The Science Of Environmental Management

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GSE803 Science in Environmental Management

Exercise 2 – Ecology

Due date11 May 2015, submission through Turnitin

20 points making 10% of the mark

SN- 43622321

1. What is ecology? Give three examples of modern applied ecology (2 point).

2. How do K-selected and r-selected models of life-history strategy differ? Provide an example of each life-history strategy and how the management of such species would differ.(2 point). 3. Ecologists are interested in calculating population density to measure changes in populations over time. Define absolute and relative population densities. Indices of abundance can provide relative measures of animal densities or abundances, and may be used over time to describe population …show more content…

(0.5 point)

c) Most natural populations are not closed, how can we simulate a closed population? (0.5 point)

5. Error bars provide a) a measure of what within samples around a mean or medial value, why are they useful? c) What are two factors that can influence variability in the samples? d) Also in the two plots (below) identify where there are likely to be real statistical differences between samples. (4 points)


a) Error bars provide a graphical representation of the data variability and precision in a measurement. Within samples around mean or median value, they provide idea about how precise the measurements are and how far from reported value the true error-free value might actually be. They also provide a probable range within which the actual value may differ from the reported value.

Ceteris paribus, error bars can be used to visually compare two quantities to determine the statistical significance of the difference among them. It can also be used to suggest "goodness of fit" of a given function.

c) Variability in the samples can be reduced by increasing precision and accuracy, which in turn can be influenced through following two factors; such as:

1) sample number: Increase in sample number through increasing sample number or repeating same experiment multiple times causes mean of the result (M) to get closer to true mean, thus reducing variability.

2) sample placement with respect to spatial & temporal

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