Download Lecture 6 Economic decisions and the individual

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Extended Example: Bird Song Learning
1. Example: Bird Song Learning (Peter Marler)
2. White-crowned Sparrows – different regional dialects (Marin and
Berkeley)
3. Several possibilities for difference in song
a. Genetic differentiation
b. Is it cultural? Is song more like a meme?
White-crowned sparrows and Social Learning
Test 1
1. Took eggs from both populations and raised them in lab (no social
influences!)
2.At ~50 days young males made twittering song, only vaguely like the
adult’s song.
3.As they grew up, they kept singing but never developed the full
song.
4.This shows there has to be a social component.
White-crowned sparrows and Social Learning
Test 2
1. Reared birds with the tape recorded song of either Marin or
Berkeley (randomized)
2.These bird sang whatever song they were exposed to perfectly
3.Differences in dialect was not genetic, but instead cultural/memetic.
White-crowned sparrows and Social Learning
Test 3
1.Took young WC sparrows and played Song Sparrow song. (Song
Sparrow is a different, yet closely related, species to WC sparrow)
2.Young birds developed an aberrant song that resembled the song of
birds that had not heard a song.
3. Even though highly memetic, there is a genetic component that
constrains the songs they can learn.
4. If played both a Song Sparrow song and a White-crowned Sparrow
song, they always chose to learn species-specific song (their own
species song)!
White-crowned sparrows and Social Learning
Test 4
1. Exposed bird to a song during its critical period (10-50 days of age),
then deafened it.
2.Deafened birds could not develop the proper song.
3.At 150 days, males produce a subsong and try to match their own
vocal output to their memory. They needed to hear themselves sing.
White-crowned sparrows and Social Learning
Summary
1. Regional dialects are cultural and plastic.
2.Learning is needed: needed to learn song from other birds; needed
to learn how the song sounds as it was practiced.
3.Learning the species specific song is canalized (probably due to
natural selection).
Economic Decisions and the Individual
How much food to carry?
Which prey items are preferred?
Starvation and Predation risks
Tradeoffs
Cognitive abilities to forage
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Optimality Models
1. Usually based on trade-off between costs and benefits of behavior
a. Maximize benefits, minimize costs (B-C)
2. Test hypotheses by experimentally altering balance of trade-off or
compare species where balances differ
3. Most commonly used for foraging
a. But also for other behaviors where costs and benefits quantifiable
How best to forage for food?
1. Foraging is costly in time, energy, and exposure to
predators. Want to optimize it.
2. Problem: Resources typically distributed unevenly in
habitat.
3. Problem: Need to balance traveling and searching time
with how much food can be carried.
4. Marginal Value Theorem (Charnov 1976): model in which
animals try to maximize rate of energy gain
a. “Marginal value”: value of taking one more unit of
resource in patch
Modeling Foraging
1. Foraging typically represented by “diminishing returns”
a. Food runs out or prey start to hide.
2. “Loading curve” models energy gain vs. time.
3. Tangent=slope that maximizes food delivery
Modeling Foraging
1. Changing the travel time changes the optimal number of
prey to bring back.
2. Can use these models to generate explicit predictions
about foraging.
Foraging problem: How much to carry?
Starlings
1. Feed young Tipula fly larvae called “leatherjackets.”
2. Foraging is energetically costly. Up to 400 round trips per
DAY!
3. Problem: How many larvae to carry for each trip?
a. As mouth fills up, foraging becomes less efficient.
b. However, not efficient to return to the nest with very little
food.
Starling Foraging
1. Empirical evidence: Kacelnik 1984
2. Trained starling parents to collect mealworms from feeders
3. Mealworms dispensed at increasing intervals. This allowed
him to specify a loading curve of known shape.
a. The actual searching time of a bird would be difficult to
measure.
4. The birds would simply wait for the next worm to arrive until it
eventually flew back to its nest
5. He varied the distance of the wooden tray from between 8
and 600 meters from the bird’s nest to see how distance
influenced how long the bird stayed
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Starling Foraging
4. Starlings collected more mealworms when the foraging time
increased, as predicted.
5. Starlings appear to maximize the net rate of food delivery.
a. Understand the currency and constraints of their foraging.
b. A model based on maximizing energetic efficiency was not
predictive.
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Foraging in Bees
1. Bees often return to the hive with less than the maximum
load they could carry.
2. Bees don’t appear to be limited by how much nectar
they can hold in their crop.
3. They are limited by the weight of nectar, which add
energetic costs to flight.
4. The more the bee loads up, the more nectar will be used
as fuel before it gets home.
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Foraging in Bees
1. Schmid-Hempel et al. (1985) trained bees to fly to
artificial flowers, each with 0.6 mg of nectar.
2. He varied the distance between the flowers to
manipulate the cost of carrying the crop load of nectar.
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Foraging in Bees
3. Bees went home with smaller load when distance between
flowers was greater.
4. Bees maximize the currency of energetic efficiency, not the
net rate of energy delivery.
e=energy gained/energy expended
r=energy gained/time
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Why opposite pattern for starlings and bees?
1. Maximizing net rate is generally a good currency.
a. Strategy A: spend 1 kJ, gain 9kJ, forage 1 hr
b. Strategy B: spend 10 kJ, gain 90kJ, forage 1 hr
c. Both have efficiency = 9, but strategy B has 10x the net gain.
2. Energy efficiency may be particularly important if you have a fixed
amount of fuel.
3. In the case of bees, this may be the lifetime capacity for
expenditure of energy.
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Why opposite pattern for starlings and bees?
1. Schmid-Hempel and Wolf (1988) manipulated energy expenditure by
fixing different size weights onto bees
2. Bees that worked hardest lived shortest amount of time; lifetime
reduced from 10.8 to 7.5 days
3. Bees contribute more nectar overall to colony by maximizing
efficiency
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Prey Selection
1, Prey choice depends on energy value (E) and handling time (h).
2. Profitability (E/h) determines which prey to eat when multiple
types (species or different size classes) are available
3. For example, does ELarge/hLarge > ESmall/hSmall?
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Prey Selection
4. Shore crabs (Carcinus maenas) can easily break into small
mussels, but don’t gain much food. Very large mussels take so
long to crack open that they are not profitable in terms of energy
yield per unit breaking time.
5. Shore crabs prefer mussels with highest rate of energy return
when given a choice of different sized mussels.
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Predation risk
1. Foraging = short-term caloric gain; predation = permanent
death
a. Balance energy intake with need to remain vigilant
2. Can cause predictions based on optimality models to differ
from observations
3. Shift to less-preferred food when predation risk for
preferred habitats is high
a. But condition not static. Even high predation-risk
habitats can be preferred if pay-off is big enough
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Predation risk
1. Milinski and Heller (1978) examined if predation risk influences
choice of food intake in sticklebacks (Gastersteus aculeatus)
2. Hungry fish preferred high prey densities. However, when a
model kingfisher was flown over the tank, the fish moved to low prey
density.
3. Low prey density allows more time for vigilance
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Predation risk
1. Predation risk can also be age/size specific
2. Gilliam (1982) tested habitat preference as bluegill sunfish
(Lepomis macrochirus) grow
3. With no predators, fish foraged on benthic inverts which gave
highest rate of food intake compared to plankton
4. When predatory bass added to ponds smaller sunfish foraged
in reeds where food intake reduced by 1/3 and growth rate by
27%. Larger sunfish were safe and continued to forage in the
benthos.
5. Fish maximized chance of survival by adapting their foraging
strategy with age
Food storing
1. Many birds collect food in the autumn, which they then hide.
The food is retrieved during the winter and spring.
a. A single nutcracker is estimated to store 30000 seeds in
2500-4000 separate hiding places.
2. This helps them deal with environmental variability. Stored
food is similar to body fat. Both are stored during times of plenty
and used in times of scarcity.
3. Food storing requires spatial memory to retrieve the food.
a. Hippocampus is the part of the brain involved in spatial
memory.
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Food storing
4. Species that store food tend to have larger relative
hippocampal volumes than species that do not store food.
a. Light blue = average for families that do not store food.
b. Dark blue = average for familes that do store food.
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Food storing and the evolution of cognition
1. Mental abilities extend beyond spatial memory in some food storing
birds.
2. Nicky Clayton and colleagues tested this with Western scrub jays
(Aphelocoma californica).
3. Test1: Can the jays remember what kind of food stored, as well as
when and where (i.e. can they remember specific events)?
4. Experiment: Jays were allowed to store either nuts or worms and then
could store the other food after 120 hours. Food was retrieved 4 hours
later.
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Food storing and the evolution of cognition
5. Worms are preferred, but they go bad by 124 hours, whereas nuts
do not.
6. Birds retrieved the worms if they were stored second but not if they
were stored first.
a. Would do this even if the food was removed from the hiding place,
which eliminated any scent cues.
7. Thus, they can remember what, where, and when they hid food!
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Food storing and the evolution of cognition
1. Test 2: Can scrub jays interpret the knowledge of another
individual? Can they recognize potential thieves
2. When a bird was observed by others when storing food, it
would later on in private move the food cache to a new location.
3. Birds more likely to move food when observed by a dominant
individual than by their partner or subordinate
4. Individuals also more likely to move cache if they stole food
from others
Evolution of cognition
1. Test 3: Can Scrub jays plan for the future?
a. ‘Mental time travel’: ability to project into the future, independent
of current physiological conditions, and plan accordingly.
2. Experiment: Raby et al. (2007) placed birds overnight either in a
compartment where they received food first thing in the morning or in
a compartment where they had to wait 2 hours before receiving food
3. After training period, birds were allowed to obtain nuts from a
central room and store them. They preferentially stored them in the
room where they had to wait for food in the morning.
4. Birds could anticipate in which room they would be hungry if
locked in overnight!
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Optimality Models
Limitations
• What to do when an animal doesn’t behave
“optimally”?
•
Incorrect assumptions
• currency
• incomplete knowledge either by animal or by
scientist
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Summary
1. Optimality models are used to make quantitative, testable
predictions about the choices an animal makes that maximize the
benefits, while minimizing costs
a. The currency for maximum benefit and the constraints will
influence predictions
2. Foragers often face trade-offs in relation to foraging: predation
and/or starvation risk, handling time, etc
3. Foraging is a very important part of life and may lead to the
evolution of higher cognitive abilities.