3a and 3b

• Populations


  Groups of individuals of the same species living in the same area
• Life tables

  A numerical summary of the products of fecundity and mortality of a population

  
• Survivorship curves


  Plots showing how mortality changes over time, influencing population structure

  
• Life history strategies

  Organisms tend towards either an r-selection strategy (numerous offspring with little investment) or a K-selection strategy (few offspring with high investment)
• Competition

  Interactions between organisms over limited resources (space, food, water, mates etc.)
• Population densities


  The number of individuals per unit area or volume
• Estimating populations

  Techniques used to determine the size of a population

  
• Cohort life table

  1. ax - Number alive at start of stage x

  2. lx - Proportion of original cohort surviving to start of stage x

  3. dx - Proportion of original cohort that "dies" in that stage

  4. qx - Stage specific mortality rate

  
• Life table with fecundity

  1. Fx - Total fecundity (offspring produced) at that stage

  2. mx - Individual fecundity (Fx/ax)

  3. lxmx - Fecundity per original cohort member (Fx/a0)

  4. Ro - Basic reproductive rate (mean offspring per individual)
• Ro = 1 means the population is stable
• Ro < 1 means the population is in decline
• Ro > 1 means the population is increasing or too high
• Life table response experiments

  "What if?" scenarios to predict population changes under different conditions
• Survivorship curves

  • Show how mortality changes over time, influencing population structure

  
• Density dependent mortality


  The rate of death is linked to the size of the population, higher density leads to greater mortality

  
• Density independent mortality


  Mortality not linked to population size

  
• Birth rate

  Increases population size
• Death rate

  Decreases population size
• 1. selection strategy

  Having numerous offspring with little investment per individual
• 1. selection strategy

  Having few offspring but investing heavily in each one
• Population effects of r vs K strategies


  • r-selected populations biased towards juveniles, K-selected biased towards adults
• Limits to population growth


  Overpopulation, diseases, lack of food, predators etc. will limit population growth and can lead to crashes
• Inverse density dependence

  At low densities, mortality may greatly exceed fecundity, leading to extinction

  
• Interspecific competition

  Competition between different species, can be direct or indirect
• Intraspecific competition

  Competition between individuals or populations of the same species, density dependent
• Scramble competition

  All individuals scrambling for limited resources, none likely getting enough
• Contest competition

  Individuals competing directly for resources, some winning and others losing out
• Interspecific Competition

  Competition between species. Species may compete directly or indirectly.
• Direct competition

  • A wolf and a bear fighting over a single carcass
• Indirect competition

  • Wolves and bears both hunt and eat deer, so every deer removed by wolves is not available to bears even if they never meet
• Intraspecific competition

  Competition between individuals (or perhaps populations) of a single species
• Members of a species will likely have the highest competition with conspecifics – they have the same requirements!
• They will also compete for resources that heterospecifics will not, especially mates
• Intraspecific competition

  Density dependent
• Scramble competition

  All individuals scrambling for the resource with none likely getting enough to sustain them
• Contest competition


  A deciding factor (e.g. a direct fight b/w individuals or a binary resource) as to who gets the resources with winners getting enough
• Below K (carrying capacity)

  There is minimal competition, then it becomes extreme and huge numbers die
• As population increases

  Competition increases steadily
• Losers in contest competition don't necessarily die (e.g. may not get a breeding site)
• Theoretical extrapolations and mathematical models are very important for understanding the world, but the observation or implementation can be very different