BCOR 102: Exam 2 Flashcards
Age structure
relative number of individuals in each age class
stable age distribution
when lx and bx are constants, relative numbers in each age class do not change
stationary age distribution
relative + absolute numbers are constant
Life history strategy
schedule of lx and bx that maximizes offspring production and survival in a particular environment
Ways to increase r
- Reduce age at first reproduction
- Increase litter size
- Increase number of litters
- Increase survivorship of juvenile and reproductive ages
Cole’s paradox
r(iteroparous)=r(semelparous + 1 offspring)
Bet-hedging strategy
“Insurance policy” that some offspring will make it
r-selected populations (low density)
Competitive ability: weak
Development: fast
Reproduction: Early, semelparous
Juveniles: Many, small
Survival: Type III
r: large
k-selected populations (high density)
Competitive ability: strong
Development: slow
Reproduction: Late, iteroparous
Juveniles: few, large
Survival: Type I
r: small
intraspecific competition
competition within a species
Interspecific competition
competition between species
exploitation competition
population growth rates indirectly reduced through use of shared resources
interference competition
behavior or activity that reduces the uptake efficiency of another species
alpha (a) (competition model
the effect of N2 on the population growth rate of N1 measured in units of N1
isocline
combination of abundances of N1 and N2 such the dn(1)/dt = 0
Case I Competition graph
species 1 wins in competition
Case 2 Competition graph
Species 2 wins
Case 3 Competition graph
stable, coexistence
Case 4 Competition graph
unstable, species 1 or species 2 wins
Marble U shape analogy
Cases 1,2,3
stable equilibrium
doesn’t depend on initial n1, n2
not depending on r1, r2
Marble n Analogy
Case 4
unstable
depends on n1, n2
Hutchinson niche
n-dimensional hypervolume that defines a range of conditions for which dn/dt > 0
realized niche
effects of other species in the enivornment
character displacement
shifts in body size or morphology of a species in the presence of a competitor
ecological assortment
if species are “too close” in size or morphology on one of them to go extinct
Allopatric
living apart
sympatric
living together
“1.3” rule
species needed to differ in body size by a ratio of 1.3 to coexist
Mimicry (Mullerian)
warning colorization, unpalatable, dangerous
alpha (predation model)
capture efficiency
beta (predation model)
conversion efficiency (the ability of a predator to convert captured prey into new predator offspring
Large numbers of P needed to control V when:
- r is large (V has high growth rate)
- alpha is small (low capture efficiency
Large numbers of V needed to control P when:
- q is large (P starves quickly without V)
- beta is small ( low conversion efficiency)
Assumptions of Loka-V predation models
- no migration, age/size structure, genetic structure, time lags
- no carrying capacity for V (rV)
- P is a specialist on V population (-qP)
- P&V encounter one another randomly in a homogenous environment (Walking Dead)
- Individual predators are insatiable (no limit to a predator can eat, constant line of dV/dt = 0)
Lynx & snowshoe hare
has similar oscillations in population, lynx is a little delayed
scenario: if no lynx present, hare still have population cycles and cycles are synchronized across canada
due to vegetation, nitrogen content, and sunspots
Escape in size
chipmunks & oak trees
escape in space
shelters from predation, mussels vs. seastars
Escape in time
Day vs. night scuba anology
Escape in numbers
periodical cicadas, every 13-17 years, out of sync with other predator cycles
what happens with body mass and r?
if increase in mass –> low surface area to volume ratio (s/v) –> lower metabolism –> slow growth rate –> long generation time –> low r
**constant linear line downwards (looks like isocline)
Exploitation Competition model for N1
dN/(1)dt = r1N1(K(1) - N(1) - αN(2) / K(1))
Exploitation Competition model for N2
dN/(2)dt = r2N2(K(2) - N(2) - βN(2) / K(2))
N(1) (in compet. model)
intraspecific effect of N1 on N2
αN(2) (in compet. model)
interspecific effect of N2 on N1
N2 (in compet. model)
intraspecific of N2 on N2
βN(2) (in compet. model)
interspecific of N1 on N2
when does dn1/dt = 0?
when n1 = K(1) - αN(2)
k1/alpha
number of indiv. of n2 needed to use up all the resources of n1
when does dn2/dt = 0?
When n2 = K(2) - βN(2)
Victim predation eq.
dV/dt= rV - αVP
Predator predation eq.
dP/dt = βVP - qP
beta (competition model)
the effect of n1 on the growth if n2 per capita
