Announcements:-- For lecture next week, read Chapters 6 and 7 (now 1-7).-- For lab this week, read Chapter 9 (Using the Library and

Scientific Literature)

-- ALSO, for the lab, read the paper posted on the website by Erichsen, Krebs, and Houston (1980).

This paper tests the modelI presented last week, using . . . Great Tits on a conveyorBelt. (Get over the silly name).It will be discussed in the labs this week!

Lots of talks this week:

Wednesday, January 21, 4:00 pm, 208 BIO—SPECIAL ECOLOGY AND EVOLUTION SEMINAR, "Climate change and coral reef resilience: are we expecting too much from marine reserves?," Dr. John F. Bruno, University of North Carolina, Chapel Hill

Thursday, January 22, 7:00 pm, FSU Coastal and Marine Laboratory Auditorium, St. Teresa, Florida—COASTAL AND MARINE CONSERVATION LECTURE, "Florida's coral reefs: threats, decline, management, and signs of hope," Dr. John F. Bruno, University of North Carolina, Chapel Hill. Refreshments will be provided.

Friday, January 23, 2:00 pm, 327 OSB—BIOLOGICAL OCEANOGRAPHY SEMINAR, "Sticking with simplicity: facile regeneration, versatile morphology, and diverse collaborations promote persistence of the most basal metazoans," Dr. Janie L. Wulff, Department of Biological Science, FSU

Friday, January 23, 4:00 pm, 1024 KIN—ECOLOGY AND EVOLUTION SEMINAR, "Context-dependent streak spawning in a simultaneous hermaphrodite, Serranus subligarius,” Mia Adriani, Department of Biological Science, FSU.

I. Purpose of this CourseII. The Scientific MethodIII. What are Foragers?IV. Decision Making by Foragers

A. Types of decisionsB. Balancing Costs and Benefits in DecisionsC. Optimal Diet Model

Ei/hi > E/(s+h)

Optimal diet model would predict that as prey become more abundant, predators should become more picky (specialists).

low

I -largest Daphnia preyIV - smallest Daphnia prey

Clear area -- actually eatenStippled area -- random eating

50 75 200

300 350

IV. Decision Making by ForagersA. Types of decisionsB. Balancing Costs and Benefits in DecisionsC. Optimal Diet Model

1. Logic2. Mathematical Model3. Predictions4. Evidence: an example with fish5. Other factors to consider

a. samplingb. switchingc. competitiond. predation

5. Other factors to considera. samplingb. switchingc. competitiond. predation

-- sampling: This theory requires that foragers know the costs and benefits of their prey. They can only do that if they occasionally sample all the prey.

-- switching: some prey require some time for the predator to learn how to catch. This learning can depend on the density of the prey.

-- competition: Resource competition just affects prey density, which doesn’t change the basic theory. Interference competition can leave the predator with less time to forage, forcing more of a generalist diet.

-- predation can also affect when and where a forager looks for prey, forcing more of a generalist diet.

I. Purpose of this CourseII. The Scientific MethodIII. What are Foragers?IV. Decision Making by Foragers

A. Types of decisionsB. Balancing Costs and Benefits in DecisionsC. Optimal Diet ModelD. Spatial Distribution of Resources

We have been considering WHICH prey to take. Sometimes is may also be important to understand WHERE to forage. Many models and experiments have attempted to predict or understand the spatial components of foraging.

D. Spatial Distribution of Resources1. The Ideal Free Distribution

(IDF)

-- WHERE to forage depends on both the number of prey and competition among foragers.

-- IDF states that animals disperse to equalize energy intake or reproductive success

Milinski, M. 1979. An evolutionarily stable feeding strategy in sticklebacks. Zeitschrift fur Tierpsychologie 51:36-40.

Placed 6 fish (sticklebacks) in tank and fed at different rates at each end of fish tank.

5:1 food ratio

2:1 then switch to 1:2

D. Spatial Distribution of Resources1. The Ideal Free Distribution

(IDF)-- so fish are “smart” and

conform to IDF. Other studies have

generally found similar results.

Harper DC, 1982. Competitive foraging in mallards: “ideal free” ducks. Anim Behav 30:575-84

However, the IDF doesn’t always hold. Why not?

IDF assumes that all individuals are equal. But, differences in competitive ability can lead to deviations from the IFD expectations. Dominant individuals get more than the predicted share of the resources.

I. Purpose of this CourseII. The Scientific MethodIII. What are Foragers?IV. Decision Making by Foragers

A. Types of decisionsB. Balancing Costs and Benefits in DecisionsC. Optimal Diet ModelD. Spatial Distribution of Resources

-- more in labs on Marginal Value TheoremE. Lots of other models you may encounter

in your reading!

I. Purpose of this CourseII. The Scientific MethodIII. What are Foragers?IV. Decision Making by ForagersV. Dynamics of Forager-Resource Numbers

V. Dynamics of Forager-Resource NumbersA. Dynamics of predator and prey are “tied”

1. When prey increases, predators can reproduce more, increasing their numbers as well. This drives prey numbers down, which results in fewer predators.

V. Dynamics of Forager-Resource NumbersA. Dynamics of predator and prey are “tied”

1. Predator and prey numbers linked

a. use PopDynb. Example: Huffacker’s mites

b. Example: Huffacker’s mites

V. Dynamics of Forager-Resource NumbersA. Dynamics of predator and prey are “tied”

1. Predator and prey numbers linked

2. We can show this mathematically by constructing simple equations:

Growth rate of prey (H):dH/dt = rH - cHP

Growth rate of predator (P):dP/dt = ecHP - mP

2. We can show this mathematically by constructing simple equations:

dH/dt = rH - cHP

dP/dt = ecHP - mP

You do not need to memorize these equations. But, you need to understand that they are linked: the predator and prey abundances depend on each other in characteristic ways.

Some implications of these equations.-- what is c and what behaviors are related to

it?-- what is e and what behaviors are related to

it?-- are r, c, e, m, really constants?-- what happens if P = 0? H = 0? Is this

realistic?

V. Dynamics of Forager-Resource NumbersA. Dynamics of predator and prey are “tied”B. Behaviors Associated with changes in

numbers.1. c and prey abundance

-- is c a constant?

Let’s hold the abundance of predators constant and increase the number of prey. Does the per-predator consumption of prey increase directly as a function of P?

A simple experiment can resolve this question.

1. C and prey abundanceClearly, at some point the predator becomes

satiated and cannot capture anymore prey and so c is not a constant at all. The form of the curve we created is called the functional response curve. This curve was initially derived by C.S. Holling who blindfolded his secretary and had her forage for sandpaper disks.

Holling suggested that there are three types of curves:

-- Type I-- Type II-- Type III

Who cares about these response curves? Well, for example, they are important for understanding those oscillations that predator and prey have.

As Huffaker’s work shows, the oscillations can cause either predator or prey to go extinct (often both). Behaviors that prevent predator and prey numbers from overshooting one another will stabilize predator-prey dynamics, allowing both to coexist.

-- The learning or switching component of the Type III curve can actually lead to stabilized P-H interactions.

V. Dynamics of Forager-Resource NumbersA. Dynamics of predator and prey are

“tied”B. Behaviors Associated with changes in

numbers.1. c and prey abundance 2. c and predator abundance

-- predator abundance can also influence foraging behavior. Examples suggest that c may go up or down.

-- negative relationships between feeding rate and predator density occur when there is competition interactions between predators.

-- positive relationships between feeding rate and predator density occur when there is group foraging behaviors, such as with organized predators (birds flocking and fish schooling).

V. Dynamics of Forager-Resource NumbersA. Dynamics of predator and prey are

“tied”B. Behaviors Associated with changes in

numbers.1. C and prey abundance 2. c and predator abundance3. Refuges and patch dynamics,

readin the book. Be ready for lab!

Example Study Chase, J. M. 1998. Central-place forager effects on food web dynamics and spatial pattern in northern California meadows. Ecology 79:1236-1245

A pattern is observed between lizards, their grasshopper prey, and the plants eaten by grasshoppers

• Is this pattern caused by a “trophic cascade” from foraging lizards?

• What else might cause this pattern? Could it be shading around structures? Wetter soil? Temperature changes?

• How would we test the idea that lizards are the most important factor?

They set up exclosures where they could keep out lizards. To determine if it was the exclosures or the structure that caused any pattern, the experiment was repeated with and without structure nearby.

They also looked for the expected effects of lizards on plants, but in this case, the exclosures could keep out lizards and grasshoppers (plants only) or only lizards.

Would similar spatial patterns be expected for other types of foragers?

-- must be a “central-place forager” with a constant home territory.

-- primary effects expected for herbivores, but secondary effects expected for true predators.

-- effects may be different for each species. Chase showed his effect primarily on forbs, not grasses.