Tinbergen’s Four Questions Causation Ontogeny Survival value Evolution

Four questions in modern jargon Causation: neural, hormonal, perceptual and cognitive mechanisms mediating behavior Ontogeny: development and learning Survival value: adaptation and adaptive significance Evolution: historical patterns by which behavior evolve

Wilson’s view of Animal Behavior Ethology: taxonomic character (Lorenz), ritualization (Huxley), comparative studies (Tinbergen). Sociobiology: shifted emphasis away from 3 of 4 questions. We will concentrate on two of Tinbergen’s four questions: survival value (adaptation) and evolution (historical patterns). We will also consider the advantages of integrating all four questions.

Profound historical distinctions between early ethology and comparative psychology have been recently bridged by shared interest in communication and social behaviour, and research from physiology and applied areas. Although we reiterate the rise of sexual selection and mating behaviour as prominent areas of research, we also show that interest in mechanism and development has proven particularly resilient over the years.

Adaptations and Such Adaptive: An aspect of the phenotype that on average enhances the inclusive fitness. Adaptation: An aspect of the phenotype that has evolved to fill its current function. G.C. Williams: “adaptation is a special and onerous concept that should be used only where it is really necessary” (1966, Adaptation and Natural Selection, p 4)

Studying Adaptive Function The Behavior of Animals, Chs 1, 9, 13 Fit by design: The design of the animal matches its function so well, there is a strong argument for adaptation. Optimality: To what degree does behavior fit the predictions of a mechanism needed to fulfill a specific function. Game Theory: Do animals behave in a frequency-dependent manner to maximize fitness.

Fit by design

Orchid-Moth pollinator Darwin wrote a book on the “contrivances by which orchids are pollinated”. The Madagascar orchid, Angraecum sequipedale has an 11 inch long nectar receptacle. Darwin predicted a moth with a tongue that long. 40 years later the moth Xanthopan morgannii was discovered.

Bat Pollinators Many bat species pollinate flowers but there is no evidence of a match between bat morhphology and flower parts. Anoura fistulata is a glossophagine bat in the Andes of Ecuador Nature, 2006, 444, 701.

Bat Pollinators Many bat species pollinate flowers but there is no evidence of a match between bat morhphology and flower parts. Anoura fistulata is a glossophagine bat in the Andes of Ecuador Nature, 2006, 444, 701. Do flowers evolve to enhance bat detections? Nature 1999, 398, 759.

Glossophaga commissarisi Mucunaholtonii

Is the vexillum a signal to the bats?

When the vexillum is covered with a plastic bag the flower is less likely to be pollinates (evidenced by the exploded keel): 21% vs 88 %

Is it an odor, visual, or echolocation cue? Stuff vexillum with cotton, so it looks and smells the same but gives a different echo it is less likely to be fertilized: 17% vs 66%

Is it an odor, visual, or echolocation cue? Stuff vexillum with cotton, so it looks and smells the same but gives a different echo it is less likely to be fertilized: 17% vs 66%

The vexillum provides both a conspicuous signal and one that is directional. This is true if the echo hits the fronts of the vexillum or if it is rotated by 30 dgrees. Other congeners that are pollinated by megachiropterns do not have a raised and convex vexillum.

Optimal Foraging MacArthur & Pianka (1966) began optimal foraging theory with questions of how animals used resources in a patchy environment. One of first intros of animal behavior into ecology

Optimal Foraging: Building the Model Should an animal consume all prey items encountered or reject the less profitable? Step 1: Specify alternatives. After encounter with prey item X should it be consumed or searching continue? Step 2: Fitness currency or proxy. E/T.

Optimal Foraging: Building the Model Step 3: Specify constraints. –Energy (E) can only be acquired after a certain handling time (H) –Prey is encountered randomly during search (S) at some rate (λ) –Predator knows encounter rate, identifies prey without error, can not search and eat, search efficiency and speed remain constant

Testing the model: Step 1 Formulate Predictions Maximize E/T Compare specialist versus generalist, E 1 is more profitable For generalist: – E = S(λ 1 E 1 + λ 2 E 2 ) – T = S + S(λ 1 H 1 + λ 2 H 2 ) – E/T = S(λ 1 E 1 + λ 2 E 2 ) / S + S(λ 1 H 1 + λ 2 H 2 ) For specialist: E/T = Sλ 1 E 1 / S + Sλ 1 H 1

Testing the model: Step 1 Formulate Predictions Maximize E/T Compare specialist versus generalist, E 1 is more profitable For generalist: – E = S(λ 1 E 1 + λ 2 E 2 ) – T = S + S(λ 1 H 1 + λ 2 H 2 ) – E/T = S(λ 1 E 1 + λ 2 E 2 ) / S + S(λ 1 H 1 + λ 2 H 2 ) For specialist: E/T = Sλ 1 E 1 / S + Sλ 1 H 1

Be a specialist when E/T spec > E/T gen : Sλ 1 E 1 / S + Sλ 1 H 1 > S(λ 1 E 1 + λ 2 E 2 ) / S + S(λ 1 H 1 + λ 2 H 2 ) or (E 1 H 2 / E 2 ) - H1 > 1/λ 1 A specialist is favored when the encounter rate with prey 1 increases and thus 1/λ 1 gets smaller.

A generalist when: 1/λ 1 > (E 1 H 2 / E 2 ) - H 1 As the encounter rate with the more profitable prey decreases and thus 1/λ 1 becomes larger, generalists are favored. Relative abundance of prey does not affect choice, only encounter rate with more profitable prey. More abundant prey 1, more likely prey 2 gets dropped out of diet. Duration of search time (S) has no effect.

Testing the Model: Step 2 Experimentation Great tits could view meal worms of 2 sizes passing on a conveyer belt, λ with each prey is varied. Once a prey is taken, bird must fly to its perch to eat, could not handle and search at the same time. All H is the same.

Prey density and proportion of both the large (L) and small (S) prey are varied Equal λ, low densities predicts generalist foraging. > λ for L prey → specialist Maintain λ L increase λ S,, λ L = λ S → specialist Maintain λ L increase λ S,, λ S = 2λ L → specialist Relative prey abundance is unimportant, only the encounter rate with more profitable prey.

Prey density and proportion of both the large (L) and small (S) prey are varied Equal λ, low densities predicts generalist foraging. > λ for L prey → specialist Maintain λ L increase λ S,, λ L = λ S → specialist Maintain λ L increase λ S,, λ S = 2λ L → specialist Relative prey abundance is unimportant, only the encounter rate with more profitable prey.

Prey density and proportion of both the large (L) and small (S) prey are varied Equal λ, low densities predicts generalist foraging. > λ for L prey → specialist Maintain λ L increase λ S,, λ L = λ S → specialist Maintain λ L increase λ S,, λ S = 2λ L → specialist Relative prey abundance is unimportant, only the encounter rate with more profitable prey.

Prey density and proportion of both the large (L) and small (S) prey are varied Equal λ, low densities predicts generalist foraging. > λ for L prey → specialist Maintain λ L increase λ S,, λ L = λ S → specialist Maintain λ L increase λ S,, λ S = 2λ L → specialist Relative prey abundance is unimportant, only the encounter rate with more profitable prey.