Sublethal and transgenerational effects of lufenuron on the biological traits of Panonychus citri (McGregor) (Acari: Tetranychidae)

The citrus red mite, Panonychus citri (McGregor), is a globally important pest that has developed severe resistance to various pesticides. Lufenuron has been widely used in the control of the related pests in citrus orchard ecosystem. In this study, the susceptibilities of egg, larva, deutonymph and female adult of P. citri to lufenuron was determined, and the LC50 values were 161.354 mg/L, 49.595 mg/L, 81.580 mg/L, and 147.006 mg/L, respectively. Life-table analysis indicated that the fecundities were significantly increased by 11.86% and 26.84% after the mites were treated with LC20 concentrations of lufenuron at the egg or deutonymph stages, respectively. After eggs were treated with lufenuron, the immature stage and longevity were also affected, and resulted in a significant increase in r, R0 and λ. After exposure of female adults to LC20 of lufenuron, the fecundity and longevity of F0 generation significantly decreased by 31.99% and 10.94%, respectively. Furthermore, the expression level of EcR and Vg was significantly inhibited upon mites was treated with lufenuron. However, lufenuron exposure has a positive effect on fecundity and R0 in F1 generation, the expression of all reproduction-related genes was significantly up-regulated. In conclusion, there was a stimulating effect on the offspring population. Our results will contribute to the assessment of the resurgence of P. citri in the field after the application of lufenuron and the development of integrated pest control strategies in citrus orchards.

The utility of joinpoint regression for estimating population parameters given changes in population structure

The method of joinpoint regression has been used in numerous domains to assess changes in time series data, including such things as cancer mortality rates, motor vehicle collision mortalities, and disease risk. To help improve estimation of population parameters for use in ecological risk assessment and management, we present a simulation and analysis to describe the utility of this method for the ecological domain. We demonstrate how joinpoint regression can accurately identify if the population structure changes based on time series of abundance, as well as identify when this change occurs. In addition, we compare and contrast population parameter estimates derived through joinpoint and surplus production methods to those derived from standard surplus production methods alone. When considering a change point at 32 years (out of a 64 year simulation), the joinpoint regression model was able, on average, to estimate a joinpoint time of 32.31 years with a variance of 6.82 and 95% confidence interval for the mean relative bias of (0.0085, 0.0112). The model was able to consistently estimate population parameters, with variance of these estimations decreasing as the change in these population parameters increased. We conclude that joinpoint regression be added to the list of methods employed by those who assess ecological risk to allow for a more accurate and complete understanding of population dynamics.