Presentation is loading. Please wait.

Presentation is loading. Please wait.

RA Framework. Risk Assessment ‘Area of concern’…  Every risk assessment has a geographic dimension  You need to explicitly identify the geographic.

Similar presentations


Presentation on theme: "RA Framework. Risk Assessment ‘Area of concern’…  Every risk assessment has a geographic dimension  You need to explicitly identify the geographic."— Presentation transcript:

1 RA Framework

2 Risk Assessment

3 ‘Area of concern’…  Every risk assessment has a geographic dimension  You need to explicitly identify the geographic area for which the assessment pertains  must be clearly defined  Big enough, but not too big

4 Case studies’ experience…  Area of concern

5 ESBW Case Study – area of concern  Province of Quebec  But…  UAF 09-751  opportunity to be more quantitative  satisfy DSS evaluation goal

6 Risk Assessment

7  Quick assessment (elements of a full assessment but done in less detail)  Determines whether immediate action is needed or whether the full assessment should continue  Requires relatively little information  Likelihood and impacts – but quick & dirty Pre-assessment

8  Does the pest meet the criteria for a quarantine pest?  What is the potential for the pest to be associated with the commodity or pathway?  What is the potential impact of the pest?  How likely is introduction and establishment of the pest if no mitigation measures are applied to the pathway(s)? Pre-assessment – for IAS

9  A pest of potential economic importance to the area endangered thereby and not yet present there, or present but not widely distributed and being officially controlled [ISPM No. 5, 2006] Quarantine Pest

10 Risk Assessment

11  What bad thing could happen?  Categorizing the pest  How likely is it to happen?  Potential introduction & spread  How bad will it be?  Potential economic & environmental effects Risk  Risk = Likelihood X Consequences

12  Likelihood  Potential  Probability  Quantitative or qualitative  Relative possibility of the event Risk  Risk = Likelihood X Consequences

13  Economic and environmental impacts  Effects  Consequences  Quantitative or qualitative  Relative magnitude of the event Risk  Risk = Likelihood X Consequences

14 Qualitative vs. quantitative pest risk assessments  Qualitative pest risk assessments:  Non-numerical terms  Descriptive words  Highly adaptable  Most commonly used method  Challenge to be consistent & use terms that are interpreted consistently by others  “The pest is highly likely to be present on conifer seedlings imported from ….”  “The pest is expected to have negligible effects on market sales”  “Outbreaks will be as frequent and serious as outbreaks of the native pest….”

15 Qualitative vs. quantitative pest risk assessments  Quantitative pest risk assessments:  Numerical terms  Measurable  Assigns values to variables  Programs for modelling likelihood or impacts (e.g., @Risk, Crystal Ball, ModelRisk)  Challenge to obtain data or defend selection of values for variables  “The pest is expected to be present at detectable levels in 99 seed shipments out of 100”  “There is an 85% chance of losses equalling or exceeding 1.2 million m3 of softwood growing stock per annum”  “Outbreaks are projected to occur once in every 50 years 95 times out of 100”

16 Choosing the right methods  Each method has pros & cons  May use a combination of methods to address different parts of the assessment  Quantitative to assess likelihood along different pathways  Qualitative to assess impacts  Method selected depends on many variables  Urgency of the issue  Seriousness of the issue  Availability of resources & expertise  Availability of data  Needs of the NPPO  Sensitivity of the issue  Focus this week will be on qualitative pest risk assessment

17 Likelihood of occurrence…  Native: outbreak  Alien: establishment Pest Host (Habitat) Environment (Ecosystem)

18  Perpetuation, for the foreseeable future, of a pest within an area after entry (ISPM 5, 2007) Alien: establishment Likelihood of occurrence…

19  Collect information from area(s) where pest occurs & in area of concern  Pest information  Environment information  Host information  Compare  Assess probability of establishment Probability of establishment Likelihood of occurrence…

20  Availability of suitable hosts, alternate hosts and vectors  Suitability of environment, including biotic & abiotic factors  Control measures  Other characteristics affecting probability of establishment Factors to consider… Likelihood of occurrence…

21  Are hosts & alternates present?  Are habitats available for pest plants?  How likely is the pest to find hosts? Are they abundant?  Are hosts present in the vicinity of expected entry points? Host information Likelihood of occurrence…

22  Is the pest adaptable?  Has it established/reached OB in other areas?  Can it adapt to different climatic or other environmental factors?  Can the pest seek out hosts? Is it mobile? Pest information Likelihood of occurrence…

23  How does the pest reproduce? Does it have a high reproductive capacity?  How does it survive adverse conditions?  Does it require an alternate host or a vector? Pest information Likelihood of occurrence…

24  Is a vector required for dispersal of the pest?  Is it present in the area of concern?  Is it likely to be introduced?  Are other potential vectors available? Dispersal & spread  Local and long-distance dispersal  Is it likely to get to the area of concern?  Effects of weather & landscape  Pop’n growth rates Likelihood of occurrence…

25  Does the climate in the area of concern differ from that where the pest occurs? How?  What climatic factors are critical for the pest’s success? What climatic factors, if any, are limiting?  Is the climate suitable for the pest? Will it be able to survive? Will it be able to reproduce? Climate information Likelihood of occurrence…

26 Climate information  Precipitation  Rain, snow, fog ….  Temperature  Seasonal highs and lows, temperature extremes …  Seasonal variation Likelihood of occurrence…

27 Other environmental information  Soil  Hydrology  Vegetation  Prevailing winds  Day length  Species interactions Likelihood of occurrence…

28 Cultural practices or Control measures  Would existing practices mitigate risk?  Are there any pest control programs or natural enemies already in the area of concern? Likelihood of occurrence…

29 Probability of Spread  Means of spread  How?  Rate of spread  How fast?  Magnitude of spread  How far? CFIA-ACIA Likelihood of occurrence…

30 Rate and Magnitude of Spread  Probability of spread influences  Scale of potential impacts  Urgency of potential responses  Survey design  Potential success of any future control or eradication program Likelihood of occurrence…

31  Suitability of environment  Biology of the pest  Presence of natural barriers  Intended end use of the commodity  Production / harvesting practices  Vectors  Natural enemies  History elsewhere Factors influencing spread Likelihood of occurrence…

32  Suitability of environment  Biology of the pest  Presence of natural barriers  Intended end use of the commodity  Vectors  Natural enemies  History elsewhere Factors influencing spread CFIA-ACIA Likelihood of occurrence…

33  Suitability of environment √  Biology of the pest  Presence of natural barriers  Intended end use of the commodity  Vectors  Natural enemies  History elsewhere Factors influencing spread CFIA-ACIA Likelihood of occurrence…

34  Suitability of environment √  Biology of the pest √  Presence of natural barriers  Intended end use of the commodity  Vectors  Natural enemies  History elsewhere Factors influencing spread CFIA-ACIA Likelihood of occurrence…

35  Suitability of environment √  Biology of the pest √  Presence of natural barriers √  Intended end use of the commodity  Vectors  Natural enemies  History elsewhere Factors influencing spread CFIA-ACIA Likelihood of occurrence…

36  Suitability of environment √  Biology of the pest √  Presence of natural barriers √  Intended end use of the commodity  Vectors  Natural enemies  History elsewhere Factors influencing spread CFIA-ACIA Likelihood of occurrence…

37  Suitability of environment √  Biology of the pest √  Presence of natural barriers √  Intended end use of the commodity √  Vectors  Natural enemies √  History elsewhere Factors influencing spread CFIA-ACIA Likelihood of occurrence…

38 Using the Gypsy Moth experience to predict behaviour of other species  Predicting spread of related or similar organisms  Species X is expected to behave much as did Gypsy moth, e.g., another Lymantria species such as nun moth  Comparison with dissimilar organisms  Species Y will spread faster & further than Gypsy moth, e.g., a rust of field crops  Species Z will spread more slowly & less far than Gypsy moth, e.g., a root-feeding nematode Likelihood of occurrence…

39  Looking back is easy  Understand why spread occurred as it did  Pest risk assessment looks forward  Much more challenging Likelihood of occurrence…

40  Comparative analysis  qualitative  Predictive Models  semi-quantitative or quantitative  Useful information sources  Case histories of comparable pests  Assessments and information from areas where the pest is present  Life history information  Site information  Expert opinion How to assess spread Likelihood of occurrence…

41  Model Types  Spatial or temporal models  Quantitative or qualitative models  Selecting a model  Fit for purpose  Scale & time are important  Challenges  Subjectivity in selection of parameters  Lack of or contradictory data  Difficult to validate Spread Models Likelihood of occurrence…

42 Spread Potential  Means of spread  How?  Rate of spread  How fast?  Magnitude of spread  How far?  Life history  Area of origin factors  PRA Area factors  Human factors  Compare to other pests  Compare to other places CFIA-ACIA Likelihood of occurrence…

43 Assessing potential economic impact  Determine pest impact in regions where pest occurs already  note whether the pest causes major, minor or no damage  whether the pest causes damage frequently or infrequently  relate this, if possible, to biotic and abiotic effects Consequences…

44 Assessing potential economic impact  Use information from where pest occurs and compare with that in the PRA area  Assess potential for economic importance  Qualitative, expert judgement  Quantitative, biological & economic techniques/ models Consequences…

45 Identifying pest effects  Direct effects  Longevity, viability of host plants  Yield, quality  Indirect effects  Market effects, environmental effects and social effects Consequences…

46 Direct pest effects  Value of the known or potential host plants in RA area  Types, amount and frequency of damage reported in areas where pest is present  Losses reported in areas where pest is present  Biotic factors affecting damage and losses Consequences…

47 Direct pest effects  Abiotic factors affecting damage and losses  Rate of spread  Rate of reproduction  Control measures, their efficacy and cost  Effect of existing production practices  Environmental effects Consequences…

48 Indirect pest effects  Effects on domestic and export markets, including effects on export market access  Changes to producer costs or input demands  Changes to domestic or foreign consumer demand for a product resulting from quality changes  Environmental and other undesired effect of control measures Consequences…

49 Indirect pest effects  Capacity to act as a vector for other pests  Feasibility and cost of eradication and containment  Resources needed for additional research and advice  Environmental effects  Social and other effects Consequences…

50 Economic impact matrix Market ImpactsNon-Market Impacts Direct Pest Effects  Commercial crops  Timber products  Control costs  Urban ornamental  Wildlife habitat Indirect Pest Effects  Trade  Tourism  Nutrient cycle  Hydrology Consequences…

51 Analysis of economic consequences  Time and place factors  Analysis of commercial consequences  Environmental and social consequences Consequences…

52 Time and place factors  Economic consequences are expressed over a period of time - possible lag between establishment and expression of consequences  Consequences can change over time  Distribution of pest occurrences  The rate and manner of spread  May use expert judgment and estimations Consequences…

53 Impacts over time Consequences…

54 Analysis of commercial consequences  Important to consider effect of pest-induced changes on:  Producer profits resulting from changes in production costs, yields and prices  Crop losses or crop failure resulting in loss of customers  Quantities demanded or prices paid for commodities by domestic and international customers Consequences…

55 Environmental impacts  Direct environmental effects  Loss of keystone species  Loss of threatened/endangered species  Decrease in range/viability of keystone species  Decrease in range/viability of threatened/endangered species Consequences…

56 Environmental impacts  Indirect environmental effects  Changes in habitat composition  Loss of habitat or nourishment for wildlife  Changes in soil structure or water table  Changes in ecosystem processes  Impacts of risk management options Consequences…

57 Environmental impact: tree death CFIA-ACIA Consequences…

58 Social consequences  Social effects  Loss of employment  Migration  Reduction in property values  Loss of tourism  Reduction or loss of availability of traditional plants for cultural purposes  Human health risks Consequences…

59 Challenges INFORMATION  Resources  Biological data  Financial & Economic data  Tools  Biological models  Financial & Economic models TECHNIQUES  Economists & biologists working together  Assessing impacts with little information  Quantifying environmental impacts  Scaling up from local to national impacts  Modelling changes in impacts over time Consequences…

60 Risk Assessment

61 Case studies’ experience…  Exceeds threshold?

62 Risk Assessment

63 Evidence: Knowledge Synthesis  Review of published research  Data on status of pest in area & other areas  Historic data  Expert opinion

64 Expert Opinion

65 Case studies’ experience…  Knowledge synthesis

66 Risk Assessment

67 Case studies’ experience…  Quantification -- ESBW  Setting up the SBW DSS in Quebec  UAF 09-751  Quantify scenarios for ESBW  Explore the utility of the DSS for MRNQ

68

69 A A A AB C D B B B B C C C C D D D D D D DD D D D

70

71

72 UAF 097-51 12 3 4

73 Informing the RA  Likelihood of occurrence  Magnitude of effects (consequences)  `Relative` effects for alternative scenarios  Response strategies  Alter expected defoliation  Alter species, age, etc. of stands Quantifying the risk…

74 Risk Assessment

75 Uncertainty  Uncertainty is inherent to risk analysis for pests  Using historical data to predict the future  Using data from one area to predict behaviour in another  Complete information is rarely available

76 Uncertainty  Identifying uncertainty  Reducing uncertainty  Documenting uncertainty

77 Identifying uncertainty  Sources of uncertainty include:  Incomplete data  Inconsistent or conflicting data  Imprecision or variability in data  Flaws in methodology  Subjective judgement  Lack of expertise

78 Sources of uncertainty  Data  Missing, inconsistent, conflicting, imprecise  Judgement  Subjective, time-limited, expertise-limited  Methodology  Undeveloped, untested, inconsistent, not repeatable, pathways not considered or described inappropriately  Other  Pest & human behaviour, random events, unexpected events, complexity of biological systems

79 Reducing uncertainty  Collect more data  Validate data with observations  Statistical analysis  Research  Use original sources  Expert consultation / peer review

80 Degree of uncertainty RatingUncertainty Very highLittle or no information – “Best guess” High Moderate Low Very lowExtensive, peer-reviewed information

81 Documenting uncertainty  Documenting uncertainty contributes to transparency  Define terms  Describe all plausible scenarios  State assumptions  Use your judgement  Experience brings confidence

82 Uncertainty table ElementRankUncertainty Probability of EntryHighLow Probability of Establishment Probability of Spread Direct ConsequencesLowHigh Indirect Consequences Overall Risk

83 Conclusion  Uncertainty is an inherent part risk analysis  Documenting uncertainties and assumptions in RA is a part of being transparent

84 Case studies’ experience…  Uncertainty

85 Risk Assessment

86 Overall assessment of risk  Combines the likelihood of pest introduction with the consequences of that introduction  “Without any mitigation measures, the pest is likely to be present on (host) from (origin) and to be able to survive transport and reach suitable hosts such as …. which are widely distributed in the PRA area”

87 Overall assessment of risk  Combines the likelihood of pest introduction with the consequences of that introduction  “Without any mitigation measures, the pest is likely to be present on (host) from (origin) and to be able to survive transport and reach suitable hosts such as …. which are widely distributed in the PRA area and could cause yield losses of up to 15% during a severe outbreak”

88 Overall assessment of risk  “Although the pest can spread (be introduced – enter and establish) from neighbouring country ….. impacts are likely to be very low”  Improvement

89 Overall assessment of risk  “Although the pest can spread (be introduced – enter and establish) from neighbouring country ….. impacts are likely to be very low”  Improvement  “Although the pest is very likely to spread (be introduced – enter and establish) from neighbouring country ….. impacts are likely be very low”

90 Overall assessment of risk  Summarise using words  Advantages  Disadvantages  Alternative approach?

91 Summarizing aspects of the assessment  Word scale  Likelihood  Very unlikely  Unlikely  Likely  Very likely

92 Summarizing aspects of the assessment  Word scale  Impact  Negligible  Low  Medium  High

93 Risk matrix High Medium Low Negligible LowMediumHigh Likelihood of introduction Impact

94 Risk matrix High Medium Low Negligible LowMediumHigh Likelihood of introduction Impact

95 Summary  Part of the pest risk assessment process  Qualitative descriptions - free text  Qualitative descriptions – word scales  Summarising aspects of risk assessment  Combining likelihood and impact  Summarising the summary!  Characterizing the risk

96 Risk Assessment

97 RA Framework


Download ppt "RA Framework. Risk Assessment ‘Area of concern’…  Every risk assessment has a geographic dimension  You need to explicitly identify the geographic."

Similar presentations


Ads by Google