RCP 시나리오에 따 른 해양교란생물 유령멍게 (Ciona robusta)의 서식지 분포 예측
Prediction of the Suitable Habitats of Marine Invasive Species, Ciona robusta based on RCP Scenarios
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초록
The active development of the global marine trade industries has been known to increase the inflows of marine invasive species and harmful organisms into the ecosystem, and the marine ecological disturbances. One of these invasive species, Ciona robusta, has now spread to the Korea Strait, the East Sea, and Jeju Island in connection with the climate change but not the Yellow Sea in Korea. Currently, the spread and distribution of C. robusta is increasingly damaging aquaculture and related facilities. Therefore, this study aims to identify the spread of C. robusta and potential habitats and to secure a data for the prevention of effective management measures due to climate change as well as damage the reduction in future through the prediction of spread. We used environmental variables in BioOracle. Also, the potential habitat and distribution of C. robusta was predicted using MaxEnt, a species distribution model. Two different RCP scenarios (4.5 and 8.5) were specified to predict the future distributions of C. robusta. The results showed that the biggest environmental factor affecting the distribution of C. robusta was the salinity as well as the highest distribution and potential habitats existent in the East Sea and around Jeju Island.
Abstract
The active development of the global marine trade industries has been known to increase the inflows of marine invasive species and harmful organisms into the ecosystem, and the marine ecological disturbances. One of these invasive species, Ciona robusta, has now spread to the Korea Strait, the East Sea, and Jeju Island in connection with the climate change but not the Yellow Sea in Korea. Currently, the spread and distribution of C. robusta is increasingly damaging aquaculture and related facilities. Therefore, this study aims to identify the spread of C. robusta and potential habitats and to secure a data for the prevention of effective management measures due to climate change as well as damage the reduction in future through the prediction of spread. We used environmental variables in BioOracle. Also, the potential habitat and distribution of C. robusta was predicted using MaxEnt, a species distribution model. Two different RCP scenarios (4.5 and 8.5) were specified to predict the future distributions of C. robusta. The results showed that the biggest environmental factor affecting the distribution of C. robusta was the salinity as well as the highest distribution and potential habitats existent in the East Sea and around Jeju Island.
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