2021Journal of Physical and Applied SciencesOpen access

Factorial Design and Model for the Effect of Anti-Poaching Rules and Laws a Case Study in South Africa, India, and Kenya.

Grace Chepkorir Chumba

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Abstract

The purpose of this study is to use factorial design to investigate the effect of anti-poaching rules and laws in the reduction of illegal poaching of wildlife, and find a model for adequate description of the various observations in the data for the number of poached wildlife. Two-factor factorial design with mixed factors (country as the random factor and wildlife) as the mixed factor was used for the presentation and analysis of the data of the yearly number of poached wildlife for the period 2014 – 2017 recorded by KWS statistics in Kenya, South Africa and India. It resulted that the campaign on the ant-poaching rules and laws helped in the reduction of killed wildlife. There was also an indication that the effect of anti-poaching rules and laws in the reduction of poached wildlife in Kenya is different from that in South Africa and India. Also a mixed effect model was found to be adequate in the description of the various observations in the data for the number of poached wildlife as about 99% of variability in the mixed effect model on the number of poached wildlife is explained by the country (factor A), type of wildlife (factor B) and country-type of wildlife interaction.

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The purpose of this study is to use factorial design to investigate the effect of anti-poaching rules and laws in the reduction of illegal poaching of wildlife, and find a model for adequate description of the various observations in the data for the number of poached wildlife. Two-factor factorial design with mixed factors (country as the random factor and wildlife) as the mixed factor was used for the presentation and analysis of the data of the yearly number of poached wildlife for the period 2014 – 2017 recorded by KWS statistics in Kenya, South Africa and India. It resulted that the campaign on the ant-poaching rules and laws helped in the reduction of killed wildlife. There was also an indication that the effect of anti-poaching rules and laws in the reduction of poached wildlife in Kenya is different from that in South Africa and India. Also a mixed effect model was found to be adequate in the description of the various observations in the data for the number of poached wildlife as about 99% of variability in the mixed effect model on the number of poached wildlife is explained by the country (factor A), type of wildlife (factor B) and country-type of wildlife interaction.

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Available abstract

The purpose of this study is to use factorial design to investigate the effect of anti-poaching rules and laws in the reduction of illegal poaching of wildlife, and find a model for adequate description of the various observations in the data for the number of poached wildlife. Two-factor factorial design with mixed factors (country as the random factor and wildlife) as the mixed factor was used for the presentation and analysis of the data of the yearly number of poached wildlife for the period 2014 – 2017 recorded by KWS statistics in Kenya, South Africa and India. It resulted that the campaign on the ant-poaching rules and laws helped in the reduction of killed wildlife. There was also an indication that the effect of anti-poaching rules and laws in the reduction of poached wildlife in Kenya is different from that in South Africa and India. Also a mixed effect model was found to be adequate in the description of the various observations in the data for the number of poached wildlife as about 99% of variability in the mixed effect model on the number of poached wildlife is explained by the country (factor A), type of wildlife (factor B) and country-type of wildlife interaction.

Key concepts: Poaching, Wildlife, Geography, Environmental protection, Ecology, Biology

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Factorial Design and Model for the Effect of Anti-Poaching Rules and Laws a Case Study in South Africa, India, and Kenya. — Research Paper | ScholarLens