HUMAN & DISASTER: A Study of Prediction on the Species Number and Naturalization Index of Land Naturalized Plants
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초록
Foreign plants introduced by overseas exchanges are rapidly transformed into naturalized plants and pose se-rious threats to biodiversity, including domestic native species. Therefore, this study is based on the flora survey data of 776 map numbers(1200 places) for 12 years from 2006 to 2017, the third to fourth data of the National Natural Environment Survey, the nation’s largest basic research project on the natural ecosystem. By analyzing plant species and naturalized plant species and predicting naturalized plant species and naturalization Index, they can be used as basic data to study environmental changes, or they can be used to set various indicators ap-plying naturalized plants and naturalization Index and to set the upper limit of permit for development activities. Therefore, in this study, one-way ANOVA analysis and MANOVA analysis were conducted to determine whether there is a difference in naturalized plant species and naturalization Index by year, region, altitude, population density, GDP, and the ratio of forest to area. There was a correlation between the items such as year, region, alti-tude, population density, GDP, the ratio of forest to area and the number and naturalization Index of naturalized plants, and the greatest impact on the naturalized plant species and naturalization Index. Curve estimation re-gression, multiple regression, and dummy variable regression were performed to find out which items are causing the problem. Through this research, it is thought that the naturalization Index predicted by this study can be used for the issue of Permit on Exclusive use of inter-mountain area altitude standard, which is operated under the Act on Planning, and Use of National Territory, and the Mountain Site Management Act. The naturalization Index predicted by this study can be used as basic data for setting the upper limit of Permit on Exclusive use of inter-mountain area, or for studying environmental change, or for setting various indicators.
Abstract
Foreign plants introduced by overseas exchanges are rapidly transformed into naturalized plants and pose se-rious threats to biodiversity, including domestic native species. Therefore, this study is based on the flora survey data of 776 map numbers(1200 places) for 12 years from 2006 to 2017, the third to fourth data of the National Natural Environment Survey, the nation’s largest basic research project on the natural ecosystem. By analyzing plant species and naturalized plant species and predicting naturalized plant species and naturalization Index, they can be used as basic data to study environmental changes, or they can be used to set various indicators ap-plying naturalized plants and naturalization Index and to set the upper limit of permit for development activities. Therefore, in this study, one-way ANOVA analysis and MANOVA analysis were conducted to determine whether there is a difference in naturalized plant species and naturalization Index by year, region, altitude, population density, GDP, and the ratio of forest to area. There was a correlation between the items such as year, region, alti-tude, population density, GDP, the ratio of forest to area and the number and naturalization Index of naturalized plants, and the greatest impact on the naturalized plant species and naturalization Index. Curve estimation re-gression, multiple regression, and dummy variable regression were performed to find out which items are causing the problem. Through this research, it is thought that the naturalization Index predicted by this study can be used for the issue of Permit on Exclusive use of inter-mountain area altitude standard, which is operated under the Act on Planning, and Use of National Territory, and the Mountain Site Management Act. The naturalization Index predicted by this study can be used as basic data for setting the upper limit of Permit on Exclusive use of inter-mountain area, or for studying environmental change, or for setting various indicators.
참고문헌 (11)
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