Integrating science through Bayesian Belief Networks : case study of Lyngbya in Moreton Bay

Bayesian Belief Networks (BBNs) are emerging as valuable tools for investigating complex ecological problems. In a BBN, the important variables in a problem are identified and causal relationships are represented graphically. Underpinning this is the probabilistic framework in which variables can take on a finite range of mutually exclusive states. Associated with each variable is a conditional probability table (CPT), showing the probability of a variable attaining each of its possible states conditioned on all possible combinations of it parents. Whilst the variables (nodes) are connected, the CPT attached to each node can be quantified independently. This allows each variable to be populated with the best data available, including expert opinion, simulation results or observed data. It also allows the information to be easily updated as better data become available ----- ----- This paper reports on the process of developing a BBN to better understand the initial rapid growth phase (initiation) of a marine cyanobacterium, Lyngbya majuscula, in Moreton Bay, Queensland. Anecdotal evidence suggests that Lyngbya blooms in this region have increased in severity and extent over the past decade. Lyngbya has been associated with acute dermatitis and a range of other health problems in humans. Blooms have been linked to ecosystem degradation and have also damaged commercial and recreational fisheries. However, the causes of blooms are as yet poorly understood.

Effects of phosphorus on the growth and nitrogen fixation rates of Lyngbya majuscula: implications for management in Moreton Bay, Queensland

Significant acetylene reduction and therefore N-2 fixation was observed for Lyngbya majuscula only during dark periods, which suggests that oxygenic photosynthesis and N-2 fixation are incompatible processes for this species. Results from a series of batch and continuous-flow-culture reactor studies showed that the specific growth rate and N-2 fixation rate of L, majuscula increased with phosphate (P-PO4) concentration up to a maximum value and thereafter remained constant. The P-PO4 concentrations corresponding to the maximum N-2 fixation and maximum growth rates were -0.27 and -0.18 muM respectively and these values are denoted as the saturation values for N-2 fixation and growth respectively. Regular monitoring studies in Moreton Bay, Queensland, show that concentrations Of P-PO4 generally exceed these saturation values over a large portion of the Bay and therefore, the growth of the bloom-forming L, majuscula is potentially maximised throughout much of the Bay by the elevated P-PO4 concentrations. Results from other studies suggest that the elevated P-PO4 concentrations in the Bay can be largely attributed to discharges from waste-water treatment plants (WWTPs), and thus it is proposed that the control of the growth of L. majuscula in Moreton Bay will require a significant reduction in the P load from the WWTP discharges. If the current strategy of N load reduction for these discharges is maintained in the absence of substantial P load reduction, it is hypothesised that the growth of L, majuscula and other diazotrophs in Moreton Bay will increase in the future.

Ecophysiology of the marine cyanobacterium, Lyngbya majuscula (Oscillatoriaceae) in Moreton Bay, Australia

Large blooms of the marine cyanobacterium Lyngbya majuscula in Moreton Bay, Australia (27 degrees 05'S, 153 degrees 08'E) have been re-occurring for several years. A bloom was studied in Deception Bay (Northern Moreton Bay) in detail over the period January-March 2000. In situ data loggers and field sampling characterised various environmental parameters before and during the L. majuscula bloom. Various ecophysiological experiments were conducted on L. majuscula collected in the field and transported to the laboratory, including short-term (2h) C-14 incorporation rates and long-term (7 days) pulse amplitude modulated (PAM) fluorometry assessments of photosynthetic capacity. The effects of L. majuscula on various seagrasses in the bloom region were also assessed with repeated biomass sampling. The bloom commenced in January 2000 following usual December rainfall events, water temperatures in excess of 24 degrees C and high light conditions. This bloom expanded rapidly from 0 to a maximum extent of 8 km(2) over 55 days with an average biomass of 210 g(dw)(-1) m(-2) in late February, followed by a rapid decline in early April. Seagrass biomass, especially Syringodium isoetifolium, was found to decline in areas of dense L. majuscula accumulation. Dissolved and total nutrient concentrations did not differ significantly (P > 0.05) preceding or during the bloom. However, water samples from creeks discharging into the study region indicated elevated concentrations of total iron (2.7-80.6 mu M) and dissolved organic carbon (2.5-24.7 mg L-1), associated with low pH values (3.8-6.7). C-14 incorporation rates by L. majuscula were significantly (P < 0.05) elevated by additions of iron (5 mu M Fe), an organic chelator, ethylenediaminetetra-acetic acid (5 mu M EDTA) and phosphorus (5 mu M PO4-3). Photosynthetic capacity measured with PAM fluorometry was also stimulated by various nutrient additions, but not significantly (P > 0.05). These results suggest that the L. majuscula bloom may have been stimulated by bioavailable iron, perhaps complexed by dissolved organic carbon. The rapid bloom expansion observed may then have been sustained by additional inputs of nutrients (N and P) and iron through sediment efflux, stimulated by redox changes due to decomposing L. majuscula mats. (c) 2004 Elsevier B.V. All rights reserved.

A bloom of Lyngbya majuscula in Shoalwater Bay, Queensland, Australia: An important feeding ground for the green turtle (Chelonia mydas)

Lyngbya majuscula, a toxic cyanobacterium, was observed blooming during June-July (winter) 2002 in Shoalwater Bay, Queensland, Australia, an important feeding area for a large population of green turtles (Chelonia mydas). The bloom was mapped and extensive mats of L majuscula were observed overgrowing seagrass beds along at least 18 km of coast, and covering a surface area of more than I I km(2). Higher than average rainfall preceded the bloom and high water temperatures in the preceding summer may have contributed to the bloom. In bloom samples, lyngbyatoxin A (LA) was found to be present in low concentration (26 mu g kg(-1) (dry weight)), but debromoaplysiatoxin (DAT) was not detected. The diet of 46 green turtles was assessed during the bloom and L. majuscula was found in 51% of the samples, however, overall it contributed only 2% of the animals' diets. L. majuscula contribution to turtle diet was found to increase as the availability of the cyanobacterium increased. The bloom appeared to have no immediate impact on turtle body condition, however, the presence of a greater proportion of damaged seagrass leaves in diet in conjunction with decreases in plasma concentrations of sodium and glucose could suggest that the turtles may have been exposed to a Substandard diet as a result of the bloom. This is the first confirmed report of L. majuscula blooming in winter in Shoalwater Bay, Queensland, Australia and demonstrates that turtles consume the toxic cyanobacterium in the wild, and that they are potentially exposed to tumour promoting compounds produced by this organism. (c) 2005 Elsevier B.V. All rights reserved.

Effects of Lyngbya majuscula (Cyanophycea) blooms on sediment nutrients and meiofaunal assemblages in seagrass beds in Moreton Bay, Australia

Blooms of Lyngbya majuscula have been increasingly recorded in the waters of Moreton Bay, on the south-east coast of Queensland, Australia. The influences of these blooms on sediment infauna and the implications for sediment biogeochemical processes was studied. Sediment samples were taken from Moreton Bay banks during and after the bloom season. The deposition of L. majuscula seems to be responsible for the higher total Kjedahl nitrogen (TKN) concentrations measured during the bloom period. Total organic carbon (TOC) concentrations did not change. Lyngbya majuscula blooms had a marked influence on the meiobenthos. Nematodes, copepods and polychaetes were the most abundant groups of meiofauna, and the bloom produced a decrease in the abundance and a change in the sediment depth distribution of these organisms. The distribution of nematodes, copepods and polychaetes in sediment became shallower. Further, the bloom did not affect the abundance and distribution of polychaetes as strongly as it did copepods and nematodes. The changes observed in the distribution of meiofauna in the sediment during the bloom period indicate that L. majuscula produces oxygen depletion in sediments, and that different fauna seem to be affected to different degrees.

Feeding preference and deterrence in rabbitfish Siganus fuscescens for the cyanobacterium Lyngbya majuscula in Moreton Bay, south-east Queensland, Australia

Rabbitfish Siganus fuscescens preferences for Lyngbya majuscula collected from three bloom locations in Moreton Bay, Queensland, Australia, were tested along with a range of local plant species in the laboratory. Consumption of L. majuscula by fish did not differ between wild and captive-bred fish (P = 0.152) but did differ between bloom location (P = 0.039). No relationship was found between consumption rates and lyngbyatoxin-a concentration (r(2) = 0.035, P = 0.814). No correlation existed between C : N and proportion of food consumed when all food types were analysed statistically, whereas a clear correlation was observed when L. majuscula was removed from the calculations. In simulated bloom conditions, fish avoided ingestion of L. majuscula by feeding through gaps in the L. majuscula coverage. Both wild and captive-bred S. fuscescens showed a distinct feeding pattern in 10 day no-choice feeding assays, with less L. majuscula being consumed than the preferred red alga Acanthophora spicifera. Lyngbya majuscula however, was consumed in equal quantities to A. spicifera by wild S. fuscescens when lyngbyatoxin-a was not detectable. Wild fish probably do not preferentially feed on L. majuscula when secondary metabolites are present and are not severely impacted by large L. majuscula blooms in Moreton Bay. Furthermore, poor feeding performance in both captive-bred and wild S. fuscescens suggests that they would exert little pressure as a top-down control agent of toxic L. majuscula blooms within Moreton Bay. (c) 2006 The Fisheries Society of the British Isles.

A Bayesian network approach to modelling temporal behaviour of Lyngbya majuscula bloom initiation

Lyngbya majuscula is a cyanobacterium (blue-green algae) occurring naturally in tropical and subtropical coastal areas worldwide. Deception Bay, in Northern Moreton Bay, Queensland, has a history of Lyngbya blooms, and forms a case study for this investigation. The South East Queensland (SEQ) Healthy Waterways Partnership, collaboration between government, industry, research and the community, was formed to address issues affecting the health of the river catchments and waterways of South East Queensland. The Partnership coordinated the Lyngbya Research and Management Program (2005-2007) which culminated in a Coastal Algal Blooms (CAB) Action Plan for harmful and nuisance algal blooms, such as Lyngbya majuscula. This first phase of the project was predominantly of a scientific nature and also facilitated the collection of additional data to better understand Lyngbya blooms. The second phase of this project, SEQ Healthy Waterways Strategy 2007-2012, is now underway to implement the CAB Action Plan and as such is more management focussed. As part of the first phase of the project, a Science model for the initiation of a Lyngbya bloom was built using Bayesian Networks (BN). The structure of the Science Bayesian Network was built by the Lyngbya Science Working Group (LSWG) which was drawn from diverse disciplines. The BN was then quantified with annual data and expert knowledge. Scenario testing confirmed the expected temporal nature of bloom initiation and it was recommended that the next version of the BN be extended to take this into account. Elicitation for this BN thus occurred at three levels: design, quantification and verification. The first level involved construction of the conceptual model itself, definition of the nodes within the model and identification of sources of information to quantify the nodes. The second level included elicitation of expert opinion and representation of this information in a form suitable for inclusion in the BN. The third and final level concerned the specification of scenarios used to verify the model. The second phase of the project provides the opportunity to update the network with the newly collected detailed data obtained during the previous phase of the project. Specifically the temporal nature of Lyngbya blooms is of interest. Management efforts need to be directed to the most vulnerable periods to bloom initiation in the Bay. To model the temporal aspects of Lyngbya we are using Object Oriented Bayesian networks (OOBN) to create ‘time slices’ for each of the periods of interest during the summer. OOBNs provide a framework to simplify knowledge representation and facilitate reuse of nodes and network fragments. An OOBN is more hierarchical than a traditional BN with any sub-network able to contain other sub-networks. Connectivity between OOBNs is an important feature and allows information flow between the time slices. This study demonstrates more sophisticated use of expert information within Bayesian networks, which combine expert knowledge with data (categorized using expert-defined thresholds) within an expert-defined model structure. Based on the results from the verification process the experts are able to target areas requiring greater precision and those exhibiting temporal behaviour. The time slices incorporate the data for that time period for each of the temporal nodes (instead of using the annual data from the previous static Science BN) and include lag effects to allow the effect from one time slice to flow to the next time slice. We demonstrate a concurrent steady increase in the probability of initiation of a Lyngbya bloom and conclude that the inclusion of temporal aspects in the BN model is consistent with the perceptions of Lyngbya behaviour held by the stakeholders. This extended model provides a more accurate representation of the increased risk of algal blooms in the summer months and show that the opinions elicited to inform a static BN can be readily extended to a dynamic OOBN, providing more comprehensive information for decision makers.

Blooms of the cyanobacterium Lyngbya majuscula in coastal Queensland, Australia: disparate sites, common factors

During the last decade there has been a significant rise in observations of blooms of the toxic cyanobacterium, Lyngbya majuscula along the east coast of Queensland, Australia. Whether the increase in cyanobacterial abundance is a biological indicator of widespread water quality degradation or also a function of other environmental change is unknown. A bioassay approach was used to assesses the potential for runoff from various land uses to stimulate productivity of L. majuscula. In Moreton Bay, L. majuscula productivity was significantly (p < 0.05) stimulated by soil extracts, which were high in phosphorus, iron and organic carbon. Productivity of L. majuscula from the Great Barrier Reef was also significantly (p < 0.05) elevated by iron and phosphorus rich extracts, in this case seabird guano adjacent to the bloom site. Hence, it is possible that other L. majuscula blooms are a result of similar stimulating factors (iron, phosphorus and organic carbon), delivered through different mechanisms. (c) 2004 Elsevier Ltd. All rights reserved.

Harvest strategy evaluations and co-management for the Moreton Bay Trawl Fishery

Non-Technical Summary Seafood CRC Project 2009/774. Harvest strategy evaluations and co-management for the Moreton Bay Trawl Fishery Principal Investigator: Dr Tony Courtney, Principal Fisheries Biologist Fisheries and Aquaculture, Agri-Science Queensland Department of Agriculture, Fisheries and Forestry Level B1, Ecosciences Precinct, Joe Baker St, Dutton Park, Queensland 4102 Email: tony.courtney@daff.qld.gov.au Project objectives: 1. Review the literature and data (i.e., economic, biological and logbook) relevant to the Moreton Bay trawl fishery. 2. Identify and prioritise management objectives for the Moreton Bay trawl fishery, as identified by the trawl fishers. 3. Undertake an economic analysis of Moreton Bay trawl fishery. 4. Quantify long-term changes to fishing power for the Moreton Bay trawl fishery. 5. Assess priority harvest strategies identified in 2 (above). Present results to, and discuss results with, Moreton Bay Seafood Industry Association (MBSIA), fishers and Fisheries Queensland. Note: Additional, specific objectives for 2 (above) were developed by fishers and the MBSIA after commencement of the project. These are presented in detail in section 5 (below). The project was an initiative of the MBSIA, primarily in response to falling profitability in the Moreton Bay prawn trawl fishery. The analyses were undertaken by a consortium of DAFF, CSIRO and University of Queensland researchers. This report adopted the Australian Standard Fish Names (http://www.fishnames.com.au/). Trends in catch and effort The Moreton Bay otter trawl fishery is a multispecies fishery, with the majority of the catch composed of Greasyback Prawns (Metapenaeus bennettae), Brown Tiger Prawns (Penaeus esculentus), Eastern King Prawns (Melicertus plebejus), squid (Uroteuthis spp., Sepioteuthis spp.), Banana Prawns (Fenneropenaeus merguiensis), Endeavour Prawns (Metapenaeus ensis, Metapenaeus endeavouri) and Moreton Bay bugs (Thenus parindicus). Other commercially important byproduct includes blue swimmer crabs (Portunus armatus), three-spot crabs (Portunus sanguinolentus), cuttlefish (Sepia spp.) and mantis shrimp (Oratosquilla spp.). Logbook catch and effort data show that total annual reported catch of prawns from the Moreton Bay otter trawl fishery has declined to 315 t in 2008 from a maximum of 901 t in 1990. The number of active licensed vessels participating in the fishery has also declined from 207 in 1991 to 57 in 2010. Similarly, fishing effort has fallen from a peak of 13,312 boat-days in 1999 to 3817 boat-days in 2008 – a 71% reduction. The declines in catch and effort are largely attributed to reduced profitability in the fishery due to increased operational costs and depressed prawn prices. The low prawn prices appear to be attributed to Australian aquacultured prawns and imported aquacultured vannamei prawns, displacing the markets for trawl-caught prawns, especially small species such as Greasyback Prawns which traditionally dominated landings in Moreton Bay. In recent years, the relatively high Australian dollar has resulted in reduced exports of Australian wild-caught prawns. This has increased supply on the domestic market which has also suppressed price increases. Since 2002, Brown Tiger Prawns have dominated annual reported landings in the Moreton Bay fishery. While total catch and effort in the bay have declined to historically low levels, the annual catch and catch rates of Brown Tiger Prawns have been at record highs in recent years. This appears to be at least partially attributed to the tiger prawn stock having recovered from excessive effort in previous decades. The total annual value of the Moreton Bay trawl fishery catch, including byproduct, is about $5 million, of which Brown Tiger Prawns account for about $2 million. Eastern King Prawns make up about 10% of the catch and are mainly caught in the bay from October to December as they migrate to offshore waters outside the bay where they contribute to a large mono-specific trawl fishery. Some of the Eastern King Prawns harvested in Moreton Bay may be growth overfished (i.e., caught below the size required to maximise yield or value), although the optimum size-at-capture was not determined in this study. Banana Prawns typically make up about 5% of the catch, but can exceed 20%, particularly following heavy rainfall. Economic analysis of the fishery From the economic survey, cash profits were, on average, positive for both fleet segments in both years of the survey. However, after the opportunity cost of capital and depreciation were taken into account, the residual owner-operator income was relatively low, and substantially lower than the average share of revenue paid to employed skippers. Consequently, owner-operators were earning less than their opportunity cost of their labour, suggesting that the fleets were economically unviable in the longer term. The M2 licensed fleet were, on average, earning similar boat cash profits as the T1/M1 fleet, although after the higher capital costs were accounted for the T1/M1 boats were earning substantially lower returns to owner-operator labour. The mean technical efficiency for the fleet as a whole was estimated to be 0.67. That is, on average, the boats were only catching 67 per cent of what was possible given their level of inputs (hours fished and hull units). Almost one-quarter of observations had efficiency scores above 0.8, suggesting a substantial proportion of the fleet are relatively efficient, but some are also relatively inefficient. Both fleets had similar efficiency distributions, with median technical efficiency score of 0.71 and 0.67 for the M2 and T1/M1 boats respectively. These scores are reasonably consistent with other studies of prawn trawl fleets in Australia, although higher average efficiency scores were found in the NSW prawn trawl fleet. From the inefficiency model, several factors were found to significantly influence vessel efficiency. These included the number of years of experience as skipper, the number of generations that the skipper’s family had been fishing and the number of years schooling. Skippers with more schooling were significantly more efficient than skippers with lower levels of schooling, consistent with other studies. Skippers who had been fishing longer were, in fact, less efficient than newer skippers. However, this was mitigated in the case of skippers whose family had been involved in fishing for several generations, consistent with other studies and suggesting that skill was passed through by families over successive generations. Both the linear and log-linear regression models of total fishing effort against the marginal profit per hour performed reasonably well, explaining between 70 and 84 per cent of the variation in fishing effort. As the models had different dependent variables (one logged and the other not logged) this is not a good basis for model choice. A better comparator is the square root of the mean square error (SMSE) expressed as a percentage of the mean total effort. On this criterion, both models performed very similarly. The linear model suggests that each additional dollar of average profits per hour in the fishery increases total effort by around 26 hours each month. From the log linear model, each percentage increase in profits per hour increases total fishing effort by 0.13 per cent. Both models indicate that economic performance is a key driver of fishing effort in the fishery. The effect of removing the boat-replacement policy is to increase individual vessel profitability, catch and effort, but the overall increase in catch is less than that removed by the boats that must exit the fishery. That is, the smaller fleet (in terms of boat numbers) is more profitable but the overall catch is not expected to be greater than before. This assumes, however, that active boats are removed, and that these were also taking an average level of catch. If inactive boats are removed, then catch of the remaining group as a whole could increase by between 14 and 17 per cent depending on the degree to which costs are reduced with the new boats. This is still substantially lower than historical levels of catch by the fleet. Fishing power analyses An analysis of logbook data from 1988 to 2010, and survey information on fishing gear, was performed to estimate the long-term variation in the fleet’s ability to catch prawns (known as fishing power) and to derive abundance estimates of the three most commercially important prawn species (i.e., Brown Tiger, Eastern King and Greasyback Prawns). Generalised linear models were used to explain the variation in catch as a function of effort (i.e., hours fished per day), vessel and gear characteristics, onboard technologies, population abundance and environmental factors. This analysis estimated that fishing power associated with Brown Tiger and Eastern King Prawns increased over the past 20 years by 10–30% and declined by approximately 10% for greasybacks. The density of tiger prawns was estimated to have almost tripled from around 0.5 kg per hectare in 1988 to 1.5 kg/ha in 2010. The density of Eastern King Prawns was estimated to have fluctuated between 1 and 2 kg per hectare over this time period, without any noticeable overall trend, while Greasyback Prawn densities were estimated to have fluctuated between 2 and 6 kg per hectare, also without any distinctive trend. A model of tiger prawn catches was developed to evaluate the impact of fishing on prawn survival rates in Moreton Bay. The model was fitted to logbook data using the maximum-likelihood method to provide estimates of the natural mortality rate (0.038 and 0.062 per week) and catchability (which can be defined as the proportion of the fished population that is removed by one unit of effort, in this case, estimated to be 2.5 ± 0.4 E-04 per boat-day). This approach provided a method for industry and scientists to develop together a realistic model of the dynamics of the fishery. Several aspects need to be developed further to make this model acceptable to industry. Firstly, there is considerable evidence to suggest that temperature influences prawn catchability. This ecological effect should be incorporated before developing meaningful harvest strategies. Secondly, total effort has to be allocated between each species. Such allocation of effort could be included in the model by estimating several catchability coefficients. Nevertheless, the work presented in this report is a stepping stone towards estimating essential fishery parameters and developing representative mathematical models required to evaluate harvest strategies. Developing a method that allowed an effective discussion between industry, management and scientists took longer than anticipated. As a result, harvest strategy evaluations were preliminary and only included the most valuable species in the fishery, Brown Tiger Prawns. Additional analyses and data collection, including information on catch composition from field sampling, migration rates and recruitment, would improve the modelling. Harvest strategy evaluations As the harvest strategy evaluations are preliminary, the following results should not be adopted for management purposes until more thorough evaluations are performed. The effects, of closing the fishery for one calendar month, on the annual catch and value of Brown Tiger Prawns were investigated. Each of the 12 months (i.e., January to December) was evaluated. The results were compared against historical records to determine the magnitude of gain or loss associated with the closure. Uncertainty regarding the trawl selectivity was addressed using two selectivity curves, one with a weight at 50% selection (S50%) of 7 g, based on research data, and a second with S50% of 14 g, put forward by industry. In both cases, it was concluded that any monthly closure after February would not be beneficial to the industry. The magnitude of the benefit of closing the fishery in either January or February was sensitive to which mesh selectivity curve that was assumed, with greater benefit achieved when the smaller selectivity curve (i.e., S50% = 7 g) was assumed. Using the smaller selectivity (S50% = 7 g), the expected increase in catch value was 10–20% which equates to $200,000 to $400,000 annually, while the larger selectivity curve (S50% = 14 g) suggested catch value would be improved by 5–10%, or $100,000 to $200,000. The harvest strategy evaluations showed that greater benefits, in the order of 30–60% increases in the tiger annual catch value, could have been obtained by closing the fishery early in the year when annual effort levels were high (i.e., > 10,000 boat-days). In recent years, as effort levels have declined (i.e., ~4000 boat-days annually), expected benefits from such closures are more modest. In essence, temporal closures offer greater benefit when fishing mortality rates are high. A spatial analysis of Brown Tiger Prawn catch and effort was also undertaken to obtain a better understanding of the prawn population dynamics. This indicated that, to improve profitability of the fishery, fishers could consider closing the fishery in the period from June to October, which is already a period of low profitability. This would protect the Brown Tiger Prawn spawning stock, increase catch rates of all species in the lucrative pre-Christmas period (November–December), and provide fishers with time to do vessel maintenance, arrange markets for the next season’s harvest, and, if they wish, work at other jobs. The analysis found that the instantaneous rate of total mortality (Z) for the March–June period did not vary significantly over the last two decades. As the Brown Tiger Prawn population in Moreton Bay has clearly increased over this time period, an interesting conclusion is that the instantaneous rate of natural mortality (M) must have increased, suggesting that tiger prawn natural mortality may be density-dependent at this time of year. Mortality rates of tiger prawns for June–October were found to have decreased over the last two decades, which has probably had a positive effect on spawning stocks in the October–November spawning period. Abiotic effects on the prawns The influence of air temperature, rainfall, freshwater flow, the southern oscillation index (SOI) and lunar phase on the catch rates of the four main prawn species were investigated. The analyses were based on over 200,000 daily logbook catch records over 23 years (i.e., 1988–2010). Freshwater flow was more influential than rainfall and SOI, and of the various sources of flow, the Brisbane River has the greatest volume and influence on Moreton Bay prawn catches. A number of time-lags were also considered. Flow in the preceding month prior to catch (i.e., 30 days prior, Logflow1_30) and two months prior (31–60 days prior, Logflow31_60) had strong positive effects on Banana Prawn catch rates. Average air temperature in the preceding 4-6 months (Temp121_180) also had a large positive effect on Banana Prawn catch rates. Flow in the month immediately preceding catch (Logflow1_30) had a strong positive influence on Greasyback Prawn catch rates. Air temperature in the preceding two months prior to catch (Temp1_60) had a large positive effect on Brown Tiger Prawn catch rates. No obvious or marked effects were detected for Eastern King Prawns, although interestingly, catch rates declined with increasing air temperature 4–6 months prior to catch. As most Eastern King Prawn catches in Moreton Bay occur in October to December, the results suggest catch rates decline with increasing winter temperatures. In most cases, the prawn catch rates declined with the waxing lunar phase (high luminance/full moon), and increased with the waning moon (low luminance/new moon). The SOI explains little additional variation in prawn catch rates (~ <2%), although its influence was higher for Banana Prawns. Extrapolating findings of the analyses to long-term climate change effects should be interpreted with caution. That said, the results are consistent with likely increases in abundance in the region for the two tropical species, Banana Prawns and Brown Tiger Prawns, as coastal temperatures rise. Conversely, declines in abundance could be expected for the two temperate species, Greasyback and Eastern King Prawns. Corporate management structures An examination of alternative governance systems was requested by the industry at one of the early meetings, particularly systems that may give them greater autonomy in decision making as well as help improve the marketing of their product. Consequently, a review of alternative management systems was undertaken, with a particular focus on the potential for self-management of small fisheries (small in terms of number of participants) and corporate management. The review looks at systems that have been implemented or proposed for other small fisheries internationally, with a particular focus on self-management as well as the potential benefits and challenges for corporate management. This review also highlighted particular opportunities for the Moreton Bay prawn fishery. Corporate management differs from other co-management and even self-management arrangements in that ‘ownership’ of the fishery is devolved to a company in which fishers and government are shareholders. The company manages the fishery as well as coordinates marketing to ensure that the best prices are received and that the catch taken meets the demands of the market. Coordinated harvesting will also result in increased profits, which are returned to fishers in the form of dividends. Corporate management offers many of the potential benefits of an individual quota system without formally implementing such a system. A corporate management model offers an advantage over a self-management model in that it can coordinate both marketing and management to take advantage of this unique geographical advantage. For such a system to be successful, the fishery needs to be relatively small and self- contained. Small in this sense is in terms of number of operators. The Moreton Bay prawn fishery satisfies these key conditions for a successful self-management and potentially corporate management system. The fishery is small both in terms of number of participants and geography. Unlike other fisheries that have progressed down the self-management route, the key market for the product from the Moreton Bay fishery is right at its doorstep. Corporate management also presents a number of challenges. First, it will require changes in the way fishers operate. In particular, the decision on when to fish and what to catch will be taken away from the individual and decided by the collective. Problems will develop if individuals do not join the corporation but continue to fish and market their own product separately. While this may seem an attractive option to fishers who believe they can do better independently, this is likely to be just a short- term advantage with an overall long-run cost to themselves as well as the rest of the industry. There are also a number of other areas that need further consideration, particularly in relation to the allocation of shares, including who should be allocated shares (e.g. just boat owners or also some employed skippers). Similarly, how harvesting activity is to be allocated by the corporation to the fishers. These are largely issues that cannot be answered without substantial consultation with those likely to be affected, and these groups cannot give these issues serious consideration until the point at which they are likely to become a reality. Given the current structure and complexity of the fishery, it is unlikely that such a management structure will be feasible in the short term. However, the fishery is a prime candidate for such a model, and development of such a management structure in the future should be considered as an option for the longer term.