Evolution and Population Genetics

Evolution and Population Genetics
I. The Modern Synthesis II. Beyond the Synthesis III. Types of Selection Population Ecology Populations are groups of potentially reproducing individuals in the same place, at the same time, that share a common gene pool.

Population Ecology Populations are groups of potentially reproducing individuals in the same place, at the same time, that share a common gene pool. I. Spatial Distributions A. Dispersion

I. Spatial Distributions
A. Dispersion - Regular

I. Spatial Distributions A. Dispersion - Regular
- intraspecific competition - allelopathy - territoriality

I. Spatial Distributions A. Dispersion - Clumped
- patchy resource - social effects

I. Spatial Distributions A. Dispersion - Random
- canopy trees, later in succession

I. Spatial Distributions A. Dispersion - Complexities
- can change with development. Seedlings are often clumped (around parent or in a gap), but randomness develops as correlations among resources decline. regular can develop if competition becomes limiting.

- can change with development. Seedlings are often clumped (around parent or in a gap), but randomness develops as correlations among resources decline. regular can develop if competition becomes limiting. - can change with population, depending on resource distribution.

- can change with development. Seedlings are often clumped (around parent or in a gap), but randomness develops as correlations among resources decline. regular can develop if competition becomes limiting. - can change with population, depending on resource distribution. - varies with scale. As scale increases, the environment will appear more 'patchy' and individuals will look clumped.

A. Dispersion B. Density

A. Dispersion B. Density 1. Large organisms have lower density than small organisms.

I. Spatial Distributions A. Dispersion B. Density
1. Large organisms have lower density than small organisms. Damuth (1981) - herbivorous mammals - log-log relationship - for a 10x increase in size, about an 80% reduction in density

1. Large organisms have lower density than small organisms. Damuth (1981) - herbivorous mammals - log-log relationship - for a 10x increase in size, about an 80% reduction in density White (1985) - Plants - similar trend... "-3/2 self-thinning law". A stand of dense seedlings/saplings will die back as they grow to a sparse stand of mature plants.

1. Large organisms have lower density than small organisms. 2. High density at center of range, low density along periphery

1. Large organisms have lower density than small organisms. 2. High density at center of range, low density along periphery 3. Abundant species often have larger ranges

A. Dispersion B. Density C. Extinction Factors

A. Dispersion B. Density C. Extinction Factors - small range

A. Dispersion B. Density C. Extinction Factors - small range - narrow environmental tolerances

A. Dispersion B. Density C. Extinction Factors - small range - narrow environmental tolerances - small local population

A. Dispersion B. Density C. Extinction Factors D. The Shapes of Ranges (Brown 1995)

A. Dispersion B. Density C. Extinction Factors D. The Shapes of Ranges (Brown 1995) - Many abundant species in North America have ranges oriented E-W. Most rare species have ranges oriented N-S.

A. Dispersion B. Density C. Extinction Factors D. The Shapes of Ranges (Brown 1995) - Many abundant species in North America have ranges oriented E-W. Most rare species have ranges oriented N-S. Does this tell us something about their ecologies?

D. The Shapes of Ranges (Brown 1995)
- Rivers and mountains run N-S

D. The Shapes of Ranges (Brown 1995) - Rivers and mountains run N-S
So, if a species has an E-W range, it will probably cross many habitats; signifying that the species is an abundant generalist.

So, if a species has an E-W range, it will probably cross many habitats; signifying that the species is an abundant generalist. If a species has a N-S distribution, it may be a rare specialist limited to one habitat zone.

So, if a species has an E-W range, it will probably cross many habitats; signifying that the species is an abundant generalist. If a species has a N-S distribution, it may be a rare specialist limited to one habitat zone. An independent test would be to make predictions about Europe.

An independent test would be to make predictions about Europe.

An independent test would be to make predictions about Europe. Abundant species run N-S, and rare species run E-W, as predicted by topography and the generalist-specialist argument.

II. Demography

II. Demography A. Life Tables

I. Spatial Distributions II. Demography A. Life Tables
- used to determine:

- used to determine: the survivorship patterns in a population the growth potential of a population

- used to determine: the survivorship patterns in a population the growth potential of a population - used by insurance companies to estimate the age-specific expected life span of their clients. The insurance company can then determine how much they have to charge the client to make a profit.

- used to determine: the survivorship patterns in a population the growth potential of a population - used by insurance companies to estimate the age-specific expected life span of their clients. The insurance company can then determine how much they have to charge the client to make a profit. An old person has a shorter expected life span than a young person, so they must be charged more per year in premiums in order to guarantee a profit to the company.

1. Components Age classes (x): x = 0, x = 1, etc. Initial size of the population: nx, at x = 0. x nx lx dx qx Lm ex 115 1 2 3 4 5 6

1. Components Age classes (x): x = 0, x = 1, etc. Initial size of the population: nx, at x = 0. Number reaching each birthday are subsequent values of nx x nx lx dx qx Lm ex 115 1 25 2 19 3 12 4 5 6

1. Components Age classes (x): x = 0, x = 1, etc. Initial size of the population: nx, at x = 0. Survivorship (lx): proportion of population surviving to age x. x nx lx dx qx Lm ex 115 1.00 1 25 0.22 2 19 0.17 3 12 0.10 4 0.02 5 0.01 6

1. Components Age classes (x): x = 0, x = 1, etc. Initial size of the population: nx, at x = 0. Survivorship (lx): proportion of population surviving to age x. Mortality: dx = # dying during interval x to x+1. Mortality rate: qx = proportion of individuals age x that die during interval x to x+1. x nx lx dx qx Lm ex 115 1.00 90 0.78 1 25 0.22 6 0.24 2 19 0.17 7 0.37 3 12 0.10 10 0.83 4 0.02 0.50 5 0.01 -

1. Components Age classes (x): x = 0, x = 1, etc. Initial size of the population: nx, at x = 0. Survivorship (lx): proportion of population surviving to age x. Number alive DURING age class x: Lm = (nx + (nx+1))/2 x nx lx dx qx Lm ex 115 1.00 90 0.78 70.0 1 25 0.22 6 0.24 22.0 2 19 0.17 7 0.37 15.5 3 12 0.10 10 0.83 7.0 4 0.02 0.50 1.5 5 0.01 0.5 -

1. Components Age classes (x): x = 0, x = 1, etc. Initial size of the population: nx, at x = 0. Survivorship (lx): proportion of population surviving to age x. Number alive DURING age class x: Lm = (nx + (nx+1))/2 Expected lifespan at age x = ex x nx lx dx qx Lm ex 115 1.00 90 0.78 70.0 1 25 0.22 6 0.24 22.0 2 19 0.17 7 0.37 15.5 3 12 0.10 10 0.83 7.0 4 0.02 0.50 1.5 5 0.01 0.5 -

x nx lx dx qx Lm ex 115 1.00 90 0.78 70.0 1.01 1 25 0.22 6 0.24 22.0 1.86 2 19 0.17 7 0.37 15.5 1.29 3 12 0.10 10 0.83 7.0 0.75 4 0.02 0.50 1.5 5 0.01 0.5 - Life Expectancy (ex): 1. calculate average # in each age class: Lm = (nx + (nx+1))/2. 2. T = Sum of Lm's for age classes = , > than age 3. ex = T/nx (number of individuals in the age class) 4. Value = the number of additional age classes an individual can expect to live.

x nx lx dx qx Lm ex 115 1.00 90 0.78 70.0 1.01 1 25 0.22 6 0.24 22.0 1.86 2 19 0.17 7 0.37 15.5 1.29 3 12 0.10 10 0.83 7.0 0.75 4 0.02 0.50 1.5 5 0.01 0.5 - Note.... expectancy does not always decline with increasing age. If young can survive period of high juvenile mortality (Age class 0), then survivorship increases.

1. Components 2. Cohort Table - Song Sparrows Mandarte Isl., B.C. (1988) x nx lx dx qx Lm ex 115 1.00 90 0.78 70.0 1.01 1 25 0.22 6 0.24 22.0 1.86 2 19 0.17 7 0.37 15.5 1.29 3 12 0.10 10 0.83 7.0 0.75 4 0.02 0.50 1.5 5 0.01 0.5 -

2. Cohort Table - Song Sparrows Mandarte Isl., B.C. (1988)
x nx lx dx qx Lm ex 115 1.00 90 0.78 70.0 1.01 1 25 0.22 6 0.24 22.0 1.86 2 19 0.17 7 0.37 15.5 1.29 3 12 0.10 10 0.83 7.0 0.75 4 0.02 0.50 1.5 5 0.01 0.5 - Good for describing unique history of a cohort... but bad for describing typical patterns for a population because this cohort may be affected by a unique event...

1. Components 2. Cohort Table 3. Static Table

1. Components 2. Cohort Table 3. Static Table Observe an entire population, with individuals of all ages, for a single time interval. Record the number of individuals in each age class at the start and at the end, and calculate values accordingly.

1. Components 2. Cohort Table 3. Static Table Observe an entire population, with individuals of all ages, for a single time interval. Record the number of individuals in each age class at the start and at the end, and calculate values accordingly. Is this year or time period typical?

II. Demography A. Life Tables B. Age Class Distributions

1. Components 2. Age Class Distribution

Potential Rapid Growth
Declining Growth

France: 1963

II. Demography A. Life Tables B. Age Class Distributions C. Survivorship Curves

B. Age Class Distributions C. Survivorship Curves Type I - Low Juvenile Mortality: parental care, few predators

B. Age Class Distributions C. Survivorship Curves Type II - Constant Mortality

B. Age Class Distributions C. Survivorship Curves Type III - High Juvenile Mortality

Evolution and Population Genetics

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