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Mating disruption tactics involve the deployment of pheromones to interfere with mate finding behaviors in insect populations. This management strategy is the dominant one used against expanding gypsy moth populations in the United States, and historically it has been assumed to be most effective against low-density populations. Operationally, mating disruption is used in areas where the season-long trap catch is <30 males/trap, however the maximum population density at which mating disruption is effective remains unknown. We analysed historical gypsy moth mating disruption treatment data from 2000 to 2010, and used this information to guide the mating disruption field studies conducted from 2012 to 2015 against artificially-created populations of various densities, from 0 to 116 males/trap/day. We observed that mating disruption tactics at a dose of 15 g AI/ha were effective against gypsy moth populations with a season-long trap catch of at least 115 males/trap. This research highlights the utility of mating disruption in higher gypsy moth densities than what is currently recommended in management programs. [ABSTRACT FROM AUTHOR]

An accurate quantitative relationship between key characteristics of an insect population, such as season-long and peak abundances, can be very useful in pest management programs. To the best of our knowledge, no such relationship has yet been established. Here we establish a predictive linear relationship between insect catch Mpw during the week of peak abundance, the length of seasonal flight period, F (number of weeks) and season-long cumulative catch (abundance) A = 0.41MpwF. The derivation of the equation is based on several general assumptions and does not involve fitting to experimental data, which implies generality of the result. A quantitative criterion for the validity of the model is presented. The equation was tested using extensive data collected on captures of male gypsy moths Lymantria dispar (L.) (Lepidoptera: Erebidae) in pheromone-baited traps during 15 years. The model was also tested using trap catch data for two species of mosquitoes, Culex pipiens (L.) (Diptera: Culicidae) and Aedes albopictus (Skuse) (Diptera: Culicidae), in Gravid and BG-sentinel mosquito traps, respectively. The simple, parameter-free equation approximates experimental data points with relative error of 13% and R2 = 0.997, across all of the species tested. For gypsy moth, we also related season-long and weekly trap catches to the daily trap catches during peak flight. We describe several usage scenarios, in which the derived relationships are employed to help link results of small-scale field studies to the operational pest management programs. [ABSTRACT FROM AUTHOR]

Simple Summary: The importance of conservation and pest management programs cannot be overstated as climate change, loss of biodiversity, and biological invasions are on the rise. Such programs often rely on traps for population detection and monitoring, assigning management and conservation tactics, and evaluating treatment efficacies. In this paper, we propose a universal method for any insect trap system to estimate the most probable absolute population density and its statistical bounds from a single trap catch. This approach will help take insect detection and monitoring to a new, rigorously quantitative level. Knowledge of insect population density is crucial for establishing management and conservation tactics and evaluating treatment efficacies. Here, we propose a simple and universal method for estimating the most probable absolute population density and its statistical bounds. The method is based on a novel relationship between experimentally measurable characteristics of insect trap systems and the probability to catch an insect located a given distance away from the trap. The generality of the proposed relationship is tested using 10 distinct trapping datasets collected for insects from 5 different orders and using major trapping methods, i.e., chemical-baited traps and light. For all datasets, the relationship faithfully ( R ¯ = 0.91) describes the experiment. The proposed approach will take insect detection and monitoring to a new, rigorously quantitative level. It will improve conservation and management, while driv-ing future basic and applied research in population and chemical ecology. [ABSTRACT FROM AUTHOR]

Simple Summary: Gypsy moth is one of the most devastating forest pests in the Eastern USA. In this paper, we derive a simple formula to interpret catches in monitoring moth traps deployed by management programs. Estimates of absolute pest population density are critical to pest management programs but have been difficult to obtain from capture numbers in pheromone-baited monitoring traps. In this paper, we establish a novel predictive relationship for a probability (spTfer(r)) of catching a male located at a distance r from the trap with a plume reach D. s p T f e r r = s p T f e r 0 1 + r D 2 ,   r ≤ R m a x 0 ,   r > R m a x , where spTfer(0) is the probability of catching an insect located next to the trap and Rmax is the maximum dispersal distance for the insect during the trapping period. The maximum dispersal distance for gypsy moth is known to be 1600 m. The probability of catching a gypsy moth male located next to a United States Department of Agriculture (USDA) milk carton pheromone-baited trap is 0.37, the overall probability of catching a male from the entire trapping area (Tfer) of ~800 ha is 0.0008, and plume reach of this trap is D = 26 ± 3 m. The equation for spTfer(r) is used to derive statistical upper and lower bounds (95% confidence interval) on the population density for the given value of a single trap catch. This combination of trap parameters appears to produce an effective trap: even a catch of 1 male provides meaningful lower and upper bounds on absolute population density. Applications in the management programs are discussed, and a look-up table is provided to translate the catches in USDA milk carton pheromone-baited traps to absolute population bounds, which can help design better management strategies. [ABSTRACT FROM AUTHOR]