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Measuring and Modeling Population Changes Homework: p664 #1, p 665 #2, and p 668 #3,4.

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Presentation on theme: "Measuring and Modeling Population Changes Homework: p664 #1, p 665 #2, and p 668 #3,4."— Presentation transcript:

1 Measuring and Modeling Population Changes Homework: p664 #1, p 665 #2, and p 668 #3,4

2 Measuring and Modeling Population Changes An ecosystem has a finite pool of abiotic and biotic resources. Biotic factors tend to vary greatly over time, whereas most abiotic factors vary little over time (some exceptions: temp, water availability, etc...)

3 Carrying Capacity: the maximum number of individuals an ecosystem can support based on resources available. Carrying capacity is dynamic, always changing, since resource levels are never constant.

4 Fecundity/Biotic Potential: potential number of offspring that can be produced. eg HIGH – starfish, 1 million eggs/year LOW – hippo, 20 births in 45 years Fertility: actual number of offspring produced

5 SURVIVORSHIP CURVES General patterns in the survivorship of species

6 Type I Species have a low mortality rate when young These are slow to reach sexual maturity and produce small numbers of offspring. Have a longer life expectancy. Ex: Large mammals, including humans

7 Type 2 Intermediate between types I and III Have a uniform risk of mortality over their lifetime. Certain lizards, perching birds, rodents.

8 Type 3 Very high mortality rate when young Those that reach sexual maturity have a greatly reduced mortality rate Very low average life expectancy (ex. Green Sea Turtle).

9 POPULATION CHANGE Population change (%) = [(b + i) – (d+e)] x 100 n b = births, d = deaths, i = immigration, e = emigration, n = initial population size A negative result means population is declining. A positive result means population is growing. In an open population all four factors come into play (i.e. in the wild). In a closed population only births and deaths are a factor (i.e. in a zoo)

10 POPULATION GROWTH There are 3 main types of population growth. Geometric, Exponential and Logistic.

11 Geometric Growth Many populations grow rapidly during the breeding season and then decline slowly the rest of the year. Geometric growth is a pattern of population growth where organisms reproduce at fixed intervals at a constant rate. TIME

12 Geometric Growth The growth rate is a constant ( λ) and can be determined by comparing the population size in one year to the population size at the same time the previous year. λ = N (t + 1) N(t) N is the population size at a given year (t+1) or (t) λ is the fixed growth rate (one year vs next)

13 To find the population size at any given year, the formula is: N(t) = N(0)λ t N(0) is the initial population size

14 EXAMPLE The initial Puffin population on Gull Island, Newfoundland is 88 000. Over the course of the year they have 33 000 births and 20 000 deaths. a) What is their growth rate? b) What will the population size be in 10 years at this current growth rate?

15 Answer to a) ANSWER a) N (0) = 88 000 λ = N(t + 1) = 101 000 = 1.15 N (1) =101 000 N(t) 88 000 Therefore the growth rate is 1.15.

16 Answer to b) From a) growth rate, or λ = 1.15 N(10) = N(0)λ 10 * BEDMAS = 88 000 (1.15) 10 = 356 009 Therefore the population size will be 356 009 in 10 years.

17 EXPONENTIAL GROWTH A wide variety of species are able to reproduce on a continuous, rather than intermittent basis. (ex. humans, bacteria, cancer cells) Exponential growth is growing continuously at a fixed rate in a fixed time interval J – shaped curve

18 Calculating Exponential Growth The same formulas can be used as geometric growth, however, since the time interval is not restricted to breeding periods, biologists are able to calculate the instantaneous growth rate. It is expressed in terms of the intrinsic (per capita) growth rate, r, where r = b – d (per capita birth rate – per capita death rate)

19 Exponential population growth rate is: dN = rN dt Doubling time: to find the time it takes a population that is reproducing exponentially to double, we use the equation: t d = 0.69 r Instantaneous growth rate Intrinsic growth rate Population Size

20 Sample Problem A population of 2500 yeast cells in a culture tube is growing exponentially. If the intrinsic growth rate is 0.030 per hour, calculate: a) the initial instantaneous growth rate of the yeast population. b) the time it will take for the population to double in size. c) the population size after four doubling periods.

21 Answer A population of 2500 yeast cells in a culture tube is growing exponentially. If the intrinsic growth rate is 0.030 per hour, calculate: N = 2500 yeast, r = 0.030 yeast /hr a) dN/dt = rN = 0.030 yeast/hr x 2500 yeast = 75 /hr When the population size is 2500 the instantaneous population growth rate is 75 per hour

22 Answer A population of 2500 yeast cells in a culture tube is growing exponentially. If the intrinsic growth rate is 0.030 per hour, calculate: N = 2500 yeast, r = 0.030 yeast /hr b) t d = 0.69/r = 0.69 / 0.03/hr the population size after four doubling periods.

23 Answer A population of 2500 yeast cells in a culture tube is growing exponentially. If the intrinsic growth rate is 0.030 per hour, calculate: N = 2500 yeast, r = 0.030 yeast /hr c) the population size after four doubling periods.

24 LOGISTIC GROWTH The previous two models assume an unlimited resource supply, which is never the case in the real world. When a population is just starting out, resources are plentiful and the population grows rapidly (geometrically/exponentially). BUT, as the population grows, resources are being used up and the population nears the ecosystem's carrying capacity.

25 The growth rate drops and a stable equilibrium exists b/w births and deaths. The population size is now the carrying capacity (K). This is known as a sigmoidal curve.

26 Logistic Growth Curve LAG phase: Initial growth is slow, due to small numbers LOG phase: greatest increases, lots of resources Dynamic Equilibrium: population reaches carrying capacity (b = d) Carrying capacity

27 LOGISTIC GROWTH EQUATION Logistic growth represents the effect of carrying capacity on the growth of a population. It is the most common growth pattern in nature. dN = r max N K – N dt K Population growth at a given time Max intrinsic growth rate Population size at given time Carrying capacity

28 continued... If the population size is close to the carrying capacity, there is virtually no growth (K-N = 0), thus the equation takes into account declining resources as the population increases.

29 Sample Problem A population of humans on a deserted island is growing continuously. The carrying capacity of that island is 1000 individuals and the maximum growth rate is 0.50. Determine the population growth rates over 5 years if the initial population size is 200.


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