Scientific tools to support practical implementation of EBFM

1. Scientific tools to support practical implementation of EBFM Tony Smith*, Beth Fulton*, Alistair Hobday*, David Smith*, Paula Shoulder# CSIRO Marine Research*, AFMA#

2. Outline • Ecosystem based fisheries management (EBFM) • A framework for tool development • Ecological risk assessment (ERA) • Management strategy evaluation (MSE) • Harvest strategy framework (HSF) • Expanding the toolbox • Acknowledgements

3. Ecosystem based fisheries management (EBFM) • Aka ecosystem approach to fisheries (FAO) • Objective: to sustain healthy marine ecosystems and the fisheries they support (Pikkitch et al 2004) • Key elements: • avoid degradation of ecosystems • minimize risk of irreversible change • obtain long term socioeconomic benefits • precautionary approach to uncertainty

4. Policy drivers in Australia • Major shift in emphasis in 1990s • National commitment to ecologically sustainable development (ESD) • New fisheries legislation • New environmental legislation • Australia’s Oceans Policy • Policy development ran ahead of the scientific tools and methods to support it (and still is)

5. Response to policy drivers • monitoring (ecological indicators) • assessment (ERA) • management strategy evaluation (EBFM) • performance measures (acceptable limits to change) • spatial analysis in support of spatial management • etc

6. Adaptive management cycle Management strategy evaluation = MSE Impact Monitoring Ecosystem Assessment Management strategy MSE Fishery Decision rule Regulation

7. A framework for tool development

8. Example – stock assessment

10. Ecological Risk Assessment • ERA is a key tool in support of EBFM • Analogue of stock assessment • Requirement to assess impacts of fishing on all components of ecological systems, including species, habitats and communities • CSIRO and AFMA joint project to develop and apply ERA methods for fisheries • Developed ERAEF (ERA for effects of fishing)

11. Criteria for ERA design • Comprehensive • Scientifically defensible • Make use of existing data and information • Precautionary given uncertainty • Cost effective • Flexible (apply to all types of fisheries) • Transparent • Understandable to stakeholders • Help inform management response • No such method exists!

12. ERAEF hierarchical structure Comprehensive Uncertain Scoping Scoping Time & $$ Qualitative Level 1 L H Level 2 Risk Management Response Focused More certain L H Time & $$ Quantitative Level 3 L H

13. ERAEF • 5 ecological components assessed • target species • byproduct and bycatch species • threatened, endangered and protected species • habitats • communities • 25 activities assessed, including 5 external to the fishery

14. ERAEF – Scoping and Level 1 • Scoping • fishery description, management objectives, lists of species, habitats and communities • Level 1 • consider each of 25 activities X 5 components • plausible worst case approach • if medium or high risk, proceed to Level 2 (or risk mitigation)

15. ERAEF – Level 2 • Level 3 would solve this equation…e.g. stock assessment • Cannot do this for all species…time and $ • PSA estimates the “r” and the “q” • Use available attributes related to these terms • (B = units in species, habitat or community component)

16. ERAEF – Level 2 - PSA HIGH LOW

17. Productivity attributes Maximum age Age at maturity Size at maturity Annual fecundity Maximum size Reproductive strategy Trophic level Susceptibility attributes Availability Overlap with fishery Global distribution Encounterability Water column position Depth range overlap Adult Habitat Selectivity Size at Maturity Total records (+/-) (TEP, DI, TA/BP) Post-capture mortality Fate on discarding Species attributes

18. Place species on PSA plot HIGH LOW

19. Example bycatch PSA Have conducted PSA analyses for over 1800 species to date

20. Boulders supporting crinoids; coarse sediments supporting octocorals (5 types) Inner shelf sediments supporting small/ encrusting epifauna (5 types) Sediments, various morphology/ supporting small/ encrusting/ mobile epifauna (58 types) Habitats SGF classification based on photographic images (sediment, geomorphology, fauna) Sediments, variously current/ wave rippled/ bioturbated supporting large epifauna (sponges, octocorals, crinoids) (19 types)

21. Communities – bioregions x depth

22. Purse-seine Example: Species Risk Distributions Across Fisheries Trawl Longline

23. H S L P H L ERAEF overview e.g. stock assessment e.g. PVA e.g. Ecosim Level3 H H S S Level2 L L X X P H L P H L Level1 Target Bycatch TEP Habitats Communities Fishing Activities Scoping

25. Whole of fishery assessment using MSE • Context • Southern and Eastern Scalefish and Shark Fishery • Multi-everything • species • gear (trawl, seine, gillnet, longline etc) • depth (20-1300m) • latitude (sub-tropical to sub-Antarctic) • Recently brought under single management plan

26. MSE for a whole fishery • Management arrangements • QMS with 34 stocks/species (ITQs) • licence limits by sector • some gear restrictions • Issues • declining economic performance in most sectors • increasing number of overfished species • increasing effort in several sectors, new grounds

27. AMS project • Rethink management arrangements for SESSF • Strategic approach – bring stakeholders along • Management strategy evaluation approach (MSE) • Showcase for EBFM (worst  best) • Two phases • qualitative (expert judgement) • quantitative (Atlantis model)

28. AMS – phase 1 • Steps in MSE • specify objectives (ecological, economic, social) • develop performance measures (quantitative) • specify management options (4 scenarios) • predict consequences (expert judgement) • identify tradeoffs (decision table)

29. AMS – phase 1 • Management scenarios • Status quo – pessimistic • Status quo - optimistic • Enhance quota management system • Mix of quota, effort, gear and spatial management • Evaluate against 26 performance indicators • Economic, ecological, social

30. MSE output – decision table

31. AMS – phase 1 • Conclusions from phase 1 • Most economic and ecological indicators continue to deteriorate under scenarios 1 to 3 • Management scenario 4 does best in the medium to longer term, but with severe short term economic pain • Results were used to argue for a “restructure” package to reduce effort and to smooth the transition to a sustainable fishery

32. AMS – phase 2 - Atlantis

33. Biophysical • Biophysical (operating) model = “virtual world” • Physical • can include environmental forcing at variety of temporal and spatial scales • Structure and function • physical properties per cell • sediment nutrient cycling • growth limitation (nutrient, light, oxygen, space, substrate) • anthropogenic drivers

34. Biophysical • Ecological • population dynamics , habitat-dependent, multispecies, whole-of-ecosystem • Structure and function • main processes (feeding, reproduction, movement, mortality, waste, age) • functional groups (by size and diet) • invertebrate biomass pools, vertebrate age structured (+ condition)

35. pelagic fish demersal fish seals birds small pelagics baleen whales squid zooplankton jellies phytoplankton Unexploited toothed whales demersal sharks pelagic sharks zoobenthos filter feeders infauna detritus macrophytes

36. pelagic fish demersal fish seals birds baleen whales small pelagics zooplankton phytoplankton Heavily exploited toothed whales pelagic sharks demersal sharks squid zoobenthos filter feeders jellies infauna detritus macrophytes

37. Socioeconomic

38. Sectors • Exploitation (e.g. fisheries) • simple through to sophisticated • Harvest example • multiple fleets • ports (with dependent communities) • gears (catchability, availability, selectivity, escapement, creep, interactions) • effort allocation (access, exploration, displacement, costs, trading, targeting, behavioural types, vessel sizes) • impacts (including discarding, habitat modification etc) • compliance (differential levels & take-up, effects on harvesting, reporting veracity)

39. Monitoring and assessment

40. Monitoring & Assessment • Data collection • simple signal with noise through to detailed models • Fisheries dependent data (with error) • Fisheries independent data (with error) • observers • surveys (trawl and acoustic) • multiple spatial/temporal resolutions • Additional processing (aging, aggregate data, assessment models)

41. Decision making

42. Management • Management levers of interest • trigger points (allowances for mixed-species fisheries) • quotas (TAC, regional, companion, basket, ITQ) • seasonal access • zoning (different fleet access, MPA, seasonal) • gear (bycatch mitigation, limitation, modification, transferability) • size limits, days at sea • trip limits

43. Status quo (S1) vs Radical change (S4) AMS Phase 2 - results

44. CPUE comparison

45. Effort comparison

46. Relative Return comparison

47. Ecological status comparison

48. Intense conflict Scenario 1 No conflict Scenario 4 Gear conflict comparison

50. Harvest strategy framework for the SESSF • 34 stocks/species under quota management by 2005 • A third of these with quantitative assessments • 7 stocks classified as overfished • Despite considerable work on MSE, reference points, etc, no agreement on decision rules for setting TACs • Requirement that harvest strategies including formal decision rules be implemented by 2005