Time‐course in attractiveness of pheromone lure on the smaller tea tortrix moth: A generalized additive mixed model approach

Abstract

Long-term pest insect monitoring in agriculture and forestry has advanced population ecology. However, the discontinuation of research materials such as pheromone lure products jeopardizes data collection continuity, which constrains the utilization of the industrial datasets in ecology. Three pheromone lures against the smaller tea tortrix moth Adoxophyes honmai Yasuda (Lepidoptera; Tortricidae) were available but one was recently discontinued. Hence, a statistical method is required to convert data among records of moths captured with different lures. We developed several generalized additive mixed models (GAMM) separating temporal fluctuation in the background male density during trapping and attenuation of lure attractiveness due to aging or air exposure after settlement. We collected multisite trap data over four moth generations. The lures in each of these were unsealed at different times before trap settlement. We used cross-validation to select the model with the best generalization performance. The preferred GAMM had nonlinear density fluctuation terms and lure attractiveness decreased exponentially after unsealing. The attenuation rates varied among lures. A light trap dataset near the pheromone traps was a candidate for a male density predictor. Nevertheless, there was only a weak correlation between trap yields, suggesting the difficulty of data conversion between the traps differing in attraction mechanisms.

Time Series Analysis of Land Cover Change in Dry Mountains: Insights from the Tajik Pamirs

“…To accommodate all these challenges, we decided to use generalized additive mixed models (GAMMs, [86]) for our analyses of the time series in this study. GAMMs have been applied successfully in the past for analyses of time series in ecological studies [87][88][89][90][91] but have rarely been used in the context of the time series analysis of satellite images. Lee et al [83] used GAMMs in a post-classification analysis.…”