Effect of types of meteorological data on species distribution predicted by the CLIMEX model using an example of Lycorma delicatula (Hemiptera: Fulgoridae)

Climate has been used as a main variable in species distribution model, suggesting that the type of meteorological data can affect the predictive range of a target species. This study was to investigate the effect of meteorological data on the prediction of the potential distribution of a species in the CLIMEX model. We constructed three different types of meteorological data to be inserted into the CLIMEX model to predict the climatic suitability of the spotted lanternfly [Lycorma delicatula (Hemiptera: Fulgoridae)] in South Korea: (1) minimum–maximum data (Y-data), (2) annual average data (AY-data), and (3) 30-year long-term average data (A-data). As a result, the climatic suitability represented by the Ecoclimatic Index (EI) was significantly different in the Y-data compared with the other data sets because of the extreme winter condition in which they were recorded. In contrast, the AY- and A-data sets showed similar climatic suitability, but the AY-data showed slightly higher Ecoclimatic Index values than the A-data. It is conclusive that the AY- and A-data sets were suitable for evaluating annual variations by the years of data collection and current potential distribution, respectively, whereas the Y-data could be used for simulation under extreme climate conditions for a conservative assessment. Keywords: Climatic suitability, CLIMEX, Meteorological data, Potential distribution

Abstract licence: CC BY-NC-ND

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