Dr Carlo Mattone ~ Postdoctoral Research Fellow
College of Science & Engineering
- About
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Carlo is a coastal and estuarine ecologist with a broad spectrum of research interests and experiences, which include marine invertebrates, fish, and water quality dynamics. Carlo has spent 10+ years doing research on a wide range of aspects of coastal ecology, most recently he focused on how water quality dynamics influence fauna at different trophic levels and how this shapes their interactions with their environment. Some of his most recent research investigated how connectivity and water quality influence the nursery ground value for some coastal fish. He aims to develop a better understanding of the processes that regulate ecological functions in coastal and estuarine systems to develop better management approaches. Additionally, most recently he started collaboration within JCU to develop artificial intelligence aimed at improving the way we collect and process data.
- Publications
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These are the most recent publications associated with this author. To see a detailed profile of all publications stored at JCU, visit ResearchOnline@JCU.
- Journal Articles
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- Sheaves M, Bradley M, Herrera C, Mattone C, Lennard C, Sheaves J and Konovalov D (in press) Optimizing video sampling for juvenile fish surveys: using deep learning and evaluation of assumptions to produce critical fisheries parameters. Fish and Fisheries, , DOI:10.1111/faf.12501.
- Sheaves M, Abrantes K, Barnett A, Benham C, Dale P, Mattone C, Sheaves A, Waltham N and Bradley M (in press) The consequences of paradigm change and poorly validated science: the example of the value of mangroves to fisheries. Fish and Fisheries, , DOI:10.1111/faf.12479.
- Mattone C and Sheaves M (2019) The intertidal benthic community of mangrove dominated estuaries: the ecological implications of a decoupled habitat. ICES Journal of Marine Science, 76 (7), pp. 2329-2337, DOI:10.1093/icesjms/fsz145.
- Mattone C and Sheaves M (2017) Patterns, drivers and implications of dissolved oxygen dynamics in tropical mangrove forests. Estuarine Coastal and Shelf Science, 197, pp. 205-213, DOI:10.1016/j.ecss.2017.08.028.
- Sheaves J, Dingle L and Mattone C (2016) Biotic hotspots in mangrove-dominated estuaries: macro-invertebrate aggregation in unvegetated lower intertidal flats. Marine Ecology Progress Series, 556, pp. 31-43, DOI:10.3354/meps11860.
- Davis B, Mattone C and Sheaves M (2014) Bottom-up control regulates patterns of fish connectivity and assemblage structure in coastal wetlands. Marine Ecology Progress Series, 500, pp. 175-186, DOI:10.3354/meps10671.
- Current Funding
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Current and recent Research Funding to JCU is shown by funding source and project.
WV Scott Charitable Trust - Research Grant
Addressing urgent welfare concerns for Blackspotted Croaker (Protonibea diacanthus) populations in Queensland
- Indicative Funding
- $50,000 over 3 years
- Summary
- The Blackspotted Croaker (also known as black jewfish) is targeted by commercial, recreational, indigenous and charter fishing groups. Since 2017 there has been a rapid increase in targeted commercial fishing effort for Blackspotteed Croaker in Queensland. Given the high value of Blackspotteed Croaker, their vulnerability as aggregating species and the absence of a stock assessment to inform how many populations need to be managed, updated biological/ecological information (Including stock structure) are needed for assessment and protection of Blackspotted Croaker stock(s) in Queensland. The study aims at identifying stock structure and connectivity (including aggregation time) in order to improve management of th species across Queensland.
- Investigators
- Marcus Sheaves, Adam Barnett, Carlo Mattone and Michael Bradley (College of Science & Engineering)
- Keywords
- Population Genetic Structure; Fisheries Management; Epinephelus nigritus (Serranidae); Blackspotted Croaker
Fisheries Research & Development Corporation - Annual Competitive Round
Application of a machine learning approach for effective stock management of abalone
- Indicative Funding
- $115,649 over 2 years
- Summary
- Determining the number and size distribution of abalone present at various stages of production is critical information for effective stock management. Currently the Australian abalone aquaculture industry spends in the order of $25,000 per annum, per farm, gathering this information by hand. However, the resulting data is of mediocre quality, is limited in its scope, and collecting the data causes stress to the animals which can compromise growth and survival. Automated counting and measuring of abalone will increase farm efficiency and productivity in the short term and, in the longer term, will provide an advanced platform for further R&D improvements. Artificial intelligence and machine learning has now matured to a point that accurately counting and measuring abalone is possible using this approach. This project would involve the development, training and validation of a machine learning model to identify, segment and measure quantitative abalone traits in production systems, and render the product data to be accessible and applicable for farmers.
- Investigators
- Jan Strugnell, Marcus Sheaves, Carlo Mattone, Ickjai Lee, Joanne Lee, Jason Holdsworth and Art (Hemmaphan) Suwanwiwat (College of Science & Engineering)
- Keywords
- Abalone (Haliotidae); Machine Learning
Hinchinbrook Shire Council - Contract Research
Lower Herbert Drainage Concerns-Mangrove Expansion
- Indicative Funding
- $29,033 over 1 year
- Summary
- The Project aims at assessing the effect of removing overhanging mangrove trees that have grown over artificially made channels over the last few decades. The mangrove pose a threat to the water flow, causing the drain to overfill during periods of heavy rainfall and flood the surrounding areas.
- Investigators
- Marcus Sheaves, Nathan Waltham, Carlo Mattone and Michael Bradley (College of Science & Engineering and TropWATER)
- Keywords
- Mangrove Forest; Nursery Grounds; Clearance
World Wide Fund for Nature - Contract Research
From Coastal Communities to Cloud Communities ? New Application and Artificial Intelligence to Monitor Fish Stocks Using Photos ? Application Development
- Indicative Funding
- $53,100 over 1 year
- Summary
- The Project aims at develop an artificial intelligence capable to autonomously identify fish species and number from images collected at fish markets in remote location, so that effective catch rate can be evaluated and management policies can be developed.
- Investigators
- Marcus Sheaves, Carlo Mattone, Michael Bradley, Joanne Lee, Jason Holdsworth, Art (Hemmaphan) Suwanwiwat and Ickjai Lee (College of Science & Engineering)
- Keywords
- Artificial Intelligence; Phone App; Caught Fish; Catch Rate
WA Department of Primary Industries and Regional Development - Contract Research
Identification of benthic structure using machine learning
- Indicative Funding
- $36,200 (administered by Wa Department of Primary Industries and Regional Development)
- Summary
- The Project aims at automating the classification of benthic structure and biota from images using machine learning
- Investigators
- Marcus Sheaves, Bronson Philippa, Carlo Mattone and Michael Bradley (College of Science & Engineering)
- Keywords
- Benthic Assessment; Machine Learning
MAKO Tidal Turbines Pty Ltd - Contract Research
Barney Point Turbine Monitoring
- Indicative Funding
- $27,457
- Summary
- Monitoring surface video, underwater video, underwater acoustic and sidescan data streams using AI (January-April 2019) (including monthly regular reporting, final reporting and feasibility analysis), to assess whether the tidal turbine impacts fish and other aquatic organisms during its operations.
- Investigators
- Marcus Sheaves, Carlo Mattone and Dmitry Konovalov (College of Science & Engineering)
- Keywords
- Artificial Intelligence; Impact Assessment; Tidal turbine monitoring
The World Wide Fund for Nature, Australia - Consultancy
Queensland Coral Reef Fin Fish Fishery Electronic Observer
- Indicative Funding
- $6,000 over 1 year
- Summary
- To understand the value of a new technique for collecting critical fisheries information regarding target, bycatch and threatened species interactions in the coral reef fin fish fishery through electronic observation and machine learning.
- Investigators
- Marcus Sheaves and Carlo Mattone (College of Science & Engineering)
- Keywords
- Artificial Intelligence; Fisheries Management; Line Fishers
- Supervision
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Advisory Accreditation: I can be on your Advisory Panel as a Secondary Advisor.
These Higher Degree Research projects are either current or by students who have completed their studies within the past 5 years at JCU. Linked titles show theses available within ResearchOnline@JCU.
- Current
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- How habitat use of stingrays is impacted by biotic resources: an assessment of predator-prey interactions in intertidal sandflats (PhD , Secondary Advisor)
Connect with me
- Phone
- Location
- Advisory Accreditation
- Secondary Advisor
My research areas
Similar to me
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Prof Marcus SheavesCollege of Science & Engineering
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Prof Ian AtkinsoneResearch Centre