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Chapter 15

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James Thomson

Chapter 15Dynamics of Consumer Resource Interactions 302311 B 312315 A 315320 C 321322 ABConsumers can exert a substantial influence on resource populations Consider the example of cyclamen mites pest to strawberry plants and their natural predators also mites By experimentation it was found that cyclamen were 25 times more abundant in the absence of predator mites Generally the degree to which a resource population may be controlled by consumers depends on their respective life histories This influence in not exclusive to animals in many instances invasive plant species have been brought under control by introducing consumer species One can consider predatorprey interactions in a relatively simple way predators eat prey they increase their own numbers while decreasing the number of prey as the number of prey drop predators can go hungry and reduce in number with the reduction in predators prey can again become abundant These interactions can be modeled with relatively stable cycles 1 high prey low predator 2 high predator low prey The periods of these cycles depend on the reproductive cycles of specific species this introduces time delays and the environment assuming it follows periodic cycles of favourable vs unfavourable conditions predatorprey cycles are still quite predictable It is equally important to consider these interactions do not occurs specifically between two species other species can consume or be consumed by the population in question and these interactions may equally be modeled cyclically Parasitehost interactions can be modeled in a way similar to predatorprey interactions but the cyles are generally determined by the number of susceptible individuals within a population depending on inoculated individuals and individuals with natural antibodies In nature parasitehost interactions can mirror predatorprey interactions in the way they control populations eg tent caterpillar populations peak every two years the subsequent crash it due to a rise in the population susceptible to the nuclear polyhedrosis virus Modeling predatorprey interactions in laboratories was initially difficult as the environment is often too simplistic but once scientists created more realistic environments the characteristics oscillations of the two populations could be seen eg scientist Gause managed to achieve oscillations between predator and prey bacteria with the simple introduction of glass wool allowing prey a place to hide before this prey were always entirely eradicated by predators Predatorprey oscillations can me modeled using LotkaVolterra equations continuous growthdecline which
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