Develop A Strong Current Warning System And Inform Knowledge Of The Nearshore Current Regime Influencing The Western Rock Lobster Fishery
Funder
Fisheries Research and Development Corporation
Funding Amount
$199,000.00
Summary
By combining this greater coverage with information derived from commercial fishers (e.g. days when gear is drowned or lost to determine key current velocities) a purpose built webapp can be developed, hosted on an existing service, which allows fishers to asses the risks posed by ocean currents to their fishing operation before they set their gear. This would also allow for fishers to predict days when drowned gear may resurface and therefore the fishing operation may continue.
In addi ....By combining this greater coverage with information derived from commercial fishers (e.g. days when gear is drowned or lost to determine key current velocities) a purpose built webapp can be developed, hosted on an existing service, which allows fishers to asses the risks posed by ocean currents to their fishing operation before they set their gear. This would also allow for fishers to predict days when drowned gear may resurface and therefore the fishing operation may continue.
In addition to this helping the fishing operation, greater current modelling coverage over this part of the fishery will allow for the fine-scale assessment of the links between water movement and puerulus settlement. As part of FRDC project “2016-260 WRL IPA: assess causes and implications of anomalous low lobster catch rates in the shallow water areas near the centre of the Western Rock Lobster fishery” 40 additional puerulus collectors will be added to the current DOF monitoring program which will provide extensive coverage of settlement rates between Seven Mile, Dongara and Jurien Bay.
Objectives: 1. Establish additional coastal radar station 2. Establish a predictive warning system for ocean conditions that can be used by the WRL fishery to improve efficiency 3. Assess the relationship between water circulation and puerulus settlement rates Read moreRead less
The Detection Of Ciguatera Toxins In NSW Spanish Mackerel
Funder
Fisheries Research and Development Corporation
Funding Amount
$490,000.00
Summary
Ciguatera Fish Poisoning (CFP) causes the largest number of seafood-related food safety incidents in Australia. In NSW and southern QLD waters, CFP is mostly related to Spanish Mackerel (Scomberomorus commerson). Ciguatoxins (CTXs) produced by marine microalgae (Gambierdiscus spp), are polyether toxins that accumulate in fish and cause CFP when fish are eaten. CTXs are heat stable, odourless, tasteless, and toxic at low concentrations, therefore it is very difficult to distinguish toxic fish. In ....Ciguatera Fish Poisoning (CFP) causes the largest number of seafood-related food safety incidents in Australia. In NSW and southern QLD waters, CFP is mostly related to Spanish Mackerel (Scomberomorus commerson). Ciguatoxins (CTXs) produced by marine microalgae (Gambierdiscus spp), are polyether toxins that accumulate in fish and cause CFP when fish are eaten. CTXs are heat stable, odourless, tasteless, and toxic at low concentrations, therefore it is very difficult to distinguish toxic fish. In NSW, since 2014, 31 people have contracted CFP after consuming Spanish Mackerel caught locally, mostly through recreational fishing.
Validated commercial monitoring methods for CTXs are unavailable internationally, although research tools for CTX measurement have been developed. Regulatory methods for CFP prevention are to avoid certain fish species, fish of certain sizes (ie >10kg), or fish from certain regions. In Australia, effective prevention methods have not been clearly evaluated. This results in Spanish Mackerel that are safe to eat potentially being excluded from sale, resulting in significant losses (ie > ~$200k p.a in NSW). This project addresses this issue, which was identified as high priority in the Australian ciguatera research strategy formulated at a recent workshop (27-28th March, 2019).
In 2014, FRDC (Tactical Response) and the NSW Recreational Fisheries Trust funded an initial study on the incidence of CTXs in NSW Spanish Mackerel. CTX was present in flesh and liver samples (1-7% incidence), and was not clearly correlated with the weight of individual fish. This information showed that CFP risk management may require reassessment. This project will advance knowledge by: evaluating methods of detection of CTXs; determining detailed predictive data on CTX incidence; and evaluating environmental and biological factors associated with CTX in Spanish Mackerel to allow for an evaluation of risk assessment strategies. This information will benefit industry by enhancing consumer safety and industry confidence, and enabling the sale of safe Spanish Mackerel.
Objectives: 1. Determine industry CTX needs and conduct of review of available CTX measurement tools (including cell based assays, ELISA kits, and LCMS) against these needs. Conduct an assessment of the currently available screening tools to determine which, if any, hold promise for industry use. Conduct a viability assessment for how a tool might be used in industry or, if none of the currently available tools are appropriate, make recommendations for future activities to develop a rapid screening tool that meets industry needs. 2. Obtain samples of flesh and liver from ~300 individual Spanish Mackerel of all sizes caught in Industry relevant regions of NSW waters over a period of 2 years, as well as length, weight, sex and site information, with the participation of the Sydney Fish Market and commercial fishing Cooperatives. Obtain samples from any individual Spanish Mackerel associated with illnesses in NSW or QLD. Measure CTX1B and other available CTX analogs using best practice methods identified in Objective 1. 3. Conduct statistical data analyses of all available data on CTX concentrations in Spanish Mackerel in comparison to biological and environmental variables.Develop recommended options for food safety risk management for Spanish Mackerel in NSW that will allow for a viable industry while protecting public health. Read moreRead less
To update assessment reports on Whichfish.com to keep the site current for users. Objectives: 1. 1. Re-organise existing report format in line with the new methodology 2. 2. Update relevant information for the 20 species on Whichfish 3. 3. Reassess risk scores and future outlook sections using draft methodology 4. 4. Provide written feedback about any issues and/or challenges encountered in applying the draft risk assessment which will be incorporated into a guid ....To update assessment reports on Whichfish.com to keep the site current for users. Objectives: 1. 1. Re-organise existing report format in line with the new methodology 2. 2. Update relevant information for the 20 species on Whichfish 3. 3. Reassess risk scores and future outlook sections using draft methodology 4. 4. Provide written feedback about any issues and/or challenges encountered in applying the draft risk assessment which will be incorporated into a guidance document for future assessors and suggestions to improve risk assessment criteria. Read moreRead less
Investigating Aetiology And Risk Factors Of Ocular Lesions And Associated Mortality In Ranched Southern Bluefin Tuna
Funder
Fisheries Research and Development Corporation
Funding Amount
$200,238.00
Summary
This year (2017), some of the ranching operations reported the increased cumulative mortality. In some severe cases, up to 90% of collected mortalities present some degree of unilateral or bilateral ocular damage ranging from corneal cloudiness, with or without ulcers, up to complete perforation. The anecdotal report of eye lesions has progressively increased since the 2015 season without a definitive cause being identified. Previous reports (Rough et al., 1999; Rough, 2000; Hayward et al., 2007 ....This year (2017), some of the ranching operations reported the increased cumulative mortality. In some severe cases, up to 90% of collected mortalities present some degree of unilateral or bilateral ocular damage ranging from corneal cloudiness, with or without ulcers, up to complete perforation. The anecdotal report of eye lesions has progressively increased since the 2015 season without a definitive cause being identified. Previous reports (Rough et al., 1999; Rough, 2000; Hayward et al., 2007; Hayward et al., 2008a; Hayward et al., 2008b; Hayward et al., 2009; Hayward et al., 2010; Hayward et al., 2011, including FRDC projects No 2003/225 and 2008/228, Nowak et al., 2007; Nowak et al., 2012) identified sea lice of the genus Caligus spp. as a differential cause of eye lesions in SBT. The copepod ectoparasite is thought to damage the eyes by feeding on the cornea epithelium of infested SBT. Lesions worsen when fish flash against the cage’s net to dislodge the itchy copepods. Partial or full vision loss is suspected to impair the capacity of the fish to compete for feed and to result, with time, in the death of affected fish. At this stage, it is unclear: 1 - what is the distribution of the observed increased mortality across the industry; 2 - what is the occurrence and severity of eye lesions across the industry; 3 - if the observed increased mortality is entirely attributable to eye lesions; 4 - if eye lesions are solely caused by C. chiastos or if other causes are involved; 5 - if potential tow-, cage-, and fish-level risk factors are associated with the occurrence of eye lesions and its cause(s). Objectives: 1. Estimate the frequency and distribution of increased mortality across the industry. 2. Describe the pathology and severity of eye lesions and estimate the frequency and distribution of these lesions across the industry. 3. Investigate potential tow-, farm-, and fish-level risk factors associated with increased mortality and eye lesion occurrence. 4. Investigate the putative role of sealice in causing this episode of eye lesions. Read moreRead less
Learning to Pinpoint Emerging Software Vulnerabilities. This project aims to develop learning-based software vulnerability detection techniques to improve the reliability and security of modern software systems. The existing techniques relying on conventional yet rigid software analysis and testing techniques are ineffective and/or inefficient when detecting a wide variety of emerging software vulnerabilities. The outcomes of this project will be a deep-learning-based detection approach and an ....Learning to Pinpoint Emerging Software Vulnerabilities. This project aims to develop learning-based software vulnerability detection techniques to improve the reliability and security of modern software systems. The existing techniques relying on conventional yet rigid software analysis and testing techniques are ineffective and/or inefficient when detecting a wide variety of emerging software vulnerabilities. The outcomes of this project will be a deep-learning-based detection approach and an open-source tool that can capture precision correlations between deep code features and diverse vulnerabilities to pinpoint emerging vulnerabilities without the need for bug specifications. Significant benefits include greatly improved quality, reliability and security for modern software systems.Read moreRead less
Developing A Smart Farming Oriented Secure Data Infrastructure. Smart farming is the future of agriculture. However, recently the Federal Bureau of Investigation has issued a
warning that the lack of data privacy and cyber security mechanisms in the field runs a high risk of disaster. This
project aims to establish an innovative secure data infrastructure for smart farming including secure and automated smart farming supply-chain management. The deliverables of this project will include the cutt ....Developing A Smart Farming Oriented Secure Data Infrastructure. Smart farming is the future of agriculture. However, recently the Federal Bureau of Investigation has issued a
warning that the lack of data privacy and cyber security mechanisms in the field runs a high risk of disaster. This
project aims to establish an innovative secure data infrastructure for smart farming including secure and automated smart farming supply-chain management. The deliverables of this project will include the cutting-edge Blockchain based secure IoT data management and privacy-preserving smart contracts for smart farming supply-chain management. This data infrastructure will be the first of its kind which will lay a solid foundation for smart farming technology.Read moreRead less
MemberGuard: Protecting Machine Learning Privacy from Membership Inference. Machine Learning has become a core part of many real-world applications. However, machine learning models are vulnerable to membership inference attacks. In these attacks, an adversary can infer if a given data record has been part of the model's training data. In this project, the team aims to develop new techniques that can be used to counter these attacks, such as 1) new analytical models for membership leakage, 2) ne ....MemberGuard: Protecting Machine Learning Privacy from Membership Inference. Machine Learning has become a core part of many real-world applications. However, machine learning models are vulnerable to membership inference attacks. In these attacks, an adversary can infer if a given data record has been part of the model's training data. In this project, the team aims to develop new techniques that can be used to counter these attacks, such as 1) new analytical models for membership leakage, 2) new methods for susceptibility diagnosis, 3) new defences that leverage privacy and utility. Data-oriented services are estimated to be valuable assets in the future. These techniques can help Australia gain cutting edge advantage in machine learning security and privacy and protect its intellectual property on these services.Read moreRead less
A Novel Automatic Neural Network Feature Extractor. This project aims to study feature extraction abilities of convolutional as well as traditional neural networks and develop a generic feature extractor which can be applied to wide variety of real-world image and non-image data. New concepts for automatic feature extraction, feature explanation, hybrid evolutionary algorithms and non-iterative ensemble learning will be introduced and evaluated. The expected outcomes are a generic feature extrac ....A Novel Automatic Neural Network Feature Extractor. This project aims to study feature extraction abilities of convolutional as well as traditional neural networks and develop a generic feature extractor which can be applied to wide variety of real-world image and non-image data. New concepts for automatic feature extraction, feature explanation, hybrid evolutionary algorithms and non-iterative ensemble learning will be introduced and evaluated. The expected outcomes are a generic feature extractor for automatically extracting features, an optimiser for finding optimal parameters and non-iterative ensemble learning technique for classification of features into classes. The impact of this project will be automatic feature extractors and classifiers for real-world applications.Read moreRead less