Tools, Technologies, and Transdisciplinary Science of Area-wide Management of Insects

Transcription

1 Tools, Technologies, and Transdisciplinary Science of Area-wide Management of Insects Nancy Schellhorn, Florian Schwarzmueller, Aditi Mankad CSIRO Agriculture & Food

2 Why are we here? SCIENCE PROTECTING PLANT HEALTH SCIPLANT 2017 is focused on facilitating engagement and the exchange of ideas between researchers and the end users of this research QLD Chief Scientist, Dr Geoff Garrett AO, 2

3 Why do I do what I do? WHY WHAT HOW TED Talk Simon Sinek, the golden circle Why do you do what you do?

4

5 Arthropods don t recognise borders!

6 Not unique to Arthropods! Natural resources & conservation water, birds Air pollution Natural disasters Zombies

7 Massive Challenge: Manage highly mobile, often invasive, arthropods 1. Need support from many stakeholders, the community and public; 2. Target landscapes are heterogeneous; 3. Delays in knowing where and when pest shows up

8 What we do (end goal): Area-wide Management (AWM) Features: a solution beyond the spatial scale of a field, integrates multiple pest control tactics, neighbours-to-neighbour participation, coordinated, may involve a regulatory framework

9 How we do it (the journey): Trans-disciplinary science to know who needs to do what Technologies to simulate pest management actions across multiple spatial and temporal scales Tools to help us know where & when

10 Outline: I. Setting the scene of area-wide management (AWM) II. Case studies to illuminate T,T, and T: i. Silverleaf whitefly, Bemisia tabaci (MEAM1) invasion into Australia AWM via classical biological control ii. QLD Fruit Fly, Bactrocera tryoni, range expansion into SE Australia Who needs to do what to facilitate AWM Where can AWM be most effective iii. QLD Fruit Fly, real-time monitoring III. Conclusion - value of early end-user engagement

11 Key message: Arthropods continue to challenge plant health Research has to: 1 st connect to the end user, and address simultaneously different parts of the problem to arrive at a solution

12 Outline: I. Setting the scene of area-wide management (AWM) II. Case studies to illuminate T,T and T: i. Silverleaf whitefly, Bemisia tabaci (MEAM1) invasion into Australia AWM via classical biological control ii. QLD Fruit Fly, Bactrocera tryoni, range expansion into SE Australia Who needs to do what to facilitate AWM Where can AWM be most effective iii. QLD Fruit Fly, real-time monitoring III. Conclusion - value of early end user engagement

13 Tool for AWM Sterile Insect Technique = mass-rearing and sterilization of a target pest, followed by the systematic area-wide release of the sterile males by air over defined areas Edward Knipling father of SIT Exploited the fact that screw worm mate only once 1 st success of eradication was in 1954 screw worm fly on the island of Curacao; many dozens of programs globally for Tsetse fly, codlling moth, fruit flies, etc..

14 Evidence of Success of Coordinated Actions of Many June January 2016 Levins, R Some demographic and genetic consequences of environmental heterogeneity for biological control. Bulletin of Entomological Society of America, 15: st define meta-populations; Distinguished b/t the dynamics of single populations and a set of local populations; Model motivated by- and applied to- a pest control situation over a large region, which local populations would fluctuate in asynchrony; Model showed that control measures should be applied synchronously throughout to achieve suppression

15 Evidence of AWM of pests by their Natural Enemies Reeve 1990 (theoretical) Ives and Settle 1997 (experimental & theoretical) Considered the 3 rd trophic level (natural enemies) and area wide suppression Both showed that the combination of asynchronous planting of crops and highly mobile natural enemies resulted in area wide suppression of pests

16 Examples of pest control applied at an area-wide basis Coordinated timing of insecticide (Smith 1998; Lloyd et al 2010) Coordinated growing of trap crops (Sequeira 2001) Coordinated control of weeds (Mueller et al 1984; Abel et al 2007) Wide scale deployment of genetically modified insect resistant crops (Carriere et al 2003, Hutchinson et al 2010)

17 Outline: I. Setting the scene of area-wide management (AWM) II. Case studies to illuminate T, T and T: i. Silverleaf whitefly, Bemisia tabaci (MEAM1) invasion into Australia AWM via classical biological control ii. QLD Fruit Fly, Bactrocera tryoni, range expansion into SE Australia Who needs to do what to facilitate AWM Where can AWM be most effective iii. QLD Fruit Fly, real-time monitoring III. Conclusion - value of early end user engagement

18 The Problem: Silverleaf whitefly, Bemisia tabaci, (MEAM1) I996 Poinsettias broad host range; Yield & quality; Transmits virus (begomoviruses TLCV, TYLCV)

19 The solution: Classical Biological Control -parasitoid Eretmocerus hayati Male Female Eretmocerus hayati - Aphelinidae Originated in Pakistan Attacks 1 st and 2 nd instar nymphs

20 Presentation title Presenter name Page 20

21 The solution: Insecticide use what type, how often? Type of insecticide used Least disruptive Bundaberg Insecticide use pattern Always use softer insecticide Use softer insecticide if possible Use the most cost effective insecticide Most disruptive Only if becoming Once on young 2-4 times weekly/fortnightly a problem crop throughout crop throughout crop Frequency of insecticide use

22 The solution: Crop rotations what type, how often? Vegetable J F M A M J J A S O N D Pumpkins Rockmelon Eggfruit Watermelon Potato Zucchini Sweet Potato Capsicum Snowpeas Cucumber Peanuts

23 The solution: How fast can it move, establish and spread? 3.8km Release field; 130,000 adults as pupae 3km 2km 1km 3 Scales: Small - 10s of meters Large - 100s of meters Landscape Kms (F1s only) km m

24 Travelling 1km / day 7 days PR max 32 m Kristensen, 24 De Barro, Schellhorn, 2013, Plos One Kristensen, Schellhorn, Hulthen, Howie, De Barro, 2013, Env Ent 7 days PR bi-modal; max 270,

25 10s of metres - Flying-only Kilometres - wind-only model 100s of metres Combination = wind & flying Kristensen, De Barro, Schellhorn, 2013, Plos One Kristensen, Schellhorn, Hulthen, Howie, De Barro, 2013, Env Ent

26 Field Guide -how to tell hayati -where to source hayati -the best crop rotations -what sprays to avoid -what sprays are compatible CSIRO.

27 introduction Lives 4.5 days longer Produces 3 xs more progeny % % Mean number 4th instars/cm sq % 50% 40% 30% 20% Jan-05 Feb-05 Apr-05 Mean % parasitism of 4th instars Aug-05 Nov-05 Jan-06 Apr-06 Dec-06 4th instars/cmsq % parasitism 10% 0% De Barro & Coombs, 2009, Bull Ent Res; Villanueva-Jimenez, Schellhorn and De Barro, 2012, Biological Control

28 Grower self assessment of their SLW problem Independent survey ~ 68 growers 10 Catastrophic problem Lockyer Whitefly problem 8 6 4? Significant reduction Down from near catastrophic 2 No problem Year

29 Summary Ex 1.: Problem Tool Grower Practices Technologies

30 Outline: I. Setting the scene of area-wide management (AWM) II. Case studies to illuminate T, T and T: i. Silverleaf whitefly, Bemisia tabaci (MEAM1) invasion into Australia AWM via classical biological control ii. QLD Fruit Fly, Bactrocera tryoni, range expansion into SE Australia Who needs to do what to facilitate AWM Where can AWM be most effective iii. QLD Fruit Fly, real-time monitoring III. Conclusion - value of early end user engagement 30

31 The Problem: Bactrocera tryoni, Queensland Fruit Fly (Qfly) #1 biosecurity barrier to trade of fruit & veg in Australia 31

32 32 Dominiak and Daniels 2012, Aus J Ent

33 Background: History of Fruit Fly Exclusion Zone 1994: Tri-State Fruit Fly Exclusion Zone ( FFEZ ) established 2007: Hard to maintain, area reduced (subset of FFEZ) Frequency of outbreaks continued to rise :Restrictions placed on use of fenthion + dimethoate 2012: Goulburn Valley declared endemic 2014: Suspended the Sunraysia PFA Export value AU$m (% of Australia s fresh horticultural exports) FFEZ South Australia $204.9 (13%) Victoria $793.8 (51%) 33 New South Wales $172.9 (11%)

34 The solution: Remove the market barriers to trade fruit & vegetables Area-wide Management & $5b fruit-fly susceptible fruit; export $500m 34 Port Augusta, South Australia

35 Socio-economic Adoption Bio-physical How? Adaptive AWM of Qfly using SIT Cost-effective AWM & SIT Regionally-focused programs for AWM & SIT IMPACT Uptake of AWM for Qfly and the ability to incorporate SIT fly Strategy to maximise uptake of AWM & SIT

36 Background 500 km 36

37 Setting the scene: Qfly status Goulburn Valley Endemic Major crops: stone fruit, apples, cherries, pears persistent and increasing outbreaks endemic status declared - Shifting from canning to fresh or value added produce Riverland Fruit Fly Pest Free Area Major crops: citrus, table grapes, stone fruit - State government conduct surveillance and response to fruit fly - Gov release SIT (Qfly + Medfly) Sunraysia Suspended PFA Major crops: citrus, table grapes, stone fruit GSPFA established to replace the FFEZ persistent + increasing outbreaks voluntary suspension of PFA

38 Area suitability to receive SIT = 1st reduce flies Best Management Practice (BMP) Protein bait: start early (4 weeks before ripening) apply weekly until 3 weeks after harvest Male annihilation: place MATs in orchards (10-20 per ha) apply three times a year leave out all year Sanitation: remove all unpicked or fallen fruit after harvest

39 Social challenges and constraints to AWM and possible use of SIT Solution: What are the factors that will allow people to work together? Aditi Mankad CSIRO 39

40 Solution: The main factors for the acceptance of AWM was perception of fairness Fairness Compatibility Acceptance of AWM Complexity of AWM Observability of AWM outcomes Relative advantage of AWM

41 Solution: Self-efficacy and team spirit most important factors contributing to the intention of implementing AWM Self-efficacy re AWM Team Spirit Knowledge of Qfly controls Intention to implement AWM: Threat context Threat severity of Qfly Age Intention to implement AWM: Social context Personal responsibility Vulnerability to Qfly Efficacy of AWM Willingness to cooperate What do others think about AWM?

42 What are the landscape factors that will make AWM and SIT feasible? 42

43 Spatially explicit population model Ecology and behaviour of Qfly (reproduction, mortality, movement), Florian Schwarzmueller, CSIRO Host data (seasonality, quality, distribution) complex landscapes 43

44 no. patches with flies log10 (population density [1/m²]) Citrus Grapes Vegetables Summer- Citrus Stone Fruit - Example - other Fruit Trees Pome Fruit minor hosts Structures Urban natural Vegetation other Trees other water time Population dynamics follow fruit availability peaks at the end of Stonefruit/Grapes season (high quality crops) Field Crop number of affected properties peaks later (flies searching for resources)

45 Simulate Management Scenarios Best Management Practice (BMP) protein bait: start early (4 weeks before ripening) apply weekly until 3 weeks after harvest Male annihilation: place MATs in orchards (10-20 per ha) apply three times a year leave out all year Sanitation: remove all unpicked or fallen fruit after harvest - 60% of farms adopt BMP -

46 no. patches with flies frequency log10 (population density [1/m²]) Effectiveness affected area time time fly density per patch

47 no. patches with flies frequency log10 (population density [1/m²]) managed unmanaged Example high low log10 (population density per patch [1/m²]) time

48 frequency frequency Feasability Citrus, vegetables, Trees log10 (population density per patch [1/m²]) Table grapes & Urban log10 (population density per patch [1/m²])

49 Pest pressure Effect of implementing AWM and SIT Business as usual Implement AWM Implement SIT Maintenance 49

50 Trajectory for success social + biophysical get growers engaged in BMP social: self-efficacy; make sure they know what to do Citrus, vegetables, Trees Table grapes & Urban get both residents & growers involved; options of urban treatment social: perception of fairness; people experiencing problem is different that people affected by the problem e.g., Swan Hill, town given traps; buying into the solution, solved buying into the problem

51 Summary Ex 2.: Problem Tool Trans-disciplinary Technologies BMP SIT -solution needs to be flexible to appeal to people with different motivations & challenges

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53 Outline: I. Setting the scene of area-wide management (AWM) II. Case studies to illuminate T, T and T: i. Silverleaf whitefly, Bemisia tabaci (MEAM1) invasion into Australia AWM via classical biological control ii. QLD Fruit Fly, Bactrocera tryoni, range expansion into SE Australia Who needs to do what to facilitate AWM Where can AWM be most effective iii. QLD Fruit Fly, real-time monitoring III. Conclusion - value of early end user engagement 53

54 Problem: Inability to know in real-time the presence and location of arthropod pests Greatest barriers to better border security and sustainable food production

55 Global fruit & veg Threatened: $US18b Lost: $US30b

56 Millions of traps are checked manually RapidAIM

57 South Australia, AUSTRALIA 2000 traps RapidAIM

58 IoT We believe in making agriculture SMART

59 A New Era Presentation title Presenter name 59

60 RapidAIM Unique Sensors Behavioral fingerprint

61 Fruit Fly Alert! IoT

62 RapidAIM generates value to end users by: Real-time alert for rapid response = less damaged fruit Improved workflow = 8 fold reduction in labour Early warning of future FF hot spots = keeps trade flowing

63 Completed a semi-commercial trial Shepparton, VIC Feb April rapidaim traps;40 manual traps 15 Growers; 26 properties All growers had alert dashboard on their phones What they liked, what they wanted to change

64 GENERAL RESULTS Traps communicate to gateway from 3.5Km IoT LoRaWAN each gateway ~ 50 km 2 2 lithium ion batteries, lasting 9 months Peak season Empty traps = 44%; Traps with flies = 56% Time is wasted checking traps Further reduce time checking traps, only visit to change lures, and general maintenance

65 Value of end user engagement - Low power, high quality images of fruit fly sent as alert to an end user; Patented technology; Out of the building, engaged with end users (those wanting better fruit fly monitoring) We learned: Only need to know if a fruit fly has arrived in the trap; Don t need an image; Allowed us to develop new technology Low cost, low power

66 - Enabling the global trade of fruit and veg IoT We believe in making agriculture SMART

67 Re-cap Scope and historical context of AWM Challenge of AWM people, mobile arthropods, and heterogeneous landscapes Case studies from Silverleaf whitefly and QLD Fruit Fly tools (classical biological control & novel sensors for real-time monitoring), technologies (analytical and simulation modelling); and transdisciplinary science (social & biophysical scientists; engineers (hardware, software, cloud) & insect ecologists and socio-economics.

68 Conclusions Make your great science count! Collect baseline information on the extent of the problem at the beginning Outcome: Demonstrate the impact of the research Involve your end users at the beginning Outcome: Better hypotheses, and generate information that can affect change Consider a trans-disciplinary approach to problem solving Include multiple disciplines from the beginning to simultaneously address many parts of the problem Outcome: Pathway to impact can happen faster (social-ecological networks; social network has to match the biophysical network to make progress)

69 SLW Example: Acknowledge and thank growers, funders, and collaborators

70 Fruit fly simulation modelling and social science example: Acknowledge Hazel Parry, Penny Measham, and the wider team, growers, and community stakeholders! The Adaptive area wide management of Qfly using SIT research project is supported by Horticulture Innovation Australia and CSIRO, through funding from the Australian Government Department of Agriculture and Water Resources, Rural R&D for Profit Programme..

71 Acknowledge the RapidAIM Team, ON Program, & CSIRO for funding! Laura Jones Stephen Brosnan Les Overs Anna Marcora Xiaobei Wang Tim Pitman Ben Barnes Dave Factor Leader in Economics Ryan McAllister Ground breaking tech & software engineering Darren Moore THANK YOU!