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M 5.5. IDQ #10 – Trees PQ #15 – 14.3 and 14.4 Ch 14 Discussion Turn in today: Lab 11A; Wolves Turn in Friday: Lab 10BC; Field Lab – Handout Friday – Exam 3, 10 AM . 1. 2. 3. 4. 5. PQ #15. Predation. Behavioral: diet choice, patch use, optimal foraging ( ch 7)

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m 5 5
M 5.5
  • IDQ #10 – Trees
  • PQ #15 – 14.3 and 14.4
  • Ch 14 Discussion

Turn in today:

Lab 11A; Wolves

Turn in Friday:

Lab 10BC; Field Lab – Handout

Friday – Exam 3, 10 AM

predation
Predation
  • Behavioral: diet choice, patch use, optimal foraging (ch 7)
  • Community: diversity (ch 16)
  • Population: how do host/predator interactions regulate population numbers? (ch 14)
    • By availability H → P
    • By fear P → H
    • By death P → H
two kinds of responses
Two kinds of responses
  • Numerical – predators increase after prey increase (lag to due reproductive effort time)
  • Functional – three types of curves (ch7, p 164)
predator host models
Predator-Host Models
  • How does the growth of one affect the growth of the other?
  • We need our logistic growth equation again:
  • The limiting factor is space available

ΔN = r * N * (K – N)/K

predator host models1
Predator-Host Models
  • But, in P-H models, host N is limited by predation and predator N is limited by access to hosts.
host growth
Host Growth
  • The rate of increase in the host is equal to the normal growth rate, minus the rate of predation (calculated as a per capita rate)
predator growth
Predator Growth
  • The rate of increase in the predator is equal to the conversion factor of the food item to offspring (calculated as predation rate times conversion constant), minus the death rate of the predator (calculated as a per capita rate)
slide15

p, c, d, r are constants

  • Ns are variables
slide16

Graph by Dr. K Schmidt, Texas Tech

Pred

(+)

Pred

(-)

P

Host

(+)

Host

(-)

K

N

  • Hosts can grow when predators shrink, and hosts shrink when predators grow.
  • Reproductive lags lead to cycles
slide17

safety

in #’s

limits to

growth

In other words:

Graph by Dr. K Schmidt, Texas Tech

P

N

  • The predator in this scenario has a straight vertical line: Np is constant.
  • The intersection of the two isoclines give us a stable cycle.
slide19

Region of pos. DD:

expanding oscillations

(unstable)

P

N

Remember!

Predator variation is due to prey variation!

slide20

Two dysfunctional extremes

Inefficient predators

lead to extinction

of the predator in variable

environments

Efficient predators

lead to highly

unstable predator-

prey interactions

K

K

K

can an unstable system be stabilized
Can an unstable system be stabilized?
  • Complex (natural) environments include barriers to predator dispersal
  • Refuges become important
    • Physical
    • Behavioral/Temporal
slide23

Feed deer

(increases K to K’)

(1) Productivity goes into building

new predators NOT prey

(2) Instability increases

(3) Populations go extinct

P*

What NOT to do – the Paradox of Enrichment

mountain lion

stable EQ

K

K

mule deer

mule deer

unstable EQ

N*

K

K’

combined response
Combined response
  • Gives us percentage of host consumed within an area
  • Percentage should be lower at high densities. Why?
  • Predator satiation is a defensive mechanism
  • “Hosts can reduce their individual probability of being eaten by occurring at very high densities”
slide25
Next…
  • Ecology of fear
    • Hosts/prey engage in vigilance behavior
    • Fear is high when
      • Predators are near
      • Lethality is high
    • Fear is low when
      • Effectiveness of vigilance is low
      • Feeding opportunities are low
    • Too much vigilance leads to missing out on food
    • Too little vigilance leads to being killed