1999Universiti Putra Malaysia Institutional Repository (Universiti Putra Malaysia)Open access

Factors influencing the occurrence of forest offenses in a Peninsular Malaysia state

Rusli Mohd

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Abstract

A study was conducted in one of the states of Peninsular Malaysia to observe the trends and identity factors associated with the occurrence of forest offenses during the period from 1981 to 1992. Data and information on forest offenses, price of logs, size of forest areas, and number of enforcement officers were collected from various sources including the records and annual reports of the State Forestry Department, and MASKAYU bulletin published by the Malaysian Timber Industry Board. Correlation and regression analyses were carried out to determine the relationships between forest offenses and price of logs, size of forest area and number of enforcement officers. The number of forest offenses in the state shows a decreasing trend. Illegal logging which is a form of forest offense constitutes the highest percentage in all the years during the study period. Of the three factors investigated, only the price of logs correlated significantly with forest offenses. The price of logs is inversely correlated with forest offenses. The regression models developed show the relationships between the number of offenses and the price of logs as follows: For number of forest offenses p = 0.02 and for number of illegal logging cases p = 0.03. Further studies should be conducted to better understand other factors like penalties that influence forest offenses.

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A study was conducted in one of the states of Peninsular Malaysia to observe the trends and identity factors associated with the occurrence of forest offenses during the period from 1981 to 1992. Data and information on forest offenses, price of logs, size of forest areas, and number of enforcement officers were collected from various sources including the records and annual reports of the State Forestry Department, and MASKAYU bulletin published by the Malaysian Timber Industry Board. Correlation and regression analyses were carried out to determine the relationships between forest offenses and price of logs, size of forest area and number of enforcement officers. The number of forest offenses in the state shows a decreasing trend. Illegal logging which is a form of forest offense constitutes the highest percentage in all the years during the study period. Of the three factors investigated, only the price of logs correlated significantly with forest offenses. The price of logs is inversely correlated with forest offenses. The regression models developed show the relationships between the number of offenses and the price of logs as follows: For number of forest offenses p = 0.02 and for number of illegal logging cases p = 0.03. Further studies should be conducted to better understand other factors like penalties that influence forest offenses.

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Available abstract

A study was conducted in one of the states of Peninsular Malaysia to observe the trends and identity factors associated with the occurrence of forest offenses during the period from 1981 to 1992. Data and information on forest offenses, price of logs, size of forest areas, and number of enforcement officers were collected from various sources including the records and annual reports of the State Forestry Department, and MASKAYU bulletin published by the Malaysian Timber Industry Board. Correlation and regression analyses were carried out to determine the relationships between forest offenses and price of logs, size of forest area and number of enforcement officers. The number of forest offenses in the state shows a decreasing trend. Illegal logging which is a form of forest offense constitutes the highest percentage in all the years during the study period. Of the three factors investigated, only the price of logs correlated significantly with forest offenses. The price of logs is inversely correlated with forest offenses. The regression models developed show the relationships between the number of offenses and the price of logs as follows: For number of forest offenses p = 0.02 and for number of illegal logging cases p = 0.03. Further studies should be conducted to better understand other factors like penalties that influence forest offenses.

Key concepts: Illegal logging, Logging, State forest, Forestry, Enforcement, Law enforcement, Identity theft, Geography

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