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Testing the Australian WRA for reducing introduction of invasive plants to Florida Doria R. Gordon Associate Director of Science UF Professor of Botany UF Collaborators: Alison Fox Randall Stocker Daphne Onderdonk Thanks to: FDEP BIPM USDA APHIS PPQ FDACS DPI Lygodium microphyllum
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Why test a predictive tool in Florida? Our approach Modified Australian Weed Risk Assessment Data used Results Comparison to tests elsewhere Accuracy ROC Conclusions Outline Imperata cylindrica
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Number of Plants Imported through Miami International Airport Why a predictive tool for Florida? 57% of plant shipments, carrying 74% of all plants imported to the U.S., enter through Florida (2006)
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Hypothesis Accuracy in FL will be comparable to that for Australia, HI, and other geographies > 90% of invaders correctly identified > 75% of non-invaders correctly identified < 15% of species require further evaluation
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Florida Test Australian WRA with minor modifications to 3 questions for greater relevance to Florida’s climate Include Daehler et al. (2004) secondary screen for species requiring further evaluation
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Species List 158 non-native species in Florida 62 major invaders 31 invasive in natural areas (IFAS Assessment - Fox et al. 2005) 31 invasive in agricultural areas (SWSS lists) 48 minor invaders Documented in Florida’s flora but not as invasive 48 non-invasive – after > 50 years in FL Documented in cultivation but not in any flora Invaders and non-invaders paired by family and life form as possible Assessor had no knowledge of original category or species distribution in Florida
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Species breakdown Life form Non-invader Minor Invader Major invader Forb/herbaceous12 18 23 Graminoid 3 8 8 Shrub10 5 8 Subshrub 1 2 1 Vine 7 8 9 Tree15 7 13 Phylogeny Families35 27 36 Orders24 14 25 21% overlap across Families 59% overlap across Orders
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Results Sufficient data for all 158 species – 35 questions answered on average Natural area = agricultural weeds Scores not biased by plant family 4 question decision tree (Caley & Kuhnert 2006) correct for 100% of major invaders & 12% of non- invaders 91% of minor invaders rejected “Invader elsewhere?” correct for 92% of major invaders & 92% of non-invaders 67% of minor invaders rejected
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Evaluate Further Accept Reject Results Non-invader Minor invader Major invader
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Results 27% of species (42) in Evaluate Further category 10% of species (16) in Evaluate Further after using secondary screen (meets hypothesized < 15%) Non-invaders Minor Invaders Major invaders Accept11121 Reject011
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Results Using secondary screen No percentages significantly different than hypothesized Outcome Non- invader Minor invader Major invader Overall Accept73% (35)36%(17) 2%(1) Evaluate further19% (9) 6% (3) 6%(4)10% (16) Reject 8% (4)58%(28) 92%(57) Total number 48 62 158 Ardisia crenata
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Receiver Operating Characteristic Curve Minor and Major Invaders Combined Area not significantly different than when Minor and Non-invaders are combined (0.89) When Score = 3: 90% correct rejects 70% correct accepts Curve area = 0.91
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With secondary screen Evaluate further species removed from accuracy calculation Grouping minor and non-invaders as “Non-invader”: __________________________________________________________________ Actual: Non-invader Invader Total Likelihood of correct decision ________________________________________________________________________________________________________________________ Predicted: Accept52 1 53 98% (52/53) Evaluate12 4 16 Reject32 57 89 64% (57/89) Total96 62 158 Accuracy: Percent correct A & R outcomes: 62%98% (52/84) (57/58) __________________________________________________________________
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With secondary screen Evaluate further species removed from accuracy calculation Grouping minor and major invaders as “Invader”: __________________________________________________________________ Actual: Non-invader Invader Total Likelihood of correct decision ________________________________________________________________________________________________________________________ Predicted: Accept35 1853 66% (35/53) Evaluate 9 716 Reject 4 8589 96% (85/89) Total48 110 158 Accuracy: Percent correct A & R outcomes: 90%83% (35/39) (85/103) __________________________________________________________________
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Comparison to tests elsewhere * 82 - 100% Major Invaders rejected - NS 56 - 87% Non-invaders accepted CR > AU, HI, BI H & P > AU, HI 22 - 80% Minor invaders rejected BI > AU, CR 13 – 29% *8 – 11% Eval further **** * Used 2 o screen (Daehler et al. 2004)
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ROC Curves – Minor + Non CR area > all others Pheloung et al. 1999 Křivánek & Pyšek 2006 Kato et al. 2006 8 7 108
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ROC Curves –Minor + Major All curve areas equivalent Pheloung et al. 1999 Daehler & Carino 2000 Křivánek & Pyšek 2006 Kato et al. 2006 5 9 55 6
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Conclusions The WRA amended for conditions in Florida and with the secondary screen developed by Daehler et al. (2004) meets the three hypothesized accuracy standards: > 90% of invaders correctly rejected > 75% of non-invaders correctly accepted < 15% of species require further evaluation Results not significantly affected by: Natural areas vs. agricultural weeds Natural areas vs. agricultural weeds Families, life-form, life-history Families, life-form, life-history The WRA approach appears useful across variable geographies. Solanum viarum
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In Australia Implementation of the WRA between 1997 and 2006: 2,800 plant species proposed for introduction 53% accepted 20% need further evaluation 27% rejected (Riddle, pers com) WRA policy cost effective in 10 yrs and estimated to save Australia up to $1.8 billion over 50 years (Keller et al. 2006) Hydrilla verticillata
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How might the WRA be used at the state level? Work with the horticultural and landscape industries to voluntarily exclude likely invaders FL, CA, HI, OR and others have active efforts Identify species to be added to Noxious Weed and Invasive Plant lists But… Inclusion in revised Q-37 regulation is only way to create a national prevention mechanism Lantana camara
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Evaluate Further Accept Reject Consider moving thresholds Non-invader Minor invader Major invader
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