Habitat suitability evaluation of ancient ginkgo trees in Changsha based on random forest and MaxEnt model
[Objective]Ancient ginkgo trees in cities are important natural resources and cultural heritage with significant ecological,historical,landscape and economic values.However,rapid urbanization and human activities leading to drastic changes in urban ecosystem functions have inevitably caused problems in the growth and conservation of ginkgo trees in cities.The study was conducted with a view to realizing the assessment of the diameter at breast height(DBH),height of trees and habitat suitability of ginkgo trees in Changsha city,and to provide a reference for the conservation of ginkgo trees in Changsha city.[Method]160 ginkgo trees over 100 years old in Changsha city,Hunan province,China,were used as the research objects.Based on the provincial and municipal forest inventory data combined with the field survey data,the modeling parameters of 160 ginkgo trees were collected,including age,elevation,slope direction,slope,average annual precipitation,soil type,and average crown width,etc.,and the data were categorized according to the ratio of training:validation=4:1.After the parameters were processed by Pearson correlation screening and importance ranking,the growth model of chest diameter and tree height of Ginkgo biloba was established by using multiple linear regression,support vector machine regression and random forest regression methods.On this basis,the habitat suitability of ginkgo trees was evaluated using the maximum entropy weight model(MaxEnt),and mapping of suitable areas for ginkgo planting in Changsha city was carried out.[Result]The study showed that the random forest regression model of ginkgo diameter at breast height and tree height had the best fitting effect,in which the coefficient of determination of the random forest model of diameter at breast height was the highest R2 of 0.86,and the root mean squared error(RMSE)was 2.67,which was higher than that of the support vector machine regression(R2 of 0.72)and the multivariate linear regression(R2 of 0.79),and that of the random forest model of tree height was the highest R2 of 0.82,RMSE of 13.09,and R2 of 13.09,respectively.The RMSE of the random forest model for tree height was 13.09,which was higher than that of the support vector machine regression method(R2 of 0.59)and the multiple linear regression method(R2 of 0.78).[Conclusion]The study showed that the growth of diameter at breast height was mainly affected by elevation,slope and average annual rainfall,while tree height was more affected by tree age,elevation and average annual rainfall.The results of this study can provide a scientific basis for planting ginkgo,replenishing the number of ginkgo trees and maintaining the sustainability of ginkgo trees in Changsha city in the future.
ancient Ginkgo bilobahabitat suitabilityrandom forestMaxEntChangsha
NETL
NSTL
万方数据
