Factors influencing wild boar damage in Taohongling National Nature Reserve in China: a model approach

Conflicts between humans and wildlife, especially wild boar (Sus scrofa), have caused serious problems across the world in recent years. It is necessary to effectively control wild boar agricultural damage that may be influenced by many factors. In this study, we collected data on agricultural damage caused by wild boars from November 2009 to October 2010 using field surveys and social interviews in Taohongling National Nature Reserve of Jiangxi Province, China. We constructed models using binary logistic regression analysis to predict damage risks and to identify the factors influencing damage risks. About 8.1 % of croplands were damaged by wild boars, and the damage to rice, cotton, and other crops were not distributed based on their respective availability as shown by the result of a chi-square goodness-of-fit test. Five factors (Japanese silvergrass, soil conditions, terrain, distances to settlements, and water sources) were explained in a model based on damage area (area-based model) with the prediction accuracy being 72.1 %. In addition to these five factors, one additional factor (i.e. distance to forest edge) was retained in a model based on damage frequency (frequency-based model) with the prediction accuracy being 83.1 %. Caution is needed when we apply these two models to predict boar damage to crops, and it is recommended that both models be used in combination to predict the damage probabilities more accurately.