BIOA02H3 Lecture Notes - Lecture 5: Carrying Capacity, Logistic Function, Exponential Growth

• School: UTSC
• Department: Biological Sciences
• Course: BIOA02H3
• Professor: Rachel Sturge

Document Summary

Modelling population growth in a open system: a population growing in an unlimited environment. Pop size at next time interval = initial pop size + births in interval - deaths in interval. Converting b and d to per capita rates. Modeling exponential growth in a closed system: we can also express the equation in terms of per capita (per individual) rates of birth (b) and death (d) Example of exponential growth rate: organisms that have a higher r will grow faster. K is the point where population size is constant (birth rate = death rate): assume that b and d change linearly with population size. Comparing the growth rates: unlike exponential growth rate, logistic growth rate declines as n approaches k. Some population exhibit regular cycles: lagged responses of birth and death due to density can cause regular cycles (fluctuations around k, severity of fluctuation depends on size of time lag.