monitoring, climate change communication, adaptive strategies for fisheries and communities, as well as strong governance and policy support alongside continued efforts to empower communities through capacity building, education, and equitable engagement.

Developing ecosystem models has traditionally been limited to a small global community of experts because of the complex skills and resources required. However, the emergence of user-friendly artificial intelligence (AI) tools with powerful generative capabilities could democratize ecosystem modeling, enabling both experts and nonspecialists to build models. We explore a speculative future where AI enables automated end-to-end model development and application. Although such tools could accelerate and enhance modeling tasks, their widespread adoption raises concerns about data integrity, bias, interpretation reliability, and the potential erosion of human expertise. We argue that regardless of AI's technical advancement, human engagement and control remain essential. The global community must respond by identifying key factors that distinguish desirable outcomes and developing infrastructure, standards, and ethical guidelines to ensure AI use in ecosystem modeling remains scientifically robust while supporting sustainable and equitable outcomes.

Most fisheries stock assessments rely on fishery dependent data to a large extent, with catch per unit effort a key indicator of changes in stock conditions. However, increases in fishing efficiency due to changes in technology and physical fleet attributes distort the relationship between observable effort (e.g., days or hours fished), catch and biomass. To compensate, a key component of fisheries stock assessment is the estimation of changes in fishing power over time to adjust catch rate information for this "effort creep". Two approaches have developed in parallel for estimating changes in efficiency of fishing vessels over time. An approach commonly applied in stock assessment is engineering-based, focusing on changes in physical inputs. In contrast, economic based approaches have developed for assessing efficiency change that also capture non-physical inputs such as fisher skill, management changes and resulting behavioural change. We apply both of these approaches to the Australian Northern Prawn Fishery (NPF) and test the degree to which the derived efficiency time series agree. We find that the two series are highly correlated and cointegrated, suggesting that both provide a consistent measure of efficiency change over time. In the case of the NPF, this validates the current method used to adjust for effort creep in the stock assessments.

Fisheries based on short lived species are notoriously difficult to manage using traditional effort or catch quota controls. Such fisheries are often characterised by high fecundity, requiring only a small spawning stock to potentially produce a large biomass the following year. This stock, or at least its availability, is driven by unpredictable environmental conditions to a large extent, with the available biomass depleted over the fishing season though both natural and fishing mortality. In most instances, management of these fisheries has focused on ensuring sufficient escapement at the end of the season to allow sufficient recruitment the following year. Catch-rate triggers are one such management tool to determine when fishing should cease. In this study, the use of such triggers in the banana prawn sub-fishery of the Australian Northern Prawn Fishery are assessed. The fishery has an explicit objective of achieving maximum economic yield, and the triggers are set on an economic basis during the season based on price and cost information provided by the industry. The in-season estimates provided by industry were highly correlated with information derived retrospectively through an economic survey, with the industry-provided estimates generally resulting in a more conservative (i.e., higher) break-even catch-rate level. It is the profit maximising behaviour of the fishers, however, that results in the greatest benefits, with most boats leaving the fishery before the trigger catch-rate is reached. The catch-rate trigger operates more as a “safety-net” for the fishery, and possibly a nudge encouraging vessels to maximise their profits given their individual cost structures.

Demands on freshwater for human use are increasing globally, but water resource development (WRD) has substantial downstream impacts on fisheries and ecosystems. Our study evaluates trade-offs between WRDs and downstream ecosystem functioning considering alternative dam and water extraction options, diverse eco-hydrological responses and catchment-to-coast connectivity. We used a data-driven ensemble modelling approach to quantify the impacts of alternative WRDs. WRD impacts varied from weakly positive to severely negative depending on species, scenario and cross-catchment synergies. Impacts on fishery catches and the broader ecosystem (including mangroves) increased with catchment developments and volume of water removed, or if flow reduced below a threshold level. We found complex, linked-catchment dependence of banana prawns on flow and floods. Economic risks for this important fishery more than doubled under some scenarios. Sawfish emerged as the most sensitive across a range of WRD scenarios. Our findings highlight the need to consider marine ecosystems and fisheries to inform sustainable management of the world’s remaining free-flowing rivers.

Integrated management (IM) has been widely proposed, but difficult to achieve in practice, and there remains the need for evaluation of examples that illustrate the practical issues that contribute to IM success or failure. This paper synthesises experiences of academics and practitioners involved in seven Australian case studies in which there have been attempts to integrate or take a broader, holistic perspective of management. The evaluative framework of Stephenson et al. (2019a) was used as a lens to explore, through workshops and a questionnaire survey, the nine key features and five anticipated stages of IM in the Gladstone Harbour Project, the Great Barrier Reef, the Northern Prawn fishery and regional development, the South-East Queensland Healthy Waterways Partnership, the Australian Oceans Policy, the New South Wales Marine Estate reforms, and progress toward Integrated Management in the Spencer Gulf. Workshops involving experts with direct experience of the case studies revealed that most of the key features (recognition of the need; a shared vision for IM; appropriate legal and policy frameworks; effective process for appropriate stakeholder participation; comprehensive suite of objectives (ecological, social, cultural, economic and institutional); consideration of trade-offs and cumulative effects of multiple activities; flexibility to adapt to changing conditions; process for ongoing review, evaluation and refinement; and effective resourcing) were seen as important in all case studies. However, there are only a few examples where key features of IM were implemented ‘fully’. A subsequent questionnaire of participants using ‘best-worst’ scaling indicated that an appropriate legal and institutional framework is considered to have most influence on IM outcomes, and therefore is the most important of the key features. This is followed in salience by effective stakeholder participation, effective resourcing, capacity and tools, and recognition of the need for IM. Key features may change in relative importance at different stages in the trajectory of IM.

Consideration of economic outcomes is commonplace in most fisheries management systems globally, although only a few jurisdictions have adopted an economic objective as the primary target for fisheries management. Such an objective has been adopted for Australia's federally managed fisheries, with maximum economic yield (MEY) identified as the primary management objective. Correspondingly, target reference points defined in terms of biomass (i.e., BMEY) are used in harvest control rules. In the absence of explicit BMEY estimates, proxy estimates based on maximum sustainable yield (i.e., BMSY) are used. Identifying BMEY in multi-species fisheries is complicated as most stock assessments are undertaken at the individual species level, but economic activity occurs across species. This is further complicated when different fishing activities using different fishing gears and targeting practices (i.e., métiers) are present in a fishery. We employ an age-structured bioeconomic model to estimate BMEY for key species in a multi-species, multi-métier fishery. We find that optimal biomass levels are substantially higher than those assumed under the current proxy-based system, and that the economic targets are sensitive to prices and fishing costs, both of which change over time.

Managing fisheries to achieve ecological, economic and social sustainability is complex. The use of dynamic bioeconomic models can be and have been used to assist in determining management targets. However, optimizing profits over time can result in large reductions in fishing effort in the short term with adverse social consequences. There exist other benefits from maintaining fishing effort even in adverse conditions (e.g., maintain crew and fleet capacity). For this reason, many bioeconomic models have included some form of minimum effort, catch or short-term profit constraint. In this paper, we consider a range of approaches to assess an appropriate minimum fishing effort, including the estimation of fishery breakeven effort levels, and approaches based on historical fishing levels. These are tested using a bioeconomic model currently used for fishery management. We find that breakeven approaches tend to result in the most conservative effort levels and the highest net present value of profits. In contrast, using a proportion of the moving average of the observed fishing effort results in less conservative change in effort, while resulting in positive changes in the net present value of fishery profits. The approach also has the advantage of being dynamic, adjusting with recent fishery conditions.

Using length frequency distribution data (LFD) is cost-effective for estimating somatic growth in fish or invertebrates as length data are relatively easy to obtain. The recently developed R packages TropFishR and fishboot extend classic ELEFAN (Electronic LEngth Frequency ANalysis) programs and include more powerful optimization procedures and a bootstrap method for estimating uncertainties. Yet, the fundamental functions require users to provide search conditions (e.g. upper and lower limits for each parameter, length-class size, number of length-classes for the calculation of moving average), which can significantly affect the results. In this paper, we compare the ELEFAN approach with a Bayesian approach in analysing LFD, employing both standard and seasonal von Bertalanffy growth functions. We apply both approaches to a commercially valuable but poorly studied red endeavour prawn (Metapenaeus ensis) harvested in Australia's Northern Prawn Fishery. Sensitivity tests on ELEFAN confirm that any change in search settings would affect the results. Simulation studies on Bayesian growth models show that L-inf and K can be accurately obtained even with modal progression of only one year-class and using non-informative priors. However, age information, including the theoretical age at length zero (t(0)), is difficult to estimate and requires LFD from multiple age classes and informative priors. The Bayesian models yield mean parameters of: L-inf = 36.56 mm (carapace length), K = 2.74 yr(-1), and t(0) = -0.02 yr for the males, and L-inf = 51.81 mm, K = 1.94 yr(-1), and t(0) = -0.02 yr for the females. Seasonal oscillation models fit the LFD better, but the improvement is small and the estimated season-related parameters have large variances.

The Northern Prawn Fishery (NPF) is one of Australia's most valuable federally managed fisheries. It has also been a focus for modelling in Australia, with over 40 years of development of bioeconomic, stock assessment and management strategy evaluation models that have been used to varying degrees to inform management. The current management model has been in operation for over 10 years and is used to set the total allowable effort (TAE) for the tiger prawn (Penaeus semisulcatus and P. esculentus) component of the fishery, historically undertaken after a mid-year closure. The success of management has resulted in increased stocks of tiger prawns, and a fishery before the mid-year closure during which fishing for banana prawns was historically the main activity. While the current management model includes the consequences of fishing for tiger prawns during the first season in terms of which weeks are available for fishing for tiger prawns when estimating the TAE, the lack of explicit inclusion of banana prawns in the bioeconomic modelling has resulted in concerns that the TAE may be biased, as effort is allocated in the model to tiger prawns that, in reality, should be applied to banana prawns. The current model was consequently extended to include an explicit banana prawn component, and a range of scenarios undertaken to explore the impact of this on the management advice. It was found that the current model overestimates the optimal level of effort to be applied to tiger prawns except during periods of very low banana prawn abundance. Banana prawns, which vary substantially inter-annually due largely to environmental drivers, were also found to be the key driver of the level of overall fishery profit, suggesting that greater attention to this component of the fishery may be necessary to achieve the objective of maximizing net economic returns from the NPF.

Individual transferable quotas (ITQs) have been implemented in many fisheries in Australia and elsewhere, primarily in response to stock management challenges. However, unanticipated economic and social outcomes are also apparent, particularly for small-scale fishers. In December 2020, the Australian Senate initiated an Inquiry into the operations of ITQ management systems in Australian fisheries. Submissions were made by individual fishers, industry organisations, fisheries managers, research groups and others, detailing their perceptions on performance in terms of environmental, social and economic outcomes. We summarise the key points raised in the submissions, identifying areas where claims and perceptions were similar or diverse for the different groups. We find that the individual fishers who made submissions were largely negative about the impacts of ITQs in terms of all three outcome domains, whereas industry organisations and others were mostly positive overall. Social issues, particularly ownership of quota by non-fishers (i.e. investors), were flagged by most groups as a problem with the current system. Addressing these concerns with ITQ systems may be difficult. Enshrinement as user rights means that small-scale fisheries and local communities may be disadvantaged in the long-term due to past trade-offs favouring economic and ecological sustainability over social impacts.

The Torres Strait tropical rock lobster Panulirus ornatus (TRL) fishery is of immense social, cultural and economic importance to the region's Indigenous fishers from both Australia and Papua New Guinea (PNG). During 2020, the COVID-19 pandemic indirectly impacted this fishery as well as a number of other fisheries reliant on international export markets. The TRL fishery is managed using an empirical (databased) Harvest Control Rule (eHCR) to rapidly provide a recommended biological catch (RBC), based on catch, fishery-independent survey indices and catch-per-unit-effort (CPUE). Here, we summarize the impacts of COVID-19 on each of these critical data inputs and discuss whether the eHCR was considered adequately resilient to this unprecedented disruption to the system. Next, we use a quantitative supply chain index to analyze the impact of disruptions to the supply chain, and inform on potential adaptation strategies. The catch and CPUE data were impacted to varying degrees by external constraints influencing fishing effort, but the fishery-independent survey wasn't affected and hence there remains an unbroken survey time-series for the fishery extending back to 1989. The eHCR was shown to be reasonably robust because it incorporates longer-term trends over a 5-year period, and accords substantially more weighting (80%) to the fishery-independent survey rather than CPUE data which can be affected by trade and other disruptions. Despite the eHCR not having been tested for scenarios such as a global pandemic, this robustness is a positive given the types of disruptions we will likely face in future climate. The weak links identified in the supply chain were the same as those previously highlighted as sensitive to climate change disruptions. Our supply chain analysis quantifies the impact on system resilience of alternative paths connecting producers to consumers and reinforces that supply chains may be particularly vulnerable to external disruptions if they are not sufficiently diverse.

Short-lived, fast-growing species that contribute greatly to global capture fisheries are sensitive to fluctuations in the environment. Uncertainties in exact stock-environment relationships have meant that environmental variability and extremes have been difficult to integrate directly into fisheries management. We applied a management strategy evaluation approach for one of Australia's large prawn stocks to test the robustness of harvest control rules to environmental variability. The model ensemble included coupled environmental-population models and an alternative catchability scenario fitted to historical catch per unit effort data. We compared the efficacy of alternative management actions to conserve marine resources under a variable environment while accounting for fisher livelihoods. Model fits to catch per unit effort were reasonably good and similar across operating models (OMs). For models that were coupled to the environment, environmental parameters for El Niño years were estimated with good associated precision, and OM3 had a lower AIC score (77.61)  than the base model (OM1, 80.39), whereas OM2 (AIC 82.41) had a similar AIC score, suggesting the OMs were all plausible model alternatives. Our model testing resulted in a plausible subset of management options, and stakeholders selected a permanent closure of the first fishing season based on overall performance of this option; ability to reduce the risk of fishery closure and stock collapse; robustness to uncertainties; and ease of implementation. Our simulation approach enabled the selection of an optimal yet pragmatic solution for addressing economic and conservation objectives under a variable environment with extreme events.

Climate-driven trends in ocean temperature and primary productivity are projected to differ greatly across the globe, triggering variable levels of concern for marine biota and ecosystems. Quantifying these changes, and the complex ways in which resource-dependent communities will need to respond, is inherently difficult. Existing uncertainty about the structure, function and responses of marine ecosystems, means that a multi-model or ensemble model approach is the most prudent means of assessing the potential ecosystem responses to climate change. In this study, climate-ecological projections of 13 marine ecosystem models for regions around Australia were evaluated. Model types included dynamic food web, spatial whole of ecosystem, intermediate complexity, species distribution, and size spectrum models and were all forced by high-resolution ocean model data. Each Australian region and fishery will face its own challenges in terms of ecosystem shifts and fisheries management responses over the next 30 years. Across regions, demersal systems appear to be more strongly affected by climate change than pelagic systems, with invertebrate species in shallow waters likely to respond first and to a larger degree. With the assistance of qualitative confidence evaluations, the multi-model approach was useful for identifying the likely state of concern for each functional group and thus adaptive management and research priorities. Largest model discrepancies were found between the regional ecosystem models that represent trophic interactions and the species distribution models, with implications for future assessments and adaption planning. Study results highlight that fisheries and their management will need to foster pro-active and flexible adaptation options to make the most of coming opportunities and to minimize risks or negative outcomes.

Recent low levels of fishing effort in the redleg banana prawn (Penaeus indicus) component of the Australian Northern Prawn Fishery have highlighted challenges in assessing the stock status of the species and deriving appropriate management responses. Usually, low levels of fishing effort are associated with low stock abundance, but economic factors also affect fishing activity. In this study, we consider the key drivers of fishing effort in the sub-fishery, and conclude that fishing effort is driven by expectations of catch based on environmental drivers, realised revenue per unit of fishing effort, and the opportunity cost of fishing in other areas. In the case of the recent low effort levels, it is the opportunity cost that has been most influential, highlighting the importance of considering economic drivers when managing fisheries.

Fisheries management is characterised by multiple objectives, some of which may be complementary, while others may require trade-offs between outcomes. Balancing these objectives is made more complex in the case of multispecies and multigear fisheries. In this paper, we develop a bioeconomic model that captures the key elements of such a fishery to test a range of potential harvest strategies to provide insights into how economic target reference points could lead to both desirable and undesirable management outcomes (e.g. discards). The model is developed as a long-run optimisation model to identify target reference points to achieve multispecies maximum economic yield, and a dynamic recursive optimisation model, which includes more realistic representation of fishers' behaviour, such as discards and trading of under-caught species quotas. The potential economic, social and ecological impacts are evaluated using data envelopment analysis (DEA). The results suggest that the use of proxy target reference points can result in short-term economic benefits at the cost of slower stock recovery and higher discarding. Limiting the number of species subject to quota controls may also prove beneficial in multispecies fisheries, while ensuring quota markets are efficient is likely to produce benefits irrespective of the harvest strategy adopted.

Understanding recruitment variability in marine fisheries has benefits for the stock management and dependent fishers’ ability to plan their income. Here, we overview past and new research on the complex recruitment dynamics of redleg banana prawns Penaeus indicus in Australia’s Joseph Bonaparte Gulf to assess themes dating back to the time of Hjort and identify new challenges. During 2015 and 2016, redleg prawn catches and catch per unit effort decreased to anomalously low levels, suggesting a substantial decrease in prawn biomass. We hypothesized that low catches could be explained by temporary drops in sea level and rainfall potentially reducing the ability of postlarvae to reach their nursery ground. We contend that very bad prawn catch years may be predicted using two variables that are possible drivers of recruitment—the January Southern Oscillation Index and the combined January to February cumulative rainfall. However, due to challenges in verifying and defining such environmental relationships for inclusion in a stock assessment, we propose development of a harvest strategy framework to support management recommendations. Our study highlights the increasing role of anthropogenic climate change in exaggerating the impacts of environmental drivers on recruitment processes and the need to also focus on multidisciplinary research.

Calibration of complex, process-based ecosystem models is a timely task with modellers challenged by many parameters, multiple outputs of interest and often a scarcity of empirical data. Incorrect calibration can lead to unrealistic ecological and socio-economic predictions with the modeller's experience and available knowledge of the modelled system largely determining the success of model calibration. Here we provide an overview of best practices when calibrating an Atlantis marine ecosystem model, a widely adopted framework that includes the parameters and processes comprised in many different ecosystem models. We highlight the importance of understanding the model structure and data sources of the modelled system. We then focus on several model outputs (biomass trajectories, age distributions, condition at age, realised diet proportions, and spatial maps) and describe diagnostic routines that can assist modellers to identify likely erroneous parameter values. We detail strategies to fine tune values of four groups of core parameters: growth, predator-prey interactions, recruitment and mortality. Additionally, we provide a pedigree routine to evaluate the uncertainty of an Atlantis ecosystem model based on data sources used. Describing best and current practices will better equip future modellers of complex, processed-based ecosystem models to provide a more reliable means of explaining and predicting the dynamics of marine ecosystems. Moreover, it promotes greater transparency between modellers and end-users, including resource managers.

Australia's oceans are undergoing rapid change and changes in fish distribution, abundance and phenology have been widely reported. A first step in ensuring that the fisheries of Australia adapt effectively to climate change is an understanding of the historical and projected changes in the species captured. This information will underpin development of industry and management responses and management systems that will allow negative impacts to be mitigated and opportunities that arise to be seized. This project takes two approaches to understanding climate impacts on species that are captured in Australian fisheries - species sensitivity analysis (Part 1) and ecosystem modelling based on new climate projections (Part 2). Species level responses for each of the Commonwealth fisheries are detailed in both sections, followed by a concluding synthesis and list of recommendations (Part 3).