Predicting assam tea distribution in upper northern thailand using species distribution models

Abstract

The aim of this study is to build species distribution models and find factors affecting Assam tea distribution in upper Northern Thailand. The data were analyzed by the logistic regression of 185 records of Assam tea and generated pseudo-absence data using the two-step method. The re-sampling technique used the bootstrapping method to interpolate small sample size problems, and the k-fold cross-validation technique was used to find the best testing data set. Furthermore, statistical values (average value, standard deviation and coefficient of variation) were used to find the best final model. From the effective predictor variables at a significance level of 0.05: aspect, annual mean temperature, mean temperature of the wettest quarter, annual precipitation, precipitation of the wettest month and precipitation of the driest quarter all had positive effects upon model. Conversely: distance from the river, minimum temperature of the warmest month, precipitation of the driest month and precipitation of the wettest quarter all had negative effects upon model. Furthermore, the most suitable areas were found to be predominantly in the north-northwest region of upper Northern Thailand.