LESSONS LEARNED FROM RISK ASSESSMENT FOR BIOLOGICAL CONTROL ORGANISMS

Transcription

1 South Asia Biosafety Conference - CERA September 2013 New Delhi, India LESSONS LEARNED FROM RISK ASSESSMENT FOR BIOLOGICAL CONTROL ORGANISMS BARBARA BARRATT AGRESEARCH INVERMAY NEW ZEALAND

2 OUTLINE Environmental risk analysis The framework BC and risk assessment Why assess risk? What are the risks? How risk can be assessed Weighing risks against benefits Dealing with uncertainty What we can learn from risk assessment for BCAs

3 Risk assessment sits within a wider risk analysis framework: What is valued in the environment and what would be considered as harm? = risk hypothesis Transparency at all stages COMMUNICATION & CONSULTATION ASSESS RISKS ESTABLISH THE CONTEXT IDENTIFY RISKS ANALYSE RISKS EVALUATE and RANK RISKS TREAT RISKS MONITOR AND REVIEW Comprehensive list of what could happen, when and how? Likelihood and magnitude, ID uncertainty Where can risks be managed? Conduct more research, monitor impacts From: Australian and New Zealand Risk Management Standard AS/NZS 4360 Moeed A, Hickson R, Barratt BIP Principles of environmental risk assessment of invertebrates in biological control of arthropods. In: Bigler F, Babendreier D, Kuhlmann U ed. Environmental impact of arthropod biological control: methods and risk assessment. CABI Publishing, Delemont, Switzerland. Pp

4 WHY ASSESS RISK? To protect the things we value from harm To systematically identify, evaluate and prioritise risks To predict and avoid adverse impacts Regulatory requirement Regulators need the results of a risk assessment for decision support

5 EXAMPLE: HSNO MINIMUM STANDARDS NZ EPA must decline an application if the new organism [incl. GMO] is likely to: (a) Cause any significant displacement of any native species within its natural habitat; or (b) Cause any significant deterioration of natural habitats; or (d) Cause any significant adverse effect to New Zealand s inherent genetic diversity

6 EXAMPLE: HSNO MINIMUM STANDARDS NZ EPA must decline an application if the new organism [incl. GMO] is likely to: (a) Cause any significant displacement of any native species within its natural habitat; or (b) Cause any significant deterioration of natural habitats; or (d) Cause any significant adverse effect to New Zealand s inherent genetic diversity NZ s values and public policy goals

7 EXAMPLE: USEPA USEPA considers risk to be the chance of harmful effects to ecological systems resulting from exposure to an environmental stressor A stressor is any physical, chemical, or biological entity that can induce an adverse response Stressors may adversely affect specific natural resources or entire ecosystems, including plants and animals, as well as the environment with which they interact USA s values and public policy goals

8 BIOLOGICAL CONTROL Pests often arrive without natural enemies Natural enemies introduced to control pests BCAs can be parasitoids, predators, pathogens Target pests can be animals, plants or pathogens Three main types of BC Classical BC released into the environment Inundative BC not expected to establish Conservation BC enhancing existing natural enemies

9 WHAT ARE THE RISKS FOR BCAS? Non-target impacts BCA attacks species other than the target NT attack leads to population impacts BCA attacks valued species (e.g. other BCAs, endangered spp. ) Host range expansion BCA acquires additional hosts over time Host preferences shift Competition/hybridization with other natural enemies BCA competes with or displaces existing natural enemies BCA hybridizes with related species compromising genetic integrity Indirect effects Complex and unpredictable impacts at other trophic levels Food web effects/ environmental effects

10 HOW IS RA CARRIED OUT FOR BCAS? Case by case: 1. Pre-introduction 2. In quarantine

11 1. PRE-INTRODUCTION RA Determine: Natural host range Impacts in other areas of introduction Potential host range in receiving environment Host specificity Determine taxonomic breadth of hosts ID candidates with unacceptable risk Biotypes BCA, target

12 1. PRE-INTRODUCTION RA Determine: Natural host range Impacts in other areas of introduction Potential host range in receiving environment Biotypes BCA, target Biosafety record in the field How accurate were predictions?

13 1. PRE-INTRODUCTION RA Determine: Natural host range Impacts in other areas of introduction Potential host range in receiving environment Biotypes BCA, target Literature and databases Collections Field surveys

14 1. PRE-INTRODUCTION RA Determine: Natural host range Impacts in other areas of introduction Potential host range in receiving environment Biotypes of BCA BCA biotypes can have different host ranges Ensure that source of BCAs is equivalent to that used in tests and released

15 2. QUARANTINE TESTING Most informative predict potential host range Choices to be made: Test species selection Type and design of tests What to measure Discuss choices with regulators/ stakeholders

16 TEST SPECIES SELECTION WEED TARGETS Well defined process, tested and proven Centrifugal phylogenetic testing (Wapshere, 1974) Testing sequence Target weed Closely related species Less closely related spp. Distantly related species Profile of host range Include cultivated and valued plants

17 TEST SPECIES SELECTION WEED TARGET Later refined: Too many false positives in cage tests Host selection cues being by-passed Safe BCAs being rejected Reverse testing sequence (Wapshere, 1989) Expose test plants at the critical host selection phase Only if positive, further tests at the next phase

18 Example: Cinnabar moth for ragwort biocontrol Yes Do adults oviposit on the plant? No Do larvae feed on the plant? No further testing Yes No Do larvae pupate and emerge successfully? No further testing Yes Carry out larger scale or field tests on only these spp. No No further testing?

19 TEST SPECIES SELECTION INSECT TARGET More challenging: Far more potential species Less well known taxonomically Rearing test species more difficult Extra trophic level Consider behaviour of target and BCA

20 TEST SPECIES SELECTION INSECT TARGET List species with Phylogenetic and ecological affinities between the target and NT species Determine target/nt range overlap ID taxa most immediately at risk May require field surveys Formulate list of test species most 'at risk' Carry out tests on these in quarantine Include beneficials, other BCAs, insects of commercial, cultural or iconic significance Evaluate the results of initial tests Determine the need for further testing Kuhlmann, U., Schaffner, U. and Mason, P.G., Selection of non-target species for host specificity testing. Pp In: Environmental impact of invertebrates for biological control of arthropods: methods and risk assessment F. Bigler, D. Babendreier and U. Kuhlmann (Ed.) CABI Publishing, Wallingford, Oxford

21 PRIORITY RANKING OF NON-TARGET INVERTEBRATES (PRONTI) Developed for GM plants: Uses database of invertebrates in receiving environment Data for each species on biology, ecology, resilience, testability, social and economic value (published info) Model calculates combined score: (hazard x exposure) x (status* + value + testability) resilience** * status = combination of biomass, food web and special function scores ** resilience = attributes that might mitigate the risk (e.g. dispersal ability, a high intrinsic rate of population increase etc.)

22 PRIORITY RANKING OF NON-TARGET INVERTEBRATES (PRONTI) Developed for GM plants: Uses database of invertebrates in receiving environment Data for each species on biology, ecology, resilience, testability, social and economic value (published info) Model calculates combined score: (hazard x exposure) x (status* + value + testability) resilience** * status = combination of biomass, food web and special function scores ** resilience = attributes of a species that might mitigate the risk (e.g. dispersal ability, a high intrinsic rate of population increase etc.)

23 PRONTI FOR BIOLOGICAL CONTROL Being evaluated for BCAs for invertebrate targets Advantages: Transparent process for regulators Peer-reviewed published information More objective way of selecting NT species More species considered Disadvantages: Database of invertebrates needed for the receiving environment

24 QUARANTINE TESTING TEST METHODS No-choice tests Conservative Is NT in fundamental host range? Prone to false positives Choice tests Which species is preferred? Is a NT attacked when target present? Not necessarily indicative of field situation Sequential tests Exposure to successive NTs with periodic re-exposure to the target BIREA - Biocontrol Information Resource for EPA Applicants

25 QUARANTINE TESTING TEST METHODS Test design pilot tests to determine: BCA : host ratio Exposure period Arena size Critical factors: Vigour and performance of organisms Appropriate controls and replication Consistent environmental conditions food plants etc.

26 QUARANTINE TESTING - WHAT TO MEASURE Non-target attack rates (target cf. NT) Compare developmental rates Rear BCA to check viability/fitness of offspring Dissect survivors (insect target) Impact on NT hosts Survival, feeding, fecundity (insect target) Growth, damage, seed set etc. (weed target)

27 QUARANTINE TESTING - INTERPRETATION Risk of over- or under-estimation of host range Artificial conditions; abnormal behaviour Environmental cues absent Poor performance of BCA/ poor fitness of test species Data analysis Interpretation of rare events Withers TM, Carlson CA, Gresham BA Statistical tools to interpret risks that arise from rare events in host specificity testing. Biological Control 64:

28 WEIGHING RISKS AGAINST BENEFITS Risks identified and assessed preintroduction and in quarantine tests For each risk/benefit evaluate: How likely is this to happen? If it did, what would be the consequences?

29 FRAMEWORK FOR EVALUATING ADVERSE RISKS Likelihood of an adverse effect Magnitude of adverse effect highly improbable improbable (remote) very unlikely unlikely (occasional) likely very likely minimal highly localised impact, affecting a few individuals of a community, no ecosystem impact minor localised and contained reversible impact, some communities temporarily damaged, no impact on species or ecosystems moderate measurable long term damage to communities, limited spread, medium term individual ecosystem damage, no species damage major long term/irreversible damage to localised ecosystem but no species loss massive irreversible ecosystem damage including species loss extremely likely

30 FRAMEWORK FOR EVALUATING BENEFITS Likelihood of a beneficial effect Magnitude of benefit highly improbable improbable (remote) very unlikely unlikely (occasional) likely very likely minimal highly localised benefit, affecting few individuals members of communities of flora or fauna, no ecosystem benefit minor local and contained environmental benefit; no discernible ecosystem benefit moderate measurable benefit to localised plant/animal communities major long-term benefit to localised ecosystems massive long-term, widespread benefits to species and/or ecosystems extremely likely

31 LEVEL OF RISK AND BENEFIT Likelihood Magnitude of effect Minimal Minor Moderate Major Massive Highly improbable A A B C D Improbable A B C D E Very unlikely B C D E E Unlikely C D E E F Likely D E E F F Very likely E E F F G Extremely likely E F F G G For each risk likelihood and magnitude combined to give a rank/ index for decision-making A & B negligible; C low; D & E medium to high (may or may not be acceptable); F & G extreme

32 Commercially available BCAs EU-ERBIC project

33 DEALING WITH UNCERTAINTY There will always be some uncertainty Context of uncertainty for classical BCAs: Exposure is hard to control, manage, mitigate Hazard is permanent, will spread, irreversible Other considerations: more data to reduce uncertainty cumulative effects time lags balance of short term benefit vs. long-term risk population impacts extrapolation to real world } indicates a riskaverse approach Make judgement on the significance of uncertainly

34 LESSONS LEARNED FROM RA FOR BCAS Important to establish the context and develop meaningful risk hypotheses Case-by-case approach Understand the organisms involved (ecology, distribution, phenology, behaviour) Design robust tests with appropriate test species to make realistic predictions Careful evaluation of likelihood and magnitude of consequences for risks and benefits will provide consistency and balance in RA Clarity of context around uncertainty Verify predictions by post-release monitoring

35 ACKNOWLEDGEMENTS Colleagues in AgResearch and the Research collaboration Better Border Biosecurity Department of Conservation EPA New Zealand Funding: FRST MBIE