Citizen science is a powerful tool that can be used to resolve the problems of introduced species. An amateur naturalist and author of this paper, S. Watanabe, recorded the total number of Limax maximus (Limacidae, Pulmonata) individuals along a fixed census route almost every day for two years on Hokkaido Island, Japan. L. maximus is an invasive slug considered a pest species of horticultural and agricultural crops. We investigated how weather conditions were correlated to the intensity of slug activity using for the first time in ecology the recently developed statistical analyses, Bayesian regularization regression with comparisons among Laplace, Horseshoe and Horseshoe+ priors for the first time in ecology. The slug counts were compared with meteorological data from 5:00 in the morning on the day of observation (OT- and OD-models) and the day before observation (DBOD-models). The OT- and OD-models were more supported than the DBOD-models based on the WAIC scores, and the meteorological predictors selected in the OT-, OD- and DBOD-models were different. The probability of slug appearance was increased on mornings with higher than 20-year-average humidity (%) and lower than average wind velocity (m/s) and precipitation (mm) values in the OT-models. OD-models showed a pattern similar to OT-models in the probability of slug appearance, but also suggested other meteorological predictors for slug activities; positive effect of solar radiation (MJ) for example. Five meteorological predictors, mean and highest temperature (°C), wind velocity (m/s), precipitation amount (mm) and atmospheric pressure (hPa), were selected as the effective factors for the counts in the DBOD-models. Therefore, the DBOD-models will be valuable for the prediction of slug activity in the future, much like a weather forecast.
Keywords: Agricultural pest; Bayesian regularization regression; Citizen science; Horseshoe; Horseshoe+; Introduced species; Laplace; Multicollinearity.
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