2.2 Study Guide Flashcards
If B=Births, D=Deaths, I=Immigration, and E=Emigration, what type of change in population size is represented by B + I > D + E? What about B + I = D + E?
B + I > D + E represents an increase in population size because the values representing gains in individuals sum to an amount larger than the values representing losses of individuals. Furthermore, based on this information, B + I = D + E represents no change in population size because the gains and losses are equal to each other.
What letter does the curve of a typical graph showing exponential growth in population size over time resemble? What is the name of that type of curve?
In typical graphs showing change in population growth rate vs change in population size, what is the difference in appearance between the exponential growth and logistic growth versions?
Exponential growth models that show change in population growth rate vs size appear as completely straight, positive trend lines (lines going from bottom left to top right) that increase in both values infinitely. Logistic growth models that show change in population growth rate vs size appear as symmetrical curves which have 0 growth at N-0 and K and the highest growth directly in the middle of population size at 1/2K.
At what point on a logistic growth model is population growth rate the highest? What about on exponential growth models?
On logistic growth models, the population growth rate is highest precisely when N=1/2K (population size is half of the carrying capacity). On exponential growth models, there is no set point where population growth rate is the highest because it is constantly increasing over time and goes into infinity.
What does the variable N represent in terms of population growth? What is the difference between N and N-0?
In terms of population growth, N represents the total population size (for a specific time, it would be N-t with t being the time). The difference between N and N-0 is that N-0 is specifically the initial size of a population being recorded.
What does the variable K represent in terms of population growth? In your own words, define the term that K represents.
In terms of population growth, K represents a population’s carrying capacity in a logistic growth model. Carrying capacity is the maximum population size a population can reach without causing damage to itself and its environment.
What do the variables r and dN/dt represent in terms of population growth? What is the difference between the two?
In terms of population growth, r represents a population’s growth per Capita (individual organism) while dN/dt represents the overall growth of the whole population (change in number over change in time). The difference between the two is that r represents each individual in a population’s capability to reproduce and multiply while dN/dt represents the capability of the population as a collective to reproduce and multiply.
What does the variable t represent in terms of population growth? How is t represented differently between discrete and continuous-time growth models?
In terms of population growth, t represents a specific time after the beginning of a recording at which data on a population is being recorded. In discrete-time models, t is represented as the base/beginning time and each data point is taken at t+ax with x representing a given interval of time and a an integer representing how many intervals have passed since t. In continuous-time models, however, data is taken literally ‘continuously’ and t can represent any amount of time after the recording begins.
What is the difference between Density-Dependent and Density-Independent Limiting Factors?
Density-Dependent Limiting Factors will affect two populations of the same species differently based on their population densities. The intensity of the effect ‘depends’ on the population’s ‘density’. Density-Independent Limiting Factors will affect two populations of the same species the same way no matter their difference in population density. The intensity of the effect is ‘independent’ of the population’s ‘density’.
What are some examples of Density-Dependent and Density-Independent Limiting Factors? Supply 2 of each and explain the main difference between the two groups of factors besides their dependence or independence on density.
Possible Density-Dependent Examples: Limited Shelter/Food/Water, Natural Predators, Diseases and Parasites (can be general and/or give specific examples), Parental Neglect, Cannibalism, etc.
Possible Density-Independent Examples: Sunlight, Temperature, Weather Patterns (severe weather like floods or droughts), Natural Disasters (can give specifics like hurricanes, fires, or volcanic eruptions), etc.
The main difference between the two groups besides their relations to density is that Density-Dependent Limiting Factors are all biotic factors while Density-Independent Limiting Factors are all abiotic factors.
In logistic growth models comparing population growth rate to population size, what changes when r increases? What doesn’t change? Why?
When r is increased in these logistic models, the range of population growth rate increases with it while the actual shape of the plot stays the same. This is because a higher r value allows the overall growth rate to increase faster, yet it still maxes out at the same population size and decreases at the same rate it increased at.
Why do population sizes of exponential growth models increase faster when N-0 is higher?
The population sizes increase faster because, as r is the same between any graphs being compared, a higher population size multiplies r by a higher number to determine the population’s growth. Thus, if r=1.5 and one exponential model has N-0=10 and one has N-0=100, the first model will only increase by 15 (1.5 x 10) and then by 37.5 (10 + 15 = 25, 25 x 1.5 = 37.5) while the second model will increase by 150 (100 x 1.5) and then 375 (100 + 150 = 250, 250 x 1.5 = 375). While the first model will eventually reach the point at which it grows at the same rate the second model does at first, the second model is already ahead of the first and will remain that way forever.
