Objective： American ginseng is a medicinal plant with large market demands,however,its producing areas are shrinking because of the continuous cropping obstacles in China.Therefore,it is urgent to establish a suitabl...Objective： American ginseng is a medicinal plant with large market demands,however,its producing areas are shrinking because of the continuous cropping obstacles in China.Therefore,it is urgent to establish a suitable model to determine the new producing areas.Here we evaluated and predicted the suitable areas of American ginseng using the maximum entropy model（Max Ent）.Methods： Based on the 37 environmental variables over thirty years from 1970 to 20 0 0 and 226 global distribution points of American ginseng,Max Ent was used to determine the global ecological suitable areas for American ginseng.The Receiver Operating Curve（ROC）was used to evaluate the model prediction accuracy.Meanwhile,an innovative ecological variable,the precipitation–temperature ratio,was established to indicate the climate characteristic in the American ginseng suitable areas based on the monthly precipitation and temperature.Results： The potential ecological suitable areas of American ginseng were primarily in Appalachian Mountain in America and Changbai Mountain in China,about in the range of 35 °N–50 °N,60 °W–120 °W and 35 °N–50 °N,110 °E–145 °E,respectively,including the United States,Canada,China,North Korea,South Korea,Russia and Japan.South Korea and Japan were the potential producing regions.The precipitation–temperature ratios were stable at（0.22,0.56）of the vigorous growth period（April–October）in the best suitable areas of American ginseng,serving as characteristic parameters to optimize the prediction model.The model showed that the common soil parameters were pH 4.5–7.2,Base Saturation（BS）above 80%,Cation Exchange Capacity（CEC）10–20 cmol/kg,organic carbon（OC）〈 1.4%,and the soil types were sandy loam or loam.Conclusion： An optimized Max Ent model was established to predict the producing area for American ginseng that needed to be validated by a field test.展开更多
We present a GIS-based habitat suitability index(HSI) model to identify suitable areas for Zostera marina L. restoration in the subtidal zone of Xiaoheishan Island. The controlling factors in the model,in order of imp...We present a GIS-based habitat suitability index(HSI) model to identify suitable areas for Zostera marina L. restoration in the subtidal zone of Xiaoheishan Island. The controlling factors in the model,in order of importance,are Secchi depth,sediment composition,water temperature,salinity,current velocity,water depth and nutrient quality. Specific factor piecewise functions have been used to transform parameter values into normalized quality indexes. The weight of each factor was defined using expert knowledge and the analytic hierarchy process(AHP) method. All of the data thus obtained were interpolated using the inverse distance weighted(IDW) interpolation method to create maps for the entire region. In this study,the analysis of habitat suitability in the subtidal zone of Xiaoheishan Island was conducted for four seasons. According to the GIS-based HSI model,the optimal habitat of Z ostera marina L. appears in spring,although habitat remains suitable all year round. On the whole,the optimum site for eelgrass restoration is located in the eastern region,followed by the western and southern regions. We believe that the GIS-based HSI model could be a promising tool to select sites for Z ostera marina L. restoration and could also be applicable in other types of habitat evaluation.展开更多
[Objectives]We intend to conduct a study to predict habitat suitability and geographic distribution of Rubia cordifolia L.,to find the most suitable ecological environment for its growth,and to provide a theoretical b...[Objectives]We intend to conduct a study to predict habitat suitability and geographic distribution of Rubia cordifolia L.,to find the most suitable ecological environment for its growth,and to provide a theoretical basis for the development and cultivation of R.cordifolia L.industry.[Methods]Based on the environmental factors and the occurrence data,we predicted the potential geographic distribution of R.cordifolia L.in China by combining the MaxEnt model and ArcGIS.[Results]The training set and test set AUC were respectively 0.963 and 0.946,indicating that the MaxEnt model predicted well.The wettest monthly precipitation,precipitation in July,precipitation of driest season,and average monthly temperature in September and April were the dominant environmental factors affecting the distribution of R.cordifolia L.The highly habitable areas were mainly concentrated in central,eastern and northern China.[Conclusions]The results of this study can be used as a reference for the development of R.cordifolia L.industry in related areas.展开更多
基金supported by National Natural Science Foundation of China (81473304)National Science and Technology Support Program (2015BAI05B01)
文摘Objective： American ginseng is a medicinal plant with large market demands,however,its producing areas are shrinking because of the continuous cropping obstacles in China.Therefore,it is urgent to establish a suitable model to determine the new producing areas.Here we evaluated and predicted the suitable areas of American ginseng using the maximum entropy model（Max Ent）.Methods： Based on the 37 environmental variables over thirty years from 1970 to 20 0 0 and 226 global distribution points of American ginseng,Max Ent was used to determine the global ecological suitable areas for American ginseng.The Receiver Operating Curve（ROC）was used to evaluate the model prediction accuracy.Meanwhile,an innovative ecological variable,the precipitation–temperature ratio,was established to indicate the climate characteristic in the American ginseng suitable areas based on the monthly precipitation and temperature.Results： The potential ecological suitable areas of American ginseng were primarily in Appalachian Mountain in America and Changbai Mountain in China,about in the range of 35 °N–50 °N,60 °W–120 °W and 35 °N–50 °N,110 °E–145 °E,respectively,including the United States,Canada,China,North Korea,South Korea,Russia and Japan.South Korea and Japan were the potential producing regions.The precipitation–temperature ratios were stable at（0.22,0.56）of the vigorous growth period（April–October）in the best suitable areas of American ginseng,serving as characteristic parameters to optimize the prediction model.The model showed that the common soil parameters were pH 4.5–7.2,Base Saturation（BS）above 80%,Cation Exchange Capacity（CEC）10–20 cmol/kg,organic carbon（OC）〈 1.4%,and the soil types were sandy loam or loam.Conclusion： An optimized Max Ent model was established to predict the producing area for American ginseng that needed to be validated by a field test.
基金Supported by the Key Laboratory of Marine Ecology and Environmental Science and Engineering,SOA(No.MESE-2013-01)the National Natural Science Foundation of China(No.41206102)the National Marine Public Welfare Research Project(No.201305009)
文摘We present a GIS-based habitat suitability index(HSI) model to identify suitable areas for Zostera marina L. restoration in the subtidal zone of Xiaoheishan Island. The controlling factors in the model,in order of importance,are Secchi depth,sediment composition,water temperature,salinity,current velocity,water depth and nutrient quality. Specific factor piecewise functions have been used to transform parameter values into normalized quality indexes. The weight of each factor was defined using expert knowledge and the analytic hierarchy process(AHP) method. All of the data thus obtained were interpolated using the inverse distance weighted(IDW) interpolation method to create maps for the entire region. In this study,the analysis of habitat suitability in the subtidal zone of Xiaoheishan Island was conducted for four seasons. According to the GIS-based HSI model,the optimal habitat of Z ostera marina L. appears in spring,although habitat remains suitable all year round. On the whole,the optimum site for eelgrass restoration is located in the eastern region,followed by the western and southern regions. We believe that the GIS-based HSI model could be a promising tool to select sites for Z ostera marina L. restoration and could also be applicable in other types of habitat evaluation.
文摘[Objectives]We intend to conduct a study to predict habitat suitability and geographic distribution of Rubia cordifolia L.,to find the most suitable ecological environment for its growth,and to provide a theoretical basis for the development and cultivation of R.cordifolia L.industry.[Methods]Based on the environmental factors and the occurrence data,we predicted the potential geographic distribution of R.cordifolia L.in China by combining the MaxEnt model and ArcGIS.[Results]The training set and test set AUC were respectively 0.963 and 0.946,indicating that the MaxEnt model predicted well.The wettest monthly precipitation,precipitation in July,precipitation of driest season,and average monthly temperature in September and April were the dominant environmental factors affecting the distribution of R.cordifolia L.The highly habitable areas were mainly concentrated in central,eastern and northern China.[Conclusions]The results of this study can be used as a reference for the development of R.cordifolia L.industry in related areas.
