Project number: 2015-506
Project Status:
Completed
Budget expenditure: $15,000.00
Principal Investigator: Beth Fulton
Organisation: CSIRO Oceans and Atmosphere Hobart
Project start/end date: 29 Feb 2016 - 30 May 2016
Contact:
FRDC

Need

Australian Government and industry have many objectives of Australia’s natural resources. Amongst their highest priorities are the sustainable use of Australian resources. Reassuring the public that this is being achieved can be difficult, however, as many of Australia’s resources are poorly known – even 18% of reasonably well known species are of unknown stock status (Georgeson et al 2014). This means that new and developing sectors, attempting to exploit resources in a new way, or targeting species that have not previously been considered main target species can come under considerable stakeholder scrutiny and public debate (as seen in the Small Pelagic Fishery in the last few years). Such situations will not ease under climate change as ecosystem restructuring will mean the mix of target species will need to shift, making the most of new opportunities, if Australian fisheries are to remain sustainable (Fulton and Gorton 2014).

To this end schemes that support responsible fisheries management of developing fisheries or small-scale, data-constrained fisheries are an important new tool needed to achieve Australian objectives for sustainable fisheries. Such a scheme will require the development of management approaches that more effectively incorporate the diverse and potentially conflicting needs and effects across all sectors accessing Australian stocks. It is already understood that management will need to more explicitly acknowledge the role of ecosystem integrity in delivering sustainable stocks and that new multispecies harvesting regimes will be required (Zhou et al 2010, Garcia et al 2012). However, the true form of such harvesting remains uncertain and any approach will need to allow for adaptive learning. Consequently, there is a need to design multispecies harvesting schemes and self-learning adaptive management approaches.

In addition to new approaches a broader set of the management and fisheries science community needs to be at ease with ecosystem oriented tools, such as Ecopath with Ecosim. Training in the latest versions of the software by those most intimately associated with it is an important step in that direction for fisheries science professionals from all jurisdictions.

Objectives

1. Scope the design of a self-learning adaptive management approach for data challenged and developing fisheries (including potential approaches for assessing species currently listed as uncertain)
2. Provide insight into assessment approaches for "uncertain" stocks and forms of multi-species harvesting (including of forage fish species) that are sustainable, account for the production-biodiversity tradeoffs, and allow for adaptive learning.
3. Expand the EBFM tool capacity of state fisheries bodies by introducing new users to the EwE software and up-skilling those already familiar with earlier versions
4. Increase the capacity of fisheries agencies and research bodies in all jurisdictions to test ecosystem based fisheries management approaches using explicit ecosystem oriented software (Ecopath with Ecosim), which can be used to synthesis existing understanding and to test management concepts using the MSE approach.

Final report

ISBN: 978-1-4863-1227-6
Author: Beth Fulton
Final Report • 2019-05-16 • 963.59 KB
2015-506-DLD.pdf

Summary

This report summarises the outcome of a Ralf Yorque symposium – a small fairly informal series of workshops aimed at providing the big picture thinking space needed to underpin multi-year, multi-project research programs that incrementally piece together the necessary components of a pragmatic, practical and effective means of delivering sustainable fisheries – across ecosystems, for data poor and data rich species alike, in the context of climate and other cumulative pressures on Australian and global ecosystems.

Such an exercise is not a trivial undertaking and benefited from synthesizing current understanding, drawing insights from the last 40-50 years of the development of adaptive management and to scope what would be required of the design of a self-learning adaptive management approach for developing fisheries or fisheries with limited access to data.

Related research

Environment
Environment
Industry