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SNIFFER DOGS FOR SURVEY AND DETECTION OF INVASIVE WOOD BORING INSECTS: PRELIMINARY RESULTS WITH THE BROWN SPRUCE LONGHORN BEETLE ( TETROPIUM FUSCUM ). SIMON GADBOIS : DALHOUSIE UNIVERSITY, HALIFAX, NS, CANADA RENÉE LAPOINTE : SYLVAR TECHNOLOGIES, FREDERICTON, NB, CANADA
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SNIFFER DOGS FOR SURVEY AND DETECTION OF INVASIVE WOOD BORING INSECTS: PRELIMINARY RESULTS WITH THE BROWN SPRUCE LONGHORN BEETLE (TETROPIUM FUSCUM). • SIMON GADBOIS: DALHOUSIE UNIVERSITY, HALIFAX, NS, CANADA • RENÉE LAPOINTE: SYLVAR TECHNOLOGIES, FREDERICTON, NB, CANADA • JON SWEENEY: CANADIAN FOREST SERVICE, FREDERICTON, NB, CANADA • DAVE DAVIES: FOREST PROTECTION LIMITED, FREDERICTON, NB, CANADA
BACKGROUND • Wallner & Ellis (1976): Scientific study • USDA (Animal Plant Health Inspection Service): Asian Longhorn Beetle • Minnesota Department of Agriculture and Working Dogs for Conservation: Emerald Ashborer • New Hampshire Division of Forests and Lands & Matt Ayres (Dartmouth College): Emerald Ashborer
HOW IS THIS PROJECT DIFFERENT? • Winter detection of larvae: Challenges • SDT application (more later) • HOW IS THIS TEAM DIFFERENT? • Canid Behaviour Research Team: Integrative ethology (biology, experimental psychology, neuroscience) and applied research • Animal learning theory and psychophysics; olfaction • Non-profit • Investigating other model (biological) detection systems
TRAINABLE PROCESSES • Detection: T. fuscum • Discrimination: T. fuscum vs. T. cinnamopterum • Identification (matching-to-sample) • Scaling: Volume, concentration, quantity; threshold • Trailing • Tracking } SEARCHING
TIMELINE: ~2 VISITS/WEEK • Dog selection: 2 months • Clicker training: 1 week (1-2 visits) • Matching-to-sample (3 choices) ~ Tea: 1 month • Matching-to-sample (3 choices) ~ Larvae: 2-3 weeks • Matching-to-sample (9 choices) ~ Larvae, no distractors: 2-3 weeks • Matching-to-sample (9 choices) ~ Larvae, with distractors: 2-3 weeks • Matching-to-sample (16 choices) ~ Larvae, with distractors: 2 weeks • Go/no-go (9 choices): 1 week • Go/no-go (16 choices): 1 week • Go/no-go (25 choices): 1 week } DISTRACTORS: FIELD RELEVANT STIMULI
THE PROBLEM OF LOW SALIENCY STIMULI • 10 concentrations (in seconds [mins]): above • Plus: 50, 25, 12.5, 6.25% dilution (with water) of the 5s tea • S+ is the dilution, S- is water
Training • Tested ability to detect decreasing saliency stimuli 3 X 80%
Training • Tested ability to detect decreasing saliency stimuli 3 X 80%
Training • Tested ability to detect decreasing saliency stimuli 3 X 80%
Training • Tested ability to detect decreasing saliency stimuli 3 X 80%
Training • Tested ability to detect decreasing saliency stimuli 3 X 80% +
MATRICES AND BEYOND Criterion for moving to next step: 3 sessions in a row at 80% or 2 sessions in a row at 100% • Uncovered matrices: • 3x3: 1 target, 8 distractors • 4x4: 1 target, 15 distractors • 5x5: 1 target, 24 distractors • Training “no target”: Blank matrices >>> “sit” • Covered matrices: Test for SDT analysis • Transfer to bolts (3 choices): ongoing • Transfer to the field: Mid-February
SIGNAL DETECTION THEORY • Parameters: • d’ (d prime): measure • detectability • discriminability • Accuracy: sensitivity and specificity >>> ROC curves • Criterion or bias: C • Conservative (false alarm tolerant) vs. liberal (false alarm tolerant) dogs • Training can be adjusted
GO/NO-GO DETECTION FLYNN, FIRST 60 TRIALS (INCLUDING PRE-TEST TRIALS!) NOT FINAL! NOTE THAT THIS IS A CONSERVATIVE ESTIMATE OF PERFORMANCE CONSIDERING THAT IT INCLUDES TRAINING AND FAMILIARIZATION TRIALS
SDT: d’ AND C (CRITERION) • d’ calculation: • d' = z(False Alarms) - z(Hits) = 2.061 • (0 = chance, 4= perfect detection) • C value: • -0.023 >>> liberal decision maker • Maximizes hits at the expense of false alarms • THIS CAN BE FIXED WITH FURTHER TRAINING
UPDATE: FEBRUARY 5 • Note that on February 5, 2014, Flynn got: • 100% hits and 100% correct rejections • 0% false alarms and 0% misses • This puts him at a d’ above 4!
COST/BENEFIT ANALYSIS AND PROGRAM EVALUATION • Cost of dogs (acquisition, selection, training, etc.) • Human resources: Trainers and handlers • Commuting with canine teams • Considerations: • Remote scenting with dogs (from REST) • Other biological systems (differential conditioning)
THANK YOU TO THE “DAL CANINES” TEAM • Catherine Floyd, PhD candidate • Emma Hoffman, Honours student, lab experiments • Fielding Montgomery, Honours student, field experiments • Maria DeNicola, Research assistant and lab manager • http://www.gadbois.org/simon • https://www.facebook.com/groups/DalCanines/