Plotting receiver operating characteristic and precision-recall curves from presence and background data

    The receiver operating characteristic (ROC) and precision-recall (PR) plots have been widely used to evaluate the performances of species distribution models. Plotting the ROC/PR curves requires a traditional test set with both presence and absence data (namely PA approach), but species absence data are usually not available in reality. Plotting the ROC/PR curves from presence-only data while treating background data as pseudo absence data (namely PO approach) may provide misleading results. In this study we propose a new approach to calibrate the ROC/PR curves from presence and background data with user-provided information on a constant c, namely PB approach. Here c defines the probability that species occurrence is detected (labeled), and an estimate of c can also be derived from the PB-based ROC/PR plots given that a model with good ability of discrimination is available. We used five virtual species and a real aerial photography to test the effectiveness of the proposed PB-base...