| Summary: | Many fish species across multiple ecosystems tend to group together in shoals. Examples of such behavior can be observed in ecosystems that are saltwater or freshwater based and lentic or lotic. The grouping fish often gather in shoals with other similar sized individuals to maximize predator evasion, and travel within their home range looking for food. In this thesis the factors influencing the grouping behavior were examined, with an emphasis on the differences in length composition caused by it. The project’s purpose was to locate how far one would have to go to see a different size composition in a fish population. This was done by catching and measuring three-spined sticklebacks (Gasterosteus aculeatus) at four different locations within one lake and one pond in the greater Reykjavík area. The length data showed a statistical significance in mean length between the two study areas, and between trap locations within the lake and pond. There was also a significant difference in length frequencies between three sets of traps within the same body of water. However, there was not an increasing trend in length variance with increased distance within the lake and pond, suggesting that the shoals of sticklebacks are rather randomly dispersed within the two habitats. Length variance was greater at individual traps than combined variance from multiple traps. I then speculate which biotic and abiotic factors could cause the length composition differences, both between the two bodies of water and within them. Finally, I conclude that differently sized stickleback shoals either share home ranges with one another because they don’t have a specific home range need, or that they don’t have access to their preferred home range and are therefore grouped together out of necessity. Margar tegundir fiska í fjölbreyttum vistkerfum eiga það sameiginlegt að hópast saman í torfur. Dæmi um slíka hegðun má sjá í ferskvatnsvistkerfum, saltvatnsvistkerfum, og vistkerfum með stillt eða rennandi vatn. Þeir fiskar sem hópa sig saman ...
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