Research highlights: Formica rufa
is used widely for biocontrol in Turkish forests. Although ecological characteristics of red wood ant habitats are well known, the statistical significance of these characteristics and their effects on nest transplantation success are largely unknown. Having such knowledge on a local scale, however, can help to predict the success of a scheduled transplantation effort, and can prevent loss of time and money. Background and objectives: In the present study, we used nest transplantation data from southern Turkey to determine habitat parameters that have a significant impact on nest survival, and to investigate possibility of predicting transplantation success from habitat parameter data. Materials and methods: Algorithms of data mining are widely used in agricultural and forestry applications for a wide range of tasks. In the present study, we used descriptive statistics to summarize the transplantation profile according to six habitat parameters (altitude, aspect, canopy closure, landform, nest substrate, and slope). We also used classification, a data mining approach, with two of its methods (decision tree and naïve Bayes) to determine the most important habitat parameters for nest survival and predict nest transplantation success in southern Turkey. Results: We found that altitude, aspect, and canopy closure were the most important factors affecting transplantation success. We also show that classification methods can be used in not only classifying, but also predicting the success rate of future transplantations. Thus, we show that the possibility of success for a given area can be predicted when certain parameters are known. Conclusions: This method can assist biological control practitioners in planning biocontrol programs and selecting favorable spots for red wood ant nest transplantation.
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