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How do the exponential and logistic differential equations model unrestricted and limited growth?

Set up and solve the exponential growth-decay equation and the logistic equation and interpret their solutions

WACE Specialist Unit 4 growth models: the exponential equation dy/dt equal to ky and its solution, the logistic equation with a carrying capacity, the S-shaped solution curve, equilibria, and interpreting parameters, with a worked example.

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  1. What this dot point is asking
  2. The exponential model
  3. Solving the exponential equation in full
  4. The logistic model
  5. Equilibria and the S-curve
  6. Interpreting the parameters
  7. Choosing between the two models

What this dot point is asking

SCSA wants you to set up these two models from a description, solve them (logistic via separation and partial fractions), and interpret the parameters and long-term behaviour.

The exponential model

When the rate of change is proportional to the current amount, dydt=ky\tfrac{dy}{dt} = ky. Separating variables and integrating gives

where y0y_0 is the initial value and kk is the constant of proportionality. Positive kk models unrestricted growth; negative kk models decay such as radioactive half-life. This model has no upper bound, which is unrealistic over long times.

Solving the exponential equation in full

It is worth seeing the separation of variables that produces the exponential solution, because SCSA can ask for the derivation, not just the formula. Starting from dydt=ky\dfrac{dy}{dt} = ky, separate the variables to 1ydy=kdt\dfrac{1}{y}\,dy = k\,dt and integrate both sides: lny=kt+c\ln|y| = kt + c. Exponentiating gives y=ekt+c=ecekt|y| = e^{kt + c} = e^c e^{kt}, so y=Aekty = A e^{kt} where A=±ecA = \pm e^c absorbs the constant. Applying the initial condition y(0)=y0y(0) = y_0 fixes A=y0A = y_0, giving y=y0ekty = y_0 e^{kt}. The same steps, with a sign, handle decay, where the half-life satisfies T=ln2kT = \dfrac{\ln 2}{|k|}.

The logistic model

Real populations are limited by resources. The logistic equation adds a braking factor:

where MM is the carrying capacity. When PP is small the bracket is near 11 and growth is nearly exponential; as PP approaches MM the bracket approaches 00 and growth slows to a halt.

Equilibria and the S-curve

Solving the logistic equation uses separation of variables with a partial-fraction decomposition of 1P(1P/M)\tfrac{1}{P(1 - P/M)}, leading to a solution of the form P=M1+AektP = \tfrac{M}{1 + A e^{-kt}}.

Interpreting the parameters

Each symbol in the logistic solution has a clear meaning that examiners ask students to read off. The carrying capacity MM is the horizontal asymptote the curve rises toward, the long-run population the environment can sustain. The growth-rate constant kk controls how fast the S-curve climbs: a larger kk gives a steeper rise and a faster approach to MM. The constant AA is fixed by the initial condition through A=MP0P0A = \dfrac{M - P_0}{P_0}, so a small starting population gives a large AA and a long slow phase before the rapid middle growth. Sketching the solution means drawing the asymptote at P=MP = M, the starting value P0P_0, and the S-shape with its inflection at P=M2P = \dfrac{M}{2}.

Choosing between the two models

Deciding which model a context calls for is itself examinable. Use the exponential model when nothing limits the growth, for example a short-term investment at compound interest or radioactive decay, where the rate stays proportional to the current amount forever. Use the logistic model when the context names or implies a ceiling, such as the maximum population an ecosystem can support or the saturation level of a market. A useful diagnostic is the early behaviour: both models look exponential while the quantity is small, but only the logistic model bends over and levels off, so any mention of a limit, saturation or carrying capacity points to logistic growth.

Exam-style practice questions

Practice questions written in the style of SCSA exam questions on this dot point, with worked answer explainers. The year tag is the paper they imitate, not the source.

WACE 20237 marksCalculator-assumed. A radioactive isotope decays so that dmdt=km\dfrac{dm}{dt} = -km, where mm is the mass in grams and tt is in years. Initially m=80m = 80 g, and after 1010 years m=60m = 60 g. (a) Find kk. (b) Find the half-life of the isotope.
Show worked answer →

An exponential-decay model.

(a) The solution is m=80ektm = 80 e^{-kt}. At t=10t = 10, 60=80e10k60 = 80 e^{-10k}, so e10k=0.75e^{-10k} = 0.75. Taking logs: 10k=ln0.75-10k = \ln 0.75, giving k=ln0.75100.0288k = -\dfrac{\ln 0.75}{10} \approx 0.0288 per year.

(b) The half-life TT satisfies 40=80ekT40 = 80 e^{-kT}, so ekT=0.5e^{-kT} = 0.5, hence T=ln2k=0.69310.028824.1T = \dfrac{\ln 2}{k} = \dfrac{0.6931}{0.0288} \approx 24.1 years.

Markers reward the solution form, solving for kk with logarithms, and the half-life formula T=ln2kT = \dfrac{\ln 2}{k}.

WACE 20216 marksCalculator-assumed. A fish population follows the logistic model dPdt=0.4P(1P5000)\dfrac{dP}{dt} = 0.4P\left(1 - \dfrac{P}{5000}\right), with P(0)=500P(0) = 500. (a) State the carrying capacity and the equilibria. (b) Find the population size at which the population grows fastest, and the maximum growth rate.
Show worked answer →

A logistic-model interpretation.

(a) The carrying capacity is M=5000M = 5000. Equilibria occur where dPdt=0\dfrac{dP}{dt} = 0: at P=0P = 0 (unstable) and P=5000P = 5000 (stable).

(b) Logistic growth is fastest at the inflection P=M2=2500P = \dfrac{M}{2} = 2500. The rate there is 0.4×2500×(125005000)=0.4×2500×0.5=5000.4 \times 2500 \times \left(1 - \dfrac{2500}{5000}\right) = 0.4 \times 2500 \times 0.5 = 500 fish per unit time.

Markers reward the carrying capacity, both equilibria with stability, the inflection at P=2500P = 2500, and the maximum rate 500500.

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