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Learning to escape robotic spiders: predator
avoidance learning in bumblebees
Tom Ings & Lars Chittka
Outline
• Challenges facing bees
– Finding food BUT avoiding predators
• Colour change in spiders
• Impact of crab spiders on bees
• Dynamics of predator avoidance
– Avoidance learning paradigm
– Predator crypsis, learning & memory
Finding food
• Complex landscapes – too much choice!
Avoiding predators - invertebratesSit-and-wait ambush predators
Misumena vatia – colour change
Yellow White
Aims
• Does predator crypsis disrupt avoidance learning?
• Quantify dynamics of predator avoidance learning – bumblebees
• Does the foraging behaviour of bees alter in response to predation risk?
Time
Avoid
ance Attack
Effects of crab spiders on bees & plants
• Consumptive – reduce density & visitation
– Most (>90%) attacks unsuccessful (ample opportunity to learn)
• Non-consumptive – FEAR
– Avoid flowers with dead bees & spiders
– Avoid flower patches with high densities of spiders (sometimes)
• Lower seed set when spiders present
e.g. Dukas (2001), Gonçalves-Souza et al (2008)
Avoidance learning paradigm
Meadow of artificial flowers
10 cm
100 cm
72 cm
72 cm
Avoidance learning paradigm
“Safe” flowers
(trap inactive)
Trapping mechanism
“Dangerous”
flowers(active trap)
+
Life-sized 3D
spider model
“Robotic” spiders
Feeding
mechanism
Remotely
controlled
solenoid
Simulated predation attempts
Simulated predation attempts
2) Trap closed by
remote control
1) Bee lands to feed
3) Bee held for 2s
1) Learning to avoid predators in a single flower species meadow
vs
Questions
• Does spider crypsis affect avoidance learning & memory?
Hypotheses
• Bees are less accurate when spiders are cryptic
• Avoidance of spiders is well maintained
Design: avoidance learning
2 treatment groups
conspicuous
(16 bees)
cryptic
(16 bees)
Ings & Chittka (2008) Current Biology, 18
Colour vision in bees
• 3 colour receptors
Adapted from: Chittka & Brockmann (2005) PLoS Biology, 3
Wavelength (nm)
UV Blue Green
Rela
tive
sensitiv
ity
Colour differences: bee colour space
0.03 units
Blue
GreenUV
0.26 units
Bees can discriminate
0.1 units
Spider
Flower
Design: avoidance learning
• 25% chance of attack
• Learning curves
• Flight behaviour (3D video tracking)
2 treatment groups
conspicuous
(16 bees)
cryptic
(16 bees)
Ings & Chittka (2008) Current Biology, 18
Procedure
• pre-training (no spiders)
• learning (4 spiders & attacks)
• mid-term memory (spiders, no attacks)
• reinforcement (as training)
• overnight memory (spiders, no attacks)
0.00
0.05
0.10
0.15
0.20
0.25
25 50 75 100 125 150 175 200
Flower visit
Pro
po
rtio
n d
an
ge
rous f
low
ers
Accuracy: probability of attack
RandomLearning
0.00
0.05
0.10
0.15
0.20
0.25
25 50 75 100 125 150 175 200
Flower visit
Pro
po
rtio
n d
an
ge
rous f
low
ers
MM OR
Memory
Accuracy: probability of attack
Learning
Flight data: rejection of flowers
• Bee enters flower
zone
• Inspects flower
• Does not land &
feed
• Time in flower zone
Flower zone
Feeding zone
Flower zone
Feeding zone
0.4
0.5
0.6
0.7
0.8
0.9
1.0
1.1
1.2
25 50 75 100 125 150 175 200
Visit number
Du
ratio
n (
s)
Speed: rejection of dangerous flowers
Learning
MM OR
0.4
0.5
0.6
0.7
0.8
0.9
1.0
1.1
1.2
25 50 75 100 125 150 175 200
Visit number
Du
ratio
n (
s)
Speed: rejection of dangerous flowers
Learning Memory
‘False alarms’
P = 0.04
LearningN
um
be
r of
safe
flo
we
rs r
eje
cte
d MM(~15mins)
OM(~24hrs)
Summary: speed-accuracy trade-off
• Bees rapidly learn to avoid conspicuous & cryptic spiders
• Bees do not make more mistakes when spiders are cryptic
• Rejecting dangerous flowers takes longer if spiders are cryptic
• Bees reject more safe flowers when spiders are cryptic
• Reduced foraging efficiency
• Reduced fitness
• Cryptic spiders have no advantage - why use camouflage?
• How does flight behaviour change in response to spiders?
Conclusions