Slide 1: Title
Slide 2: Outline
Why worry about biological invasions
- Options for managing invasions
- Power of biological control
- Peril of biological control
Slide 3: Future directions for improving management of invaders and the effectiveness and safety of biological control
- Why worry about invasive species
- Second to habitat loss as threat to biodiversity
- Many totally alter ecosystem structure and function…and the ecosystem services that we derive from them
- Recall is often not possible and control may be difficult
- Many cause enormous economic damage ($137 billion/yr)
- Problem will get worse
Slide 4: How to manage risk of invasions
- Predict and Prevent Entry
- Detect Early and Eradicate
- Mitigate using chemical, mechanical, cultural, biological control methods
- Active and passive restoration of ecosystems
- Education and Outreach
Slide 5: 1. Predict and Prevent Entry
- Noxious Weed Lists - What are the Causes and Consequences of Wide Variation in State Noxious Weed Lists?
Sales of living plants create wealth, but some nonindigenous plants cause harm
Similarity in environmental and agronomic characteristics helps explain dissimilarity in weed lists
Stakeholders play a significant role in shaping weed regulations
Seed industry’s lobby favors more uniform regulations among states
- Min, Gopinath, Buccola, McEvoy 2008 Land Economics 84:306-326 - Weed Risk Assessment –
Is risk assessment (RA) worthwhile given low base rate (i.e. only a small fraction of introduced species cause harm) and low accuracy of prediction?
- Keller, Lodge, and Finnoff 2007 Risk assessment for invasive species produces net bioeconomic benefits PNAS 104: 203-207 - Do voluntary codes of best practices provide adequate protection?
Slide 6: Wide Variation in State Noxious Weed Lists
- Reflects ecological and agronomic characteristics and stakeholder lobbying through political contributions
Slide 7: Contribution of Horticulture to the Problem
Working list of horticultural plants that have become invasive in Oregon
- Alliaria petiolata (garlic mustard)
- Lythrum salicaria (purple loosestrife)
- Buddleja davidii (butterfly bush)
- Hedera helix (English ivy)
- Clematis vitalba (traveler’s joy)
- Ailanthus altissima (tree of heaven)
- Myriophyllum aquaticum (parrot feather)
- Centaurea cyanus (bachelor’s button)
- Polygonum cuspidatum (Japanese knotweed), P. sachalinense (giant knotweed) and P. polystichum
- Himalayan knotweed) for their impact on riparian areas
- Euapatorium capillifolium (small dogfennel)
- Eichhornia crassipes (water hyacinth)
- Iris pseudacorus (yellow flag iris)
Slide 8: 2. Detect Early and Eradicate
Images by Tom Forney, ODA
Slide 9: One that got away ….our own home-grown invader
- Brachypodium sylvaticum (Huds.)
- P. Beauv.
- slender false brome
Slide 10: http://www.willamettegardens.com/
Slide 11: 3. Mitigating Invasions
Classical Biological Control
Not a panacea, Not risk-free
Slide 12: Biological Control Technology
Using Biodiversity to Protect Biodiversity
- Oregon ~75% of national BC portfolio
- 30 target organisms
- 70 control organisms
- USA
- 39 target plants
- 94 control organisms
Slide 13: Selecting targets by ranking their impacts
I = A x D x PCE
Impact ( I ) is a function of
- A = Abundance
- D = Distribution
- PCE = Per Capita (Per Unit Biomass) Effect
Slide 14: Invader abundance goes up….
Diversity (and ecosystem services) go down
Slide 15: Purple loosestrife and introduced biological control agents
Slide 16: Leaf Beetle Damage
Slide 17: Transient dynamics revealed by the purple loosestrife system (Before)
- Biological control resembles an invasion process
- Releasing and Establishing Control Organisms
- Increasing and Redistributing Control Organisms
- Damaging and Suppressing the Target Organism
- Managing Plant Succession
- Ecology can guide development of biological control step-by-step
Slide 18: Transient dynamics revealed by the purple loosestrife system (after)
Slide 19: The Power of Biological ControlMathematics of Spread
- Spread combines two processes, population growth and population redistribution (movement)
- Simplest model assumes exponential increase and random diffusion
- Requires estimates of two parameters, the intrinsic rate of increase α, and the diffusion coefficient D
Slide 20: Fisher-Skellam TheoryGrowth and Diffusion Equation
∂Ν ⌈∂2Ν ∂2Ν⌉
∂t = ƒ(Ν)+D ⌊∂x2 + ∂y2⌋
Slide 21: Asymptotic Rate of Spread
VF = √
4αD
For large time, the velocity (distance/time) VF for the advancing front approaches an asymptotic rate of spread, which depends on the intrinsic rate of increase and the coefficient of diffusion D. The radius of a species range should asymptotically increase linearly with time with slope √(4αD)
Slide 22: Autonomous Spread within a Watershed estimated by mapping at Morgan Lake (area occupied by insect in red, host plant in green)
Slide 23: Exponential Growth Rate α = 2.24 / yr
Rate of increase of insects positively correlated with rate of increase in damage during the exponential phase of population growth
So damage can be used as surrogate for insect density and a measure of ‘effective density’
…and furthermore it is easier to measure
α= 2.24 corresponds to ~10-fold increase in population each year
exp(α) =Nt+1/Nt = λ
Slide 24: Reported values of α
Slide 25: Movement Rate D calculated from equation for Asymptotic Radial Spread Rate (ASR)
C = 2 (α⋅D)1/2
Slide 26: (chart) Reported Values of D
Slide 27: (chart) Geographic Variation in Parameters Assuming C = 2 (α⋅D)1/2
Slide 28: (chart) Match between theory (line) and observation (circles)
Slide 29: (map) Anthropogenic Spread
Slide 30: (chart) Damage Translates into Decline in Loosestrife Population (Biomass) at Baskett Slough
Slide 31: Biological Control is Subject to ‘Revenge Effects’
- Scarce resources are diverted from more profitable alternatives for managing pests,
- One control organism undermines another, more effective control organism, leading to increase in pest density,
- One pest is replaced by another pest that can be even harder to control,
- Control organisms introduced to promote environmental and economic health end up undermining it by harming non-target organisms.
Slide 32: Biological control of St. JohnswortHypericum perforatum (Clusiaceae)
Slide 33: (photo) St. Johnswort
Beetle Monument
“In appreciation of the combined efforts of farm advisor Douglas Pine, Dr. A.W. Sampson, Harry S. Smith University of California and the Entomology Research Division, USDA for their work which led to the introduction of the Klamath weed beetle for the eradication of Klamath weed from our range lands”
Humbolt County Cattlemen’s Association and others
Slide 34: A weed becomes a crop
‘Listening to St. Johnswort’?
St Johnswort has become a naturopathic alternative to Prozac
Slide 35: Host SpecificityPredicting Risk to Native Plants in Weed Biocontrol (Pemberton 2000 Oecologia 125: 489-494)
Examined field host use of 117 organisms established for biological control of weeds from 1902 - 1996
- Taxonomic groups: 112 insects, 3 fungi, 1 mite, and 1 nematode
- Geographic areas: Hawaii, the continental USA, and the Caribbean
Slide 36: Main Conclusions
- Risk is borne almost entirely by native plant species that are closely related (same genus or closely related genus) to target weeds
- Taxonomically related hosts. 15 spp bc insects use 41 native plant species
- 36 of 41 natives are congeneric with target weeds
- 4 others belong to two closely allied genera
- ‘use’ does not equal ‘population suppression’
- Taxonomically unrelated hosts. Only 1 (a tingid bug Teleonemia scrupulosa ) of 117 established biological control organisms uses native plants unrelated to the target weed.
Slide 37: Elements of Safetyfor Protecting Native Plants:
how to practice BC without triggering an invasion
- Selecting the right environment : select weed targets that have few or no native congeners in recipient environment
- Selecting the right organism : introduce biological control organisms with suitably narrow diets
Slide 38: (photos) A Model SystemRagwort and introduced biological control organisms
Slide 39: (chart) Observational studies: Decline of Ragwort in Western OR
Slide 40: Combining models and field experiments - Equilibrium and transient dynamics revealed by the ragwort system
Activation-Inhibition hypothesis
- Short-range activation due to seed source and local disturbance
- Long-range inhibition due to herbivory and plant competition
- Stability due to balance in activation and inhibition
Parsimonious prescription for effective control using fewer control organisms using
- Critical attributes of successful control organisms
- Targeted-disruption of pest life cycles
- Combinatorial ecology of ‘top-down’ and ‘bottom-up’ forces in food webs
McEvoy and Coombs 1999. Ecol. Appl.
Slide 41: (chart) Combinatorial Ecology of Biological Weed Control
Slide 42: Safety of Biological Control Introductions
What is the risk to nontarget organisms?
Biological control organisms share attributes of some our worst invaders – capacity to harm, multiply, spread, evolve
(Photo: Cinnabar moth caterpillar feeding on non-target species Senecio triangularis)
Slide 43: The cinnabar moth is a flawed biological control organism
- it is less effective than alternatives (such as the ragwort flea beetle Longitarsus jacobaeae) for controlling ragwort Senecio jacobaea (McEvoy et al. 1993, McEvoy and Coombs 1999)
- it eats non-target plant species (including Senecio triangularis, a native North American wildflower) (Diehl and McEvoy 1990)
- it carries a disease (caused by a host-specific microsporidian Nosema tyriae) (Bucher and Harris 1961, Hawkes 1973, Canning et al. 1999)
Slide 44: Can a pathogen provide insurance against host shifts by a biological control organism?
McEvoy, Karacetin, Bruck 2008. Proc IX Intl Sym BC Weeds
Slide 45: Conclusions and Future DirectionsManaging Invasive Species
- Their role in society – our examination of weed lists illustrates how human activities, attitudes, beliefs, political and economic interests contribute to invasions – a prelude to reform
- Their role in nature – our measures of environmental impact help us prioritize which invasive species to manage – an invitation for wider application of these measures
- Their role in food webs - biological control systems are embedded in a web of interactions
- Linking the structure and dynamics of ecological systems (populations, communities, ecosystems)
Designing more effective and safer management interventions
For more information about this presentation, contact:
mcevoyp@science.oregonstate.edu
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Last updated: May 29, 2007