Building a reference indicator model using co-kriging interpolation to determine the geographical origin of the flighted spongy moth complex in China

Using stable isotopes to detect and analyze the geographical origin of insects represents an important traceability technology, which requires a rich isotope database. In this study, we representatively sampled the Chinese provinces where flighted spongy moth complex (FSMC) has been reported and, for the first time, used co-kriging interpolation to predict the distribution patterns of FSMC delta 13C values in the main distribution areas. From 2020 to 2022, we set up 60 traps in 12 provinces and cities in China and collected 795 FSMCs. Then, 6 main climatic factors were obtained by multi-collinearity screening from 21 types of meteorological data collected at the sample plots, and a correlation analysis was carried out by combining longitude, latitude, and altitude data with the delta 13C values of FSMC. Next, we performed a co-kriging interpolation using the 2 climatic factors with the highest correlation (isothermality and altitude) and the delta 13C values of FSMC. A cross-validation was performed to systematically test 11 candidate models and select the best semi-variogram model ("Exponential"), which was then used to build a co-kriging interpolation model. The geographical distribution patterns of the FSMC delta 13C values obtained from the 2 interpolation models (i.e., interpolated with isothermality and altitude, respectively) were almost the same. Moreover, the delta 13C values varied significantly at the regional scale, showing regular changes in spatial distribution. Overall, the reference indicator map of the delta 13C values generated from stable isotopes can be used to greatly improve the efficiency of discrimination analyses on the geographical origin of FSMC. From 2020 to 2022, we set up 60 traps in 12 provinces and cities in China, and collected 795 flighted spongy moth complexes (FSMCs). A co-kriging interpolation was performed using the 2 climatic factors with the highest correlation (i.e., isothermality and altitude) and the delta 13C values of FSMCs. The reference indicator map shows that the delta 13C values of FSMC varied significantly at the regional scale. # image