Pollinator biological traits and ecological interactions mediate the impacts of mosquito-targeting malathion application

Abstract

Mosquito adulticides are perceived by the public as detrimental to nontarget arthropods, contributing to declines of native and beneficial insects. However, the actual impact of adulticides on nontarget arthropods in nature needs to incorporate biological and ecological elements. Here, we investigated the effect of biological/behavioral traits (butterfly roosting at different heights, roosting in sites underneath foliage, bumblebee hive usage) and interactions (parasitism, predation) of pollinators (butterflies and bumblebees) that could mediate the impacts of malathion application in manipulative semi-field experiments in Florida, USA. Roosting height from the spray route had a significant negative relationship with mortality of butterflies treated with ULV malathion, with high survival at the highest roosting height (7 m), but butterflies roosting among vegetation did not have higher survival. Bumblebees with hive access had significantly higher survival than bumblebees without hive access. Host plants treated with ULV malathion significantly reduced parasitism of monarch eggs by Trichogramma platneri, but increased predation of monarch caterpillars by Polistes paper wasps. These data provide insight into the realistic impacts of adulticide applications on pollinators in nature which will enable mosquito control districts to better limit nontarget effects of adulticide treatments and may help to address concerns related to potential nontarget effects.

Figure 1

Effect of malathion on predation of monarch (D. plexippus) caterpillars. The rate of predation by aerial predators on monarch caterpillars (N = 4 per plant and N = 160 total) feeding on host plants treated with malathion was assessed at 5, 21 and 25 h after treatment. None of the caterpillars on host plants under mesh laundry hampers were predated. Bars indicate the mean number of caterpillars killed or taken by treatment group. Asterisks indicate significant differences between groups, using GLM with Poisson distribution (p < 0.05).

Figure 2

Effect of malathion on parasitism of monarch (D. plexippus) eggs. Rate of parasitism by T. platneri on monarch eggs affixed to host plant leaves (N = 5 per plant and N = 135 total) treated with malathion via truck-mounted sprayer at the maximum label rate. Asterisks indicate significant differences between groups (p < 0.05), using GLM with the Poisson distribution.

Figure 3

Effect of malathion on bumblebee (Bombus impatiens) with and without natural refugium. Survival rate of bumblebees (N = 671 total) with and without refugia (hive) at 50 m distance from truck-mounted sprayer applying malathion ULV spray at the maximum label rate. Asterisks indicate significant differences between groups (p < 0.05), using GLM with likelihood ratio test.

Figure 4

Effect of malathion on adult butterflies (N = 184 total) at different roosting heights and distances from adulticide spray route. Various species of butterfly (Nymphalidae, Pieridae and Papilionidae) were included. Asterisks indicate significant differences between groups (p < 0.05), using GLM with binominal distribution.

Figure 5

Effect of malathion on development of monarch (D. plexippus) caterpillars. Mean mass change of small (N = 87), medium (N = 80), or large-sized (N = 82) monarch caterpillars that fed on host plant leaves treated with malathion over 5 days. Small: < 0.07 g; Medium: 0.07–0.19 g; Large: 0.19–0.9 g. Asterisks indicate significant differences between groups (p < 0.05), using “indicate test”.

Figure 6

Effect of distance and size on mortality of malathion on monarch (D. plexippus) caterpillars. Mortality was assessed over 5 days on small (N = 87), medium (N = 80) and large (N = 82) caterpillars that fed on host plant leaves treated with malathion at 50 and 75 m distances from a truck-mounted sprayer applying a malathion ULV spray at the maximum label rate. Asterisks indicate significant differences between groups (p < 0.05), using GLM with the Poisson distribution.