115,100 results
People
PROJECT NUMBER • 2018-174
PROJECT STATUS:
COMPLETED

Women in Seafood Australasia - Understanding, supporting and promoting effective participation by women within the Australian seafood industry

This FRDC project, Understanding, supporting and promoting effective participation by women in the Australian seafood industry, was pivotal for WISA in supporting its future direction as an organisation. Research undertaken showcased the significance of the roles and contributions of seafood women...
ORGANISATION:
Women in Seafood Australasia (WISA)
TAGS
Workforce
Training
Media
Leadership
Human Dimensions Research
Blank
PROJECT NUMBER • 2018-173
PROJECT STATUS:
COMPLETED

Review of FRDC's Industry Partnership Agreements (IPAs), Research Advisory Committees (RACs), Subprograms and Coordination Programs

This report presents the outcomes of a project commissioned by the Fisheries Research & Development Corporation (FRDC) to provide: ‘…a comprehensive and independent review of the current FRDC partnership models with a view to identifying: how the various models are managed by the...
ORGANISATION:
Forest Hill Consulting
TAGS
Stakeholder
Resource Access And Allocation
Modelling
Capacity Building
Communities
PROJECT NUMBER • 2018-172
PROJECT STATUS:
COMPLETED

Methods to profile and connect the provenance of wild caught prawn fisheries and their values to the community

The wild prawn industry, as a key influencer of the community's (sustainability) perception of the Australian seafood industry, has addressed identified risks to social license so that it can protect its legal license to operate in public waters. This report provides the results and conclusions on...
ORGANISATION:
Australian Council of Prawn Fisheries Ltd (ACPF)
TAGS
Wild Catch
Stakeholder
Marketing
Fisheries Management
Community
SPECIES
Royal Red Prawn
Redspot King Prawn
King Prawns
Banana Prawns
Tiger Prawns
Adoption
PROJECT NUMBER • 2018-171
PROJECT STATUS:
COMPLETED

CRDC: FRDC Contribution: Growing a digital future - understanding digital capability in Australian agriculture

In an effort to respond to a rapidly changing agricultural environment and boost the industry's competitiveness entering a new age of digital farming, Cotton RDC and a group of Rural Research and Development Corporations (including FRDC) have come together to fund the Agriculture workforce digital...
ORGANISATION:
Cotton Research and Development Corporation (CRDC)
TAGS
Training
Resource Access And Allocation
Reproduction
Innovation
Education
Industry
Industry

Custom training and technical support for the fishery stock assessment software ‘stock synthesis’

Project number: 2018-168
Project Status:
Completed
Budget expenditure: $77,220.00
Principal Investigator: Michael F. O'Neill
Organisation: Department of Primary Industries (QLD)
Project start/end date: 31 Mar 2019 - 29 Jun 2020
Contact:
FRDC
TAGS
Wild Catch
Training
Sustainability
Stock Assessment
Software

Need

The Queensland Government Department of Agriculture and Fisheries (DAF) aims to manage fisheries utilising the best available science taking into account environmental, economic, social and cultural impacts.
Through the Government’s Sustainable Fisheries Strategy (SFS, 2018–2020), plans are actioned to establish regular stock assessments (ongoing annually or at least every two years) to provide the science for assessing key fishery stocks against reference points.
To conduct regular stock assessments of finfish, Fisheries Queensland and the SFS expert panel have directed DAF staff to investigate the use of off-the-shelf stock-assessment models. This recommendation is for delivery of recurring information to support fishery harvest strategies; and followed a review to support the use of common stock assessment methods and models (FRDC Research Code: 2014-039; http://www.frdc.com.au/media-and-publications/fish/fish-vol-26-3/skills-shortage-forecast-for-stock-assessments). This proposal is to progress Qld’s adoption of FRDC recommendations and research: project 2014-039.
DAF’s training needs are by 31st May 2019.
The aim for this training is to build stock assessment systems for DAF and help support similar national needs in Australia.

Objectives

1. DAF scientists to learn SS methodology and assumptions.
2. After 5-day course, DAF scientists to be proficient in the use of SS software with R
3. Produce 3–4 updated DAF finfish stock assessments through the 5-day course
4. Publish on success, outputs and findings of SS
5. Improve speed on future reassessments of fish stocks

Final report

ISBN: 978-0-7345-0464-7
Authors: M. F. O’Neill R. Lovett P. Bessell-Browne S. Streipert G. Leigh A. Campbell A. Northrop J. Wortmann F. Helidoniotis W.-H. Yang M. Holden and S. French.
Final Report • 2020-02-01 • 2.75 MB
2018-168-DLD.pdf

Summary

This is a report on ‘stock synthesis’ software training by CSIRO. Noted are training outputs and learnings, together with an assessment of what role stock synthesis (SS) may play in Department of Agriculture and
Fisheries (DAF) fish stock assessments. Findings suggest SS could potentially assess 50–60% of the fish species currently listed for Queensland stock assessment.
Reports on SS herein represent initial views after training. SS views may change in time with individuals, and with more use and learnings of the software.
Final Report • 2020-02-01 • 2.75 MB
2018-168-DLD.pdf

Summary

This is a report on ‘stock synthesis’ software training by CSIRO. Noted are training outputs and learnings, together with an assessment of what role stock synthesis (SS) may play in Department of Agriculture and
Fisheries (DAF) fish stock assessments. Findings suggest SS could potentially assess 50–60% of the fish species currently listed for Queensland stock assessment.
Reports on SS herein represent initial views after training. SS views may change in time with individuals, and with more use and learnings of the software.
Final Report • 2020-02-01 • 2.75 MB
2018-168-DLD.pdf

Summary

This is a report on ‘stock synthesis’ software training by CSIRO. Noted are training outputs and learnings, together with an assessment of what role stock synthesis (SS) may play in Department of Agriculture and
Fisheries (DAF) fish stock assessments. Findings suggest SS could potentially assess 50–60% of the fish species currently listed for Queensland stock assessment.
Reports on SS herein represent initial views after training. SS views may change in time with individuals, and with more use and learnings of the software.
Final Report • 2020-02-01 • 2.75 MB
2018-168-DLD.pdf

Summary

This is a report on ‘stock synthesis’ software training by CSIRO. Noted are training outputs and learnings, together with an assessment of what role stock synthesis (SS) may play in Department of Agriculture and
Fisheries (DAF) fish stock assessments. Findings suggest SS could potentially assess 50–60% of the fish species currently listed for Queensland stock assessment.
Reports on SS herein represent initial views after training. SS views may change in time with individuals, and with more use and learnings of the software.
Final Report • 2020-02-01 • 2.75 MB
2018-168-DLD.pdf

Summary

This is a report on ‘stock synthesis’ software training by CSIRO. Noted are training outputs and learnings, together with an assessment of what role stock synthesis (SS) may play in Department of Agriculture and
Fisheries (DAF) fish stock assessments. Findings suggest SS could potentially assess 50–60% of the fish species currently listed for Queensland stock assessment.
Reports on SS herein represent initial views after training. SS views may change in time with individuals, and with more use and learnings of the software.
Final Report • 2020-02-01 • 2.75 MB
2018-168-DLD.pdf

Summary

This is a report on ‘stock synthesis’ software training by CSIRO. Noted are training outputs and learnings, together with an assessment of what role stock synthesis (SS) may play in Department of Agriculture and
Fisheries (DAF) fish stock assessments. Findings suggest SS could potentially assess 50–60% of the fish species currently listed for Queensland stock assessment.
Reports on SS herein represent initial views after training. SS views may change in time with individuals, and with more use and learnings of the software.
Final Report • 2020-02-01 • 2.75 MB
2018-168-DLD.pdf

Summary

This is a report on ‘stock synthesis’ software training by CSIRO. Noted are training outputs and learnings, together with an assessment of what role stock synthesis (SS) may play in Department of Agriculture and
Fisheries (DAF) fish stock assessments. Findings suggest SS could potentially assess 50–60% of the fish species currently listed for Queensland stock assessment.
Reports on SS herein represent initial views after training. SS views may change in time with individuals, and with more use and learnings of the software.
Final Report • 2020-02-01 • 2.75 MB
2018-168-DLD.pdf

Summary

This is a report on ‘stock synthesis’ software training by CSIRO. Noted are training outputs and learnings, together with an assessment of what role stock synthesis (SS) may play in Department of Agriculture and
Fisheries (DAF) fish stock assessments. Findings suggest SS could potentially assess 50–60% of the fish species currently listed for Queensland stock assessment.
Reports on SS herein represent initial views after training. SS views may change in time with individuals, and with more use and learnings of the software.
Final Report • 2020-02-01 • 2.75 MB
2018-168-DLD.pdf

Summary

This is a report on ‘stock synthesis’ software training by CSIRO. Noted are training outputs and learnings, together with an assessment of what role stock synthesis (SS) may play in Department of Agriculture and
Fisheries (DAF) fish stock assessments. Findings suggest SS could potentially assess 50–60% of the fish species currently listed for Queensland stock assessment.
Reports on SS herein represent initial views after training. SS views may change in time with individuals, and with more use and learnings of the software.
Final Report • 2020-02-01 • 2.75 MB
2018-168-DLD.pdf

Summary

This is a report on ‘stock synthesis’ software training by CSIRO. Noted are training outputs and learnings, together with an assessment of what role stock synthesis (SS) may play in Department of Agriculture and
Fisheries (DAF) fish stock assessments. Findings suggest SS could potentially assess 50–60% of the fish species currently listed for Queensland stock assessment.
Reports on SS herein represent initial views after training. SS views may change in time with individuals, and with more use and learnings of the software.
Final Report • 2020-02-01 • 2.75 MB
2018-168-DLD.pdf

Summary

This is a report on ‘stock synthesis’ software training by CSIRO. Noted are training outputs and learnings, together with an assessment of what role stock synthesis (SS) may play in Department of Agriculture and
Fisheries (DAF) fish stock assessments. Findings suggest SS could potentially assess 50–60% of the fish species currently listed for Queensland stock assessment.
Reports on SS herein represent initial views after training. SS views may change in time with individuals, and with more use and learnings of the software.
Final Report • 2020-02-01 • 2.75 MB
2018-168-DLD.pdf

Summary

This is a report on ‘stock synthesis’ software training by CSIRO. Noted are training outputs and learnings, together with an assessment of what role stock synthesis (SS) may play in Department of Agriculture and
Fisheries (DAF) fish stock assessments. Findings suggest SS could potentially assess 50–60% of the fish species currently listed for Queensland stock assessment.
Reports on SS herein represent initial views after training. SS views may change in time with individuals, and with more use and learnings of the software.
Final Report • 2020-02-01 • 2.75 MB
2018-168-DLD.pdf

Summary

This is a report on ‘stock synthesis’ software training by CSIRO. Noted are training outputs and learnings, together with an assessment of what role stock synthesis (SS) may play in Department of Agriculture and
Fisheries (DAF) fish stock assessments. Findings suggest SS could potentially assess 50–60% of the fish species currently listed for Queensland stock assessment.
Reports on SS herein represent initial views after training. SS views may change in time with individuals, and with more use and learnings of the software.
Final Report • 2020-02-01 • 2.75 MB
2018-168-DLD.pdf

Summary

This is a report on ‘stock synthesis’ software training by CSIRO. Noted are training outputs and learnings, together with an assessment of what role stock synthesis (SS) may play in Department of Agriculture and
Fisheries (DAF) fish stock assessments. Findings suggest SS could potentially assess 50–60% of the fish species currently listed for Queensland stock assessment.
Reports on SS herein represent initial views after training. SS views may change in time with individuals, and with more use and learnings of the software.
Final Report • 2020-02-01 • 2.75 MB
2018-168-DLD.pdf

Summary

This is a report on ‘stock synthesis’ software training by CSIRO. Noted are training outputs and learnings, together with an assessment of what role stock synthesis (SS) may play in Department of Agriculture and
Fisheries (DAF) fish stock assessments. Findings suggest SS could potentially assess 50–60% of the fish species currently listed for Queensland stock assessment.
Reports on SS herein represent initial views after training. SS views may change in time with individuals, and with more use and learnings of the software.
Industry
PROJECT NUMBER • 2018-166
PROJECT STATUS:
CURRENT

Australian Prawn Farms - Emerging disease investigation

This project was developed by Future Fisheries Veterinary Service (FFVS) in collaboration with Australian Prawn Farms (APF), James Cook University (JCU) Aqua Path laboratory, Queensland Biosecurity Sciences Laboratory (BSL) and the University of Adelaide (UofA). Unprecedented mortality events...
ORGANISATION:
Australian Prawn Farms Pty Ltd
SPECIES
Black Tiger Prawn
Industry
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