Selective insecticides secure natural enemies action in cotton pest management

Ecotoxicology and Environmental Safety 184 (2019) 109669

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Selective insecticides secure natural enemies action in cotton pest management

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Anderson V.A. Machado, Denner M. Potin, Jorge B. Torres∗, Christian S.A. Silva Torres Departamento de Agronomia/Entomologia, Universidade Federal Rural de Pernambuco, Av. Dom Manoel de Medeiros S/N, Dois Irmãos, Recife, PE, 52171-900, Brazil

A R T I C LE I N FO

A B S T R A C T

Keywords: Biological control Nontarget effect Predatory insects Selective insecticide Sentinel prey

Cotton hosts a variety of arthropod pests requiring intensive control mostly with insecticides, which in turn may impact beneficial insects and the environment. Therefore, insect control in cotton fields preconizes the use of selective insecticides that offer pest control but conserve natural enemies. In this work, we measured the impact of recommended insecticides on the abundance of predatory insects and predation upon sentinel preys in the field. Further, the survival of four key selected predatory insects of cotton ecosystem, representing chewing and sucking feeding habits and different pest species attacked [Chrysoperla externa Hagen, Eriopis connexa (Germar), Podisus nigrispinus (Dallas) and Orius insidiosus (Say)], were assessed when exposed to the dried residues of the tested insecticides. Mortality of sentinel prey caused by natural enemies was higher in areas treated with selective insecticides relative to the non-selective ones, and most of time similar to the untreated areas. Furthermore, areas treated with non-selective insecticides experienced prolonged impact between sprays depending on the insecticide applied. Seasonal abundance of predatory insects was 2× greater in fields under selective and untreated fields compared to those under non-selective recommendation. Survival of predators exposed to the dried residues of the selective insecticides pymetrozine, chlorantraniliprole, pyriproxyfen, and cyantraniliprole were greater than when exposed to the non-selective lambda-cyhalothrin, malathion, dimethoate, and thiamethoxam. Among the non-selective insecticides, malathion and dimethoate exhibited shorter residual time compared to the thiamethoxam and lambda-cyhalothrin + thiamethoxam. Therefore, the recommendation of selective insecticides provides benefits for cotton pest management by maintaining the action of the natural enemies present in the field.

1. Introduction Pest control in cotton fields worldwide is mostly achieved by intensive insecticide use; however, the premise of cotton integrated pest management (IPM) is the recommendation of low risk insecticides to reduce impacts on beneficial arthropods and the environment. This poses a challenge for IPM practitioners in tropical regions. For instance, Brazilian cotton crop harbors more than 250 arthropod herbivores (Silva et al., 1968; Sujii et al., 2006), and despite variation across fields, several species are considered pests because of their potential to reduce cotton yield, if proper control measures are not adopted. Therefore, among the control practices available for cotton IPM in tropical regions, chemical control with recommendation of broad-spectrum insecticides (hereafter non-selective) is widely adopted as they offer control of different pest species simultaneously (Torres et al., 2003a). More than 300 insecticide formulations belonging to 72 active ingredients are

registered to spray cotton fields in Brazil (AGROFIT , 2017). In contrast, those registered products are not used by growers in practice, and only a few insecticides are recognized to provide efficient control. Therefore, these few active ingredients are regularly used without proper insecticide resistance management and observations about their impact on biological control services. These products include neonicotinoids, pyrethroids, organophosphates, methylcarbamate, and pyrroles, which are non-selective insecticides used in foliar application. However, insect growth regulators, spinosyns and diamides are registered and can be recommended against cotton pests in Brazil. These products are considered of low risk to natural enemies and the environment, compared to old non-selective insecticides (Naranjo et al., 2004; Torres and Bueno, 2018; Barros et al., 2018; Rolim et al., 2019). Many problems are related to non-selective insecticide use, and one of them is the acute toxicity against natural enemies (Tillman and Mulrooney, 2000; Elzen, 2001; Roubos et al., 2014). In addition, for

∗ Corresponding author. Departamento de Agronomia – Entomologia Universidade Federal Rural de Pernambuco Rua Dom Manoel de Medeiros, s/n, Dois Irmãos, 52171-900, Recife, PE, Brazil. E-mail address: [email protected] (J.B. Torres).

https://doi.org/10.1016/j.ecoenv.2019.109669 Received 2 June 2019; Received in revised form 6 September 2019; Accepted 9 September 2019 Available online 16 September 2019 0147-6513/ © 2019 Elsevier Inc. All rights reserved.

Ecotoxicology and Environmental Safety 184 (2019) 109669

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and the abundance of predator insect surveyed on cotton plant canopy under two insecticide recommendations. Moreover, residual toxicity of insecticide on four key predator species was evaluated in the laboratory after plants cultivated in the greenhouse were treated with the recommended insecticides used in our cotton plots. This last experiment was run in the Biological Control Laboratory and greenhouse of the Universidade Federal Rural de Pernambuco (UFRPE), Recife, PE, Brazil. The field test was set up in a commercial cotton field located in Algodão do Manso, Frei Miguelinho County, Pernambuco State (07° 55′09.3″ S and 35° 51′45.6″ W), Brazil. This area has been cultivated under the standard agronomic practices commonly used for growing cotton in the semiarid region since 2013, with 80–90 cm between rows and 5 to 6 plants per row meter. During the 2018 season, the study area consisted of 18 ha of cotton cultivated with the Bt variety IMA 5675BGIIRF and with refuge area cultivated with the non-Bt variety IMA 2106 GL. Moreover, both cotton varieties are resistant to the herbicide glyphosate allowing chemical weed control. The field was seeded on May 4 and harvested during the last week of September 2018.

those insecticides lacking acute toxicity and considered selective to natural enemies, some secondary or indirect impact may occur, such as sub-lethal effects on foraging behavior, fecundity, and other traits restraining proper natural enemy population growth and action (Desneux et al., 2007). In either case, the outcome can be seen as: i) natural enemies delay recolonization of treated areas (Kenmore et al., 1984; Hagerty et al., 2005; Holdom et al., 1989; Fonseca et al., 2007); and ii) outbreaks of target and secondary pests, which is commonly recorded in cotton fields after non-selective insecticide application (Wilson et al., 1998; Hagerty et al., 2005; Grossi and Roenheim, 2011; Hill et al., 2017). Despite that, insecticide application will continue as a core component of IPM in many crop systems including cotton (Furlong et al., 2004; Zalucki et al., 2009). For this reason, cotton ecosystem is considered unfavorable for natural enemy conservation (Torres and Bueno, 2018). Nevertheless, predators and parasitoids naturally occurring in cotton fields help delay pest outbreaks (Eveleens et al., 1973; Ruberson et al., 1994; Grossi and Roenheim, 2011). Therefore, it is fundamental to understand the impact that insecticides may have upon the action of natural enemies (Torres and Bueno, 2018) and, hence, support the IPM concept of integrating biological and chemical controls. The dynamics of predator arthropods in cotton ecosystems can be determined through different methods such as different types of traps, sweep net, shake cloth, visual inspections, and molecular analyses (Hagler and Naranjo, 1994, 1997; Torres and Ruberson, 2005, 2007). Beyond predator abundance, the fluctuation of the pest species is also required to calculate temporal correlations (Grant and Shepard, 1985; Fok et al., 2014). These data are laborious to obtain, and the correlations need special statistical treatment due to the common asynchrony between natural enemy and their prey (Wangersky and Cunningham, 1957; Kuno, 1987; Kindlmann and Dixon, 2003). Predator populations usually increase later after the increment in the prey population, and to define the dynamic of predator-prey interaction requires analyses of series of data to understand any correlation (Turchin, 1990). Beyond that, predation is difficult to measure because the prey can be fully consumed by the predator, which is different from the action of parasitoids and entomopathogens that leave the parasitized (mummies) host apparent during the parasitism development. For these reasons, alternative and feasible methods to measure the action of predatory insects are needed (Birkhofer et al., 2017). Sentinel preys/hosts have been used to evaluate predation under natural environments (Low et al., 2014; Sam et al., 2015; Greenop et al., 2019). Sentinel artificial or natural preys, with density and location pre-defined, are exposed to predation in the field. Later, they are recovered and used to quantify the predation through their consumption and sign of predator attack, allowing inferences to be drawn about the predator population and feeding habit in the area (Low et al., 2014; Sam et al., 2015). For instance, the use of predation signs left behind by the action of the predatory wasps preying on coffee leaf miners (i.e., torn mines), which is easily quantified (ca., 60%), helps with decision to not spray the coffee plantation (Fernandes et al., 2009; Howe et al., 2015). Thus, the aim of this study was to use sentinel prey in cotton fields to evaluate the impact of recommending selective and non-selective insecticides on the action of the natural enemy community. We tested the hypothesis that greater action of natural enemies will occur in fields under recommendation of selective insecticides. Further, to support the field outcome and our hypothesis, we ran a laboratory trial to measure survival of key predatory insects for cotton IPM exposed to dried insecticide residues of the insecticides used to spray our field plots.

2.1. Survey of predator and herbivore species as well as control decisions For this field experiment, we used cotton plots set up inside the refuge area, which was ∼5 ha planted with the non-Bt variety IMA 2106 GL. The experiment consisted of a randomized block design with three treatments [two insecticide-treated plots (selective and non-selective) and an untreated control plot] and four blocks. Each block included, the three treatments represented by a circular area of ∼20 m in diameter, including 20–25 cotton rows. The circular borders of the four blocks were tangent to each other, to reduce the border effect from insecticide application between treatments. The adjacent areas between treatments and blocks received all agronomic practices except insecticide applications. Densities of natural enemies and herbivores were monitored over the cotton-growing season, through 15 surveys for 14 weeks after planting. Surveys were done with 5 to 9-day intervals, from May 18 to August 13, 2018, always conducted between 8 and 10 a.m. The survey consisted of visual inspection of whole plant randomly during the presquare stage. Later in the growing season, surveys on older plants involved inspection of the terminal portion of the main stem, including flower buds, and the three uppermost-developed leaves. The first seven surveys, out of 14, were carried out using 10 plants per replicate, while the seven remaining evaluations were carried out on eight plants per replicate due to the increased time consumed to count whiteflies. The most herbivore and predator species were identified in situ, whereas those specimens not identified in situ were collected for later identification in the laboratory. Insecticide recommendation was based on the herbivore species and abundance in the cotton plots. Thus, pest control level for cotton leafworm, Alabama argillacea Hübner (Lepidoptera: Erebridae), was considered > 1 larvae per plant; for cotton aphid, Aphis gossypii Glover (Hemiptera: Aphididae), it was > 50% of plants infested irrespective of colony size; and for whitefly, Bemisia tabaci (Gennadius) (Hemiptera: Aleyrodidae), it was > 40% of inspected leaves with 2 or more adults per leaf and visible nymphs. 2.2. Action of natural enemies on sentinel prey Predation and parasitism on sentinel prey were determined as a function of recommended insecticide, according to the occurrence and population densities of pest species that require spray decision (Table 1). Three types of sentinel prey were used to measure the action of predators and parasitoids in field plots: i) eggs of the cotton leafworm, A. argillacea; ii) pupae of yellow mealworm, Tenebrio molitor L.; and iii) artificial larvae. These prey items were selected considering that cotton leafworm eggs are individually laid and spread over the plant canopy. This leafworm is a common pest in the study region and is

2. Material and methods To answer our hypothesis, we ran experiments in the laboratory, greenhouse, and field. Data originated from field plots and regarded the natural enemy action upon sentinel prey/host (hereafter sentinel prey) 2

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Table 1 Selective (S) and non-selective (NS) insecticides recommended as function of the pest species occurrence and time of application according to the plant phenology (days after emergence, DAE). Pest species/Active ingredienta 34 DAE (June 8): Aphis gossypii + Alabama argilacea PymetrozineS ChlorantraniliproleS ThiamethoxamNS ChlorpyrifosNS 63 DAE (June 22): Bemisia tabaci CyantraniliproleS DimethoateNS 94 DAE (July 11): Bemisia tabaci PyriproxyfenS MalathionNS 108 DAE (August 3): Bemisia tabaci PymetrozineS ThiamethoxamNS + Lambda-cyhalothrinNS

Trademark

Dosage (a.i./ha)

Chemical groupb

Chess 500 WG Prêmio 200 SC Actara 250 WG Klorpan 480 EC

400 g/ha 25 mL/ha 200 g/ha 0,7 L/ha

Piridine azomethine + Diamide

Benevia 100 SC Dimexion 400 EC

750 mL/ha 1000 mL/ha

Diamide Organophosphate

Tiger 100 EC Malathion 1000 EC

375 mL/ha 975 mL/ha

Pyridine mimic of JH Organophosphate

Chess 500 WG Engeo pleno

400 g/ha 250 mL/ha

Piridine azomethine Neonicotinoid + Pyrethroid

Neonicotinoid + Organophosphate

a Selectivity (S and NS) based on literature data considering major species of natural enemies in the studied area (Kim et al., 2018, Crosariol Netto et al., 2014; Kim et al., 2018; Barros et al., 2018). b Classification according to IRAC (International Resistance Action Committe 2015).

reared in our laboratory. Eggs exposed in the field were previously laid on paper, which was cut in pieces containing 3–6 eggs each. To avoid egg hatching and keep the egg suitable for parasitism (e.g., < 48 h) when exposed in the field, the sentinel eggs were sterilized by storing in a freezer at −5 °C for 5 days prior to the field exposure. The second type of sentinel prey used was the pupae of T. molitor, which is easily attacked by wasps, predatory bugs (assassin and asopini bugs), carabids, ants, etc. Furthermore, these pupae are easily obtained from laboratory rearing at a low cost, which is considered as important characteristics for sentinel prey (Lövei & Ferante 2017). The pupae used were obtained from our laboratory colony maintained according to Torres et al. (2006). The third type of prey consisted of artificial larvae (20 mm long x 4 mm diameter) made of green-colored plasticine (Acrilex®, São Paulo, Brazil) after Lövei and Ferrante (2017). Prey exposure lasted for 48 h. Two days prior to insecticide treatment, a pre-application evaluation (−2 days) occurred to check for any possible difference in the presence of natural enemies before sprays and further impact from previous insecticide application. Further surveys were taken on the day of insecticide application (day 0) and followed 5 and 10 days after insecticide application. In each replicate, four survey stations were randomly stablished, using adjacent plants within the same row to receive the sentinel preys. Each type of prey was fixed on different plants or different plant parts within the station to avoid interference such as predator aggregation. Each station received two pieces of paper containing cotton leafworm eggs (i.e., 8 pieces of paper with 3–6 eggs each per replicate), two yellow mealworm pupae, and one artificial larvae per station. The artificial worm and paper holding the eggs were attached to the underside of leaves from different plant; while, the yellow mealworm pupae were attached by its dorsum at the main-stem leaf junction of the uppermost expanded leaf. Instantaneous glue Amazonas Profissional® (Quimican, São Paulo, Brazil) was used to attach the preys onto plants. On the day of spray (day 0), sentinel prey was placed in the field 2 h after application to allow some volatilization and dripping of insecticides. Predation or parasitism on sentinel prey was evaluated 48 h after exposure by recovering remaining prey items, which were stored in Eppendorf® microtubes (Kasvi LTDA, Paraná, Brazil) for further inspection in the laboratory. The microtubes containing eggs or pupae without evidence of predation were kept at 25 °C and 12 h of photophase to verify parasitism. Likewise, yellow mealworm pupae and artificial larvae were inspected for predation signs. The quantification of predation on artificial larvae were according to Low et al. (2014).

2.3. Residual toxicity of recommended insecticides to predators Part of this experiment was run in the greenhouse and continued in the laboratory. This assay aimed to evaluate the survival of four key predators commonly found in cotton fields: the neotropical ladybird beetle Eriopis connexa (Germar) (Coleoptera: Coccinellidae); the green lacewing, Chrysoperla externa (Hagen) (Neuroptera: Chrysopidae); the predatory stinkbug, Podisus nigrispinus (Dallas) (Hemiptera: Pentatomidae); and the insidiosus bug, Orius insidious (Say) (Hemiptera: Anthocoridae). These predators represent chewing and sucking feeding habits, attack one or more than one type of prey including aphids, whiteflies, mites, thrips, eggs and larvae of lepidopteran and are abundant in cotton ecosystem in Brazil. Initially, non-Bt cotton plants were cultivated in a greenhouse (9 × 4 × 2 m) in circular microplots (100 cm diameter × 50 cm deep) containing soil up to 20 cm from the upper border, and received N:P:K fertilizer and irrigation as needed. Next, the commercial formulations of insecticides were tested at the recommended rates registered for use in Brazil (AGROFIT , 2017). Insecticide dilutions were prepared using distilled water with a spray volume of 100 L/ha plus WillFix® (Charmon Destyl Indústria Química Ltda, São Paulo, Brazil) at 0.01%, which served as a surfactant. Cotton plants with age varying from 50 to 85 DAE were treated with each insecticide dilution using a handy-sprayer 1.5 L capacity (Trapp®, Santa Catarina, Brazil) to the dripping point. Thus, insecticide-treated and untreated leaves were used in the second part of the experiment as follows. The residual toxicity was measured on the day of insecticide application (day 0), and 5, 10, and 15 days later. About 2 h after application (day 0), the upper most expanded leaves were harvested and taken to the laboratory. The remaining of the plants were kept in greenhouse over the studied period to provide treated- and untreatedleaves to test the residual effect according to the previously defined evaluation intervals. In the laboratory, cotton leaf discs measuring 8 cm in diameter were cut and transferred individually to glass Petri dishes (80 mm diameter × 12 mm height). Each dish received five predators, which were confined with the material for 48 h. Ladybird beetles, stinkbugs, and insidiosus bugs used in this test were 5–7 days old, whereas 7 days old larvae of green lacewings were used. Eggs of Anagasta kuehniella (Zeller) (Lepidoptera: Pyralidae) were provided as food for O. insidiosus, C. externa, and E. connexa, likewise pupae of yellow mealworms were provided to P. nigrispinus. The predators used in the experiment originated from the colonies kept in the Biological Control Laboratory of the UFRPE or ordered from commercial insectary and had not been exposed to selection pressure for insecticide resistance. The neotropical ladybird beetle E. connexa 3

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(eight insecticides and control) were performed using the Tukey HSD's test with Bonferroni's corrections for a 0.05 significance level (α = 0.05/n, where ‘n’ represents the number of means in comparison to hold the error level equal to or lower than 0.05). Further corrections on the significance level were according to the number of means in comparisons between day 0 and 15 after insecticide application. The number of treatments subjected to comparisons at each interval was variable because insecticide treatments exhibiting survival ≥90% were no longer tested in the next evaluation intervals.

was reared as described in Rodrigues et al. (2013), and the adults used were in the seventy-eighth generation. Larvae of C. externa were reared as described in Luna et al. (2018), and they were in the thirteenth generation when used in the bioassays. The colony of the predatory stinkbug originated from insects maintained at the Laboratory of Insect Physiology of UFRPE, with unknown number of previous generations, and reared according to Torres et al. (2006). Finally, adults of O. insidiosus were ordered from commercial insectary (PROMIP Agentes de Controle Biológico, São Paulo, Brazil). Adults were kept in glass jars (600 mL-volume) containing wrinkled paper towel, a moistened cotton pad, flowers of cobbler peg weed, Bidens pilosa L., as oviposition substratum, and eggs of A. kuheniella as prey until experiment initiation. The experiment followed a randomized design with eight insecticides plus a control treatment, four intervals of residual effect (0, 5, 10, and 15 days) as factors, with six to seven replicates each (n = 30 to 35 insects). Due to the logistics regarding the number of insecticides tested, each predator species was tested separately. Dishes containing predators were kept under laboratory conditions of 25 ± 2 °C, 12 h of photophase and relative humidity from 60 to 70% and mortality tailed 48 h after caging.

3. Results 3.1. Survey of predator and herbivore species as well as control decisions A total of 1837 immature and adult stages of predatory insects and spiders were recorded from cotton plants. This abundance was 38.3%, 42.1%, and 19.6% from control, selective, and non-selective insecticide treatments, respectively. Predator species were sorted into seven groups (ants, ladybird beetles, lacewings, stinkbugs, earwigs, ground beetles, and spiders) with ants, ladybird beetles, and spiders accounting for 94.8% of the species. Repeated measures analysis of variance for predator abundance resulted in significant effect across treatments (F2, 6 = 16.83, P = 0.0035), and sampling dates (F14, 84 = 4.92, P < 0.0001), but not in the interaction of treatment and dates (F28, 84 = 1.25, P = 0.2503). Abundance was characterized by lower predatory densities recorded on the sampling dates after non-selective insecticide application (14 and 27 June, 25 July, and 8 August; Fig. 1A). Furthermore, prolonged residual toxicity was also detected for various dates after non-selective insecticide applications. Overall reduction in predator abundance was observed after the second spray in both areas of selective insecticide and control treatments. However, the average predators found per plant, considering the 15 surveys within the season, was similar between selective insecticides and control treatment, and both exhibited higher predator average than non-selective treatment areas (F2, 177 = 18.32, P < 0.0001). The seasonal averages were 2.04- and 2.15fold higher in the control and selective insecticide areas than in nonselective insecticide areas, respectively (Fig. 1B). Herbivore surveys resulted in insecticide sprays at 34 days (June 8) after emergence (DAE) due to the simultaneous infestation of cotton leafworm and cotton aphid, and at 63, 94, and 108 DAE (June 22, July 11, and August 3, respectively) due to whitefly infestation. Other cotton herbivore species surveyed included leafhoppers, red spider mite, stinkbugs, tarnish cotton plant bug, fall armyworm, Southern armyworm, and boll weevil, but with low densities not requiring control measures. Aphid infestation occurred during early season from May 18 to June 22, throughout the first six evaluations. Repeated measure analysis detected variation in percentage of plants infested with cotton aphid as a function of treatments (F2, 6 = 13.65, P = 0.0059), sampling dates (F14, 84 = 23.09, P < 0.0001), and the interaction of treatment and sampling dates (F28, 84 = 3.72, P < 0.0001). Decision for aphid control only occurred on June 8, during the fourth evaluation. In the subsequent evaluations after insecticide application, the percentage of aphid-infested plants differed across treatments, with low densities in selective and non-selective treatments, and only in non-selective treatment in the fifth and sixth evaluations, respectively. Likewise, the number of cotton leafworm larvae per plant differed as a function of treatments (F2, 6 = 5.78, P < 0.0001), sampling dates (F14, 84 = 20.83, P < 0.0001), and their interaction (F28, 84 = 5.69, P < 0.0001). For the effect of sampling date, cotton leafworm was recorded during the first five evaluations early in the season. Furthermore, the density of larvae per plant was similar across treatments, except right after insecticide application, where a lower number of larvae was observed in the selective and non-selective treatments relative to the control treatment.

2.4. Statistical analysis Data on predatory arthropods and herbivores were transformed into standardized unit. To analyze the impact of selective and non-selective insecticides in comparison to untreated control treatments, the number of individuals counted on ten or eight plants per replicate was averaged per plant, to adjust for variation in the number of plants and sampling units used throughout the season. The average of individuals per plant required log (x+1) transformation to fit the analysis of variance (ANOVA) assumptions (Proc UNIVARIATE of SAS for normality and Proc ANOVA with Bartlet's test for homogeneity of the data); however, original means were used for result presentation and discussion. Furthermore, the transformed data were submitted to one-way ANOVA using the 15 evaluations as repeated measures (Proc GLM of SAS). The separation of the treatment means for each date of evaluation was performed by Tukey HSD test (α = 0.05), and all analysis were executed using the SAS statistical package (SAS Institute, 2002). For the action of natural enemies as function of recommended insecticide, the number of prey consumed/attacked was converted to percentage since the final number differed across treatments and replications due to loss by unknown causes. Further, the data were transformed into arcsine square root (x/100) to meet the normality (Shapiro-Wilk's test) and homogeneity (Bartlet's test) for ANOVA and post hoc for mean comparisons. The results were then submitted to oneway ANOVA under the repeated measures procedure considering the three treatments (selective and non-selective insecticides and untreated control treatments). Thus, the procedure considered four replicates per treatment, and four evaluations for time (−2, 0, 5, and 10 days) as repeated measures at each decision for insecticide application separately (34, 63, 94, and 108 DAP). Finally, mean comparisons across treatments on each interval of evaluation was performed by Tukey HSD's test (α = 0.05). All analyses were performed using the statistical software SAS 9.0 (SAS Institute, 2002). For the residual test, predator mortality was recorded 48 h after caging and used to calculate the percentage of survival. Results are presented as survival rates since our interest is about the surviving individuals that will contribute to pest management. The analyses were performed considering a 9 × 4 factorial design consisting of nine treatments (eight insecticides and control) and four residual intervals (0, 5, 10, and 15 days) (SAS Institute, 2002). Before analysis, the data were arcsine square−root transformed to meet the ANOVA assumptions after being tested for normality (Shapiro-Wilk's test, Proc Univariate of SAS) and homogeneity of variance (Barttlet's test, Proc ANOVA of SAS). However, untransformed means and standard errors are presented in tables. Mean comparisons across treatments at day 0 4

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Fig. 1. Mean predators (+SE) per plant on each plant survey in the field (A), and the seasonal mean predators per plant as function of insecticide recommendation (B). Note: The arrows and letters denote insecticide applications and statistic difference across treatment means (Tukey HSD′ test, α < 0.05), respectively.

application were similar based on their respective action on sentinel prey (Figs. 2 and 3). The pre-evaluation run during the next decisions for insecticide application were similar, but with some exceptions according to the residual impact from previous application of non-selective insecticides. Regarding the first decision for insecticide application, mortality (predation/parasitism) of cotton leafworm sentinel eggs on the day of application (day 0) was significantly lower in non-selective treatment areas with only 8.7% egg mortality, followed by selective treatment areas (ca., 24.7%); whereas, in the control treatment areas 71.8% egg mortality was recorded (Fig. 2A). Further, residual impact on egg mortality at 5 and 10 days after spray persisted with lower egg mortality in non-selective treatment areas compared to selective and control treatment areas (Fig. 2A). Egg parasitism was recorded only in the selective and control treatment areas at 34 DAE due to the occurrence of Trichogramma sp., accounting for 8.1% egg mortality. Egg mortality (predation), during the second insecticide application

Different from aphid and leafworm, whitefly infestation took place mid-late season and prevailed over other pest species in the area. Overall, high densities of whitefly occurred across all field plots, but with special occurrence of nymphs on non-selective treatment plants. Therefore, the repeated measure ANOVA detected significance across all major effects: treatments (F2, 6 = 16.68; P = 0.0035); sampling dates (F14, 84 = 152.82, P < 0.0001), and their interaction (F28, 84 = 3.37, P < 0.0001). On seven out of fifteen sampling dates, the whitefly densities per plant differed (May 30, June 6 and 20, July 2 and 20, and August 8 and 13). This difference was caused by lower whitefly densities in control treatment during the two first dates (May 30 and June 6); while during the five remaining dates, lower densities of whitefly were observed in treatment with selective insecticides. 3.2. Action of natural enemies on sentinel prey Abundance of predators and parasitoids before the first insecticide

Fig. 2. Mortality (+SE) of cotton leafworm eggs, Alabama argillacea, prior-insecticide application (−2 days) and after insecticide application (0, 5, and 10 days). Means under the same letter do not differ at each evaluation date (Tukey HSD's test, α = 0.05). A, B, C, and D stand for spray decisions at 34, 63, 94, and 108 after plant emergence (DAE) (see Table 1).

5

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Fig. 3. Mortality (+SE) of yellow mealworm pupae, Tenebrio molitor, prior-insecticide application (−2 days) and after insecticide application (0, 5, and 10 days). Means under the same letter do not differ at each evaluation date (Tukey HSD′ test, α = 0.05). A, B, C, and D stand for spray decisions at 34, 63, 94, and 108 after plant emergence (DAE) (see Table 1).

was lower and similar between insecticide treatments relative to the control treatment, persisting for 10 days after application for the nonselective treatment. During the second insecticide application at 63 DAE, the pre-spray evaluation did not detect statistical difference from residual impact from previous application (−2 days evaluation) in the non-selective treatment, but numerically only 56.2% of pupae was consumed compared to 78.1% and 81.2% in the control and selective treatments, respectively (Fig. 3B). Pupae exposure at day 0 resulted in greater predation in the selective and control treatments (71.9% and 81.2%) compared to non-selective treatment. During the third application, no pupae were available to run the evaluation at 5 days after application, while, at 10 days after application similar predation was observed in the selective and control treatments and greater than in the non-selective treatment (Fig. 3C). Finally, at 108 DAE, pupae predation at −2 days evaluation was similar across treatments (Fig. 3D). On the other hand, at day 0 pupae predation was lower in both selective and non-selective insecticide treatments. Further evaluation regarding the residual impact resulted in lower predation on days 5 and 10 after application in the non-selective treatment compared to control and selective treatments. Only 18.7, 15.6, and 18.7% of pupae were preyed in the non-selective treatment during the evaluations ran at 0, 5, and 10 days, respectively. Regarding the artificial prey, a total of 760 larvae were exposed in the field experiment, and attack upon artificial larvae accounted for 0.004%, without difference across treatments. Although artificial prey could be attacked by wasps and spiders, they are more easily attacked by vertebrates such as birds, reptiles, and rodents.

decision at 63 DAE, was lower for non-selective treatment across all intervals of evaluation (−2, 0, 5, and 10 days) (Fig. 2B). At 10 days after application, however, egg mortality in control, selective, and nonselective treatments accounted for 97.4%, 84.9%, and 64.47%, respectively, differing across all three treatments. The same trend was observed during the third insecticide application decision at 94 DAE, with similar egg mortality between control and selective insecticides and greater than non-selective insecticide (Fig. 2C). Egg mortality in control and selective insecticides was around 80%, while egg mortality in non-selective treatment was on average 6.8%, 45.0%, and 70.5% on the day of application and 5 and 10 days after application, respectively. Finally, during the fourth insecticide application at 108 DAE, residual effect from previous non-selective insecticide application resulted in lower egg mortality in the pre-spray evaluation (Fig. 2D). At 108 DAE, egg mortality was also different between selective and control treatments, 5 days after insecticide application (68.5% versus 90.9%). Predation upon yellow mealworm pupae was determined by the remains of exuviae. Besides that, predatory ants, beetles, and spiders were observed attacking this prey during the evaluations. The ant species Crematogaster victima Fr. Smith, Solenopsis globularia (Fr. Smith), and Odontomachus bauri Emery (Hymenoptera: Formicidae) were especially abundant, and to a minor extent the spider Cheiracanthium sp. Ants were identified at species level and vouchers number #5830 were stored in the “Coleção do Laboratório de Mirmecologia da Universidade Estadual de Santa Cruz (UESC)”. This research is under the register of SISGEN (A82A894), regarding genetic patrimony and associated traditional knowledge in Brazil. Yellow mealworm pupae recovered from the field without signs of predation were monitored in the laboratory and resulted in adults or died. Most pupae mortality not caused by predation was due to dehydration, hence, this fate was not considered as predation in the analysis. Further, parasitism of pupae was not detected. During the first insecticide application decision, at 34 DAE, predation evaluated at day 0 resulted in only 31.2% of pupae attacked in the non-selective treatment compared to 68.7% and 76.7% pupae attacked on selective and control treatments (Fig. 3A). For the residual impact of this insecticide application, pupae predation at 5 days after application

3.3. Residual toxicity of recommended insecticides to predators Two-way ANOVA detected significant variation in the toxicity of insecticides tested, their residual impact after application, and interaction of these two major effects for all exposed predator species (Table 2). These outcomes are due to variation of the toxicity of the tested insecticides at each residual interval evaluated, as well as the reduced impact according to the period of time after application on plants. The insecticides pymetrozine, chlorantraniliprole, and 6

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pyriproxyfen promoted survival greater than 90% for all tested predator species, except for O. insidiosus. The exposure of O. insidiosus resulted in 44.2%, 50.0%, and 90.5% survival at 0, 5, and 10 days after contact on dry residue of pymetrozine (Table 3). Residues of the organophosphates dimethoate and malathion caused 100% mortality upon application, but a reduced residual effect was observed 5 days after spray, with survival ranging from 50 to 90%. Again, the predator O. insidiosus exhibited the lowest survival rate across predator species with 69.4 and 76.6% at day 5 and 10 after dimethoate application (Table 3). Likewise, the neonicotinoid thiamethoxam did not allow survival of C. externa, O. insidiosus, and P. nigrispinus on the day of application, and only 6.1% of E. connexa survived in response to this insecticide-dry residue. In fact, survival ≥90% was observed for E. connexa, C. externa, and P. nigrispinus only at day 10 after application, which persisted for O. insidiosus up to day 15 after application (Table 3). In addition, this long residual impact was enhanced when thiamethoxam was in commercial

Table 2 Two-way ANOVA outcome for treatment effect (eight insecticides plus control treatment), residual toxicity after application (0, 5, 10, and 15 days) and their interaction, for survival of Eriopis connexa, Orius insidiosus, and Podisus nigrispinus adults, and of Chrysoperla externa larvae caged on cotton leaves collected from treated plants and maintained in greenhouse during the studied period. Factors Treatment (T) Residue (R) T*R

Treatment (T) Residue (R) T*R

DF F Eriopis connexa 8 45.69 3 90.43 11 19.41 Orius insidiosus

P

8 3 15

< 0.0001 < 0.0001 < 0.0001

74.34 78.55 16.41

< 0.0001 < 0.0001 < 0.0001

DF F Chrysoperla externa 8 40.35 3 88.63 11 19.03 Podisus nigrispinus

P

8 3 13

< 0.0001 < 0.0001 < 0.0001

37.94 133.24 15.20

< 0.0001 < 0.0001 < 0.0001

Table 3 Survival rate (%) of Eriopis connexa, Chrysoperla externa, Orius insidiosus, and Podisus nigrispinus adults caged on dry residues on cotton leaves at different intervals after application considering the insecticides used to spray our field plots according to pest infestation (see Table 1). Predators/Insecticides

Eriopis connexa Control ChlorantraniliproleS(c) Pyriproxyfen S PymetrozineS CyantraniliproleS MalathionNS DimethoateNS ThiamethoxamNS Thiamethoxam + λ-cyhalothrinNS F(df) P−value Chrysoperla externa Control ChlorantraniliproleS(c) PyriproxyfenS PymetrozineS CyantraniliproleS MalathionNS DimethoateNS ThiamethoxamNS Thiamethoxam + λ-cyhalothrinNS F(df) P−value Orius insidiosus Control ChlorantraniliproleS(c) PyriproxyfenS PymetrozineS CyantraniliproleS MalathionNS DimethoateNS ThiamethoxamNS Thiamethoxam + λ-cyhalothrinNS F(df) P−value Podisus nigripinus Control ChlorantraniliproleS(c) PyriproxyfenS PymetrozineS CyantraniliproleS MalathionNS DimethoateNS ThiamethoxamNS Thiamethoxam + λ-cyhalothrinNS F(df) P−value

Residual time after application (days)a

Statistics

0

5

10

15

F(df)P−value

99.2 ± 0.83 A 100 A 100 A 91.1 ± 4.01 A 56.7 ± 9.54 B a 0Cb 0C c 6.1 ± 3.89 C c 14.2 ± 6.88 C c 97.20(8.45)0.0001

99.2 ± 0.75 A −b – – 49.4 ± 10.34 C a 93.8 ± 3.88 AB a 62.7 ± 6.58 BC b 55.2 ± 12.25 C b 34.4 ± 6.06 C bc 13.99(5.30)0.0001

100 A – – – 62.2 ± 4.68 B a – 96.7 ± 3.33 A a 90.5 ± 4.25 A a 56.7 ± 6.14 B b 24.17(4.25)0.0001

100 A – – – 73.3 ± 9.88 B a – – – 86.7 ± 6.67 AB a 3.99(2.15)0.0408

0.67(3, 20)0.5812 – – – 1.28(3, 20)0.3091 582.78(1, 10)0.0001 132.71(2, 15)0.0001 29.37(2, 15)0.0001 23.23(3, 20)0.0001

96.7 ± – – – 53.3 ± 93.3 ± 90.0 ± 10.0 ± 55.0 ± 31.87(5,

100 A a – – – 48.3 ± 10.60 B a

100 A a – – – 80.5 ± 7.32 B a

– 60.0 ± 10.32 B b 80.0 ± 8.90 AB ab 5.18(3, 20)0.008

– 93.3 ± 4.21 A a 90.0 ± 6.83 A a 2.30(3, 20)0.1065

0.67(3, 20)0.5418 – – – 2.32(3, 20)0.1067 209.93(1, 10)0.0001 166.80(1, 10)0.0001 51.00(3, 20)0.0001 24.21(3, 20)0.0001

99.1 ± 0.83 A a 96.7 ± 3.33 A 90.0 ± 6.83 A 96.7 ± 3.33 A 53.3 ± 6.67 B a 0C 0C 0C c 6.7 ± 4.21 C c 108.24(8, 45)0.0001

3.33 A a

13.33 B a 4.21 A 4.47 A 4.72 C c 6.19 B b 30)

0.0001

95.5 ± 3.11 A a 100 A 91.5 ± 3.86 A 44.2 ± 7.38 B b 45.8 ± 7.59 B b 3.3 ± 3.33 C b 0Cb 0Cb 0C c 123.58(8.51)0.0001

93.3 ± 2.84 A a – – 50.0 ± 11.25 B b 40.0 ± 7.30 B b 93.3 ± 4.21 A a 69.4 ± 12.00 AB a 6.6 ± 4.21 C b 3.3 ± 3.33 C c 30.70(6.41)0.0001

96.7 ± 2.24 A a – – 90.5 ± 6.68 A a 60.0 ± 7.30 Bb – 76.6 ± 6.14 AB a 13.3 ± 4.21 C b 46.7 ± 8.43 BC b 27.83(5.36)0.0001

96.7 ± 2.24 A a – – – 86.7 ± 6.67 AB a – 90.5 ± 4.25 AB a 56.7 ± 9.54 B a 86.7 ± 6.67 AB a 5.64(4.31)0.0016

0.32(3, 20)0.8098 – – 11.45(2, 15)0.0010 9.34(3, 20)0.0005 115.48(1, 10)0.0001 28.68(3, 20)0.0001 18.84(3, 20)0.0001 51.09(3, 20)0.0001

100 A a 100 A 96.7 ± 3.33 A 93.3 ± 4.21 A 36.7 ± 6.14 B b 0C c 0C c 0C c 0C c 261.47(8, 45)0.0001

100 A a – – – 43.3 ± 6.14 BC b 86.7 ± 6.67 AB b 70.0 ± 8.56 AB b 56.7 ± 14.06 BC b 16.6 ± 6.14 C b 12.19(5, 30)0.0001

96.6 ± 3.33 A a – – – 56.7 ± 9.54 B b 100 A a 93.3 ± 4.21 A a 83.3 ± 8.03 AB ab 80.0 ± 7.30 AB a 6.50(5, 30)0.0003

100 A a – – – 83.3 ± 6.14 B a – – 93.3 ± 4.21 AB a 83.3 ± 6.14 B a 3.12(3, 20)0.0489

0.99(3, 20)0.4133 – – – 8.36(3, 20)0.0008 136.42(2, 15)0.0001 64.50(2, 15)0.0001 21.85(3, 20)0.0001 35.27(3, 20)0.0001

a

Means ± SEM followed by capital letter compare insecticides within residual intervals and means followed by small letter within rows compared the same insecticides across different residual intervals by Tukey HSD's test (α = 0.05). b Stands for survival value in the previous interval ≥90%. c Selectivity (S and NS) based on literature data considering major species of natural enemies in the studied area (Crosariol Netto et al., 2014; Kim et al. 2018; Barros et al. 2018). 7

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interaction of predator-prey in the crop ecosystem. Predation upon our sentinel preys was a result of predator conservation in the treated plots. Probably, physiological selectivity promoted by the difference in the susceptibility of the natural enemies to the selected insecticide (pymetrozine, pyriproxyfen, chlorantraniliprole, and cyantraniliprole) relative to the pest (Torres et al., 2003b; Barbosa et al., 2017, 2018; Barros et al., 2018) can be ruled as the major factor regulating predator action in treated areas. Few previous studies have shown the real benefits of recommending selective insecticides (Slone and Burrack, 2016; Bueno et al., 2011). For instance, the use of the insect growth regulators buprofezin and pyriproxyfen to control whitefly in cotton fields resulted in higher predator survival and predation upon secondary cotton pests (Naranjo et al., 2004). On the contrary, the use of thiamethoxam in cotton fields reduced by 25.1% the population of natural enemies seven days after insecticide application (Czepak et al., 2005). Lambda-cyhalothrin application in a cotton field reduced in 5-fold the post-application predator population (Van Hamburg and Guest, 1997). Likewise, Fernandes et al. (2016) Fernandes et al. (2016) reported reduction of predator community on tomato crop up to 21 days after application of the non-selective insecticides belonging to organophosphates and pyrethroids. Macfadyen and Zalucki (2012) found that deltamethrin application in soybean fields reduced the invertebrate abundance, with lack of restoring population equivalent to pre-application up to 20 days later. Therefore, the impact of using non-selective insecticides on predator community and abundance in the field is often reported. The primarily role of recommending selective insecticides is to preserve the biological control agents (Hassan et al., 1985; Ruberson et al., 1999; Tillman and Mulrooney, 2000; Bueno et al., 2017). Additionally, according to Torres and Bueno (2018), recommendation of selective insecticide goes beyond the preservation of the biological control agents. For instance, it also accounts for the delay or mitigation of insect resistance to insecticides, since remaining prey may be controlled by the predatory community. In addition, preservation of natural enemies will likely reduce secondary pest outbreaks, and mainly act on surviving individuals of the target pest species under selection pressure for resistance, hence delaying resistance selection. The predation upon artificial larvae was almost unnoticeable in this study. Signs of predation were observed only on larvae placed on plots that were untreated or treated with selective insecticide, but in low numbers. Usually, attack of this type of sentinel prey is done by vertebrates and a few arthropods such as wasps and large beetles, which were not very common in our field plots. In addition, they lacked chemical cues from prey itself, volatiles from injured plants, visual attraction, and mechanical vibration, which are all important for prey location and have contributed to generate unexepcted results (Hansen, 1983; Mackauer et al., 1996). Nonetheless, Sam et al. (2015)Sam et al. (2015) did not detect difference on predation or daily sign of attack between natural and artificial larvae. Furthermore, Howe et al. (2015) found similar rates of predation signs on artificial larvae displayed in treated (1.96%) and untreated (4.1%) cotton fields. It seems that in crop ecosystems, which are regularly submitted to high anthropogenic activity, the artificial larvae did not evoke the expected action. Greenhouse and laboratory outcomes of insecticide dried-residues support that recommendation of selective insecticide allowed predators to survive in the field, which were responsible for differences in predation rate observed across treatments. Nevertheless, insecticides with some impact under confined conditions, such as pymetrozine vs insidiosus bug, and cyantraniliprole vs all tested predators, could have less impact under field conditions, where active ingredients degrade faster and predators are expected to suffer less impact compared to laboratory studies (Torres and Bueno, 2018). Ryanodine receptors in the muscle cells are the action sites for cyantraniliprole, causing mortality from uncontrolled release of calcium ions. Moreover, insect death can occur by topical (contact) or ingestion (systemically) intoxication (Selby et al., 2013). Cyantraniliprole has

mixture with lambda-cyhalothrin. In this case, only larvae of C. externa exhibited survival ≥90% at day 15 after application, while the three other predators had less than 90% survival (Table 3). Interestingly for cyantraniliprole, predator survival varied from 36.7% to 56.7% on the day of its application, and survival was never ≥90% if compared to the other selective insecticides tested. Even at 15 days after cyantraniliprole application, the survival response of the four predators varied from 73.3 to 86.7% (Table 3). 4. Discussion The outcome of field and laboratory assays highlights the importance of recommending selective insecticides for cotton pest management corroborating with previous reports. Similarly, this outcome could be expected for other crop ecosystems considering the insecticides and predatory species tested, in special with tested materials (e.g., chlroantraniliprole, cyantraniliprole, pymetrozine and piryproxyfen), which represents different classes of insecticides not investigated previously in such way. The use of these selective insecticides allowed the natural enemies to survive in the field, which was reflected in higher predation upon sentinel prey items. Nevertheless, one cannot face impact on natural enemies when recommending selective insecticides, because there are indirect effects mediated by reduction of preferred prey population. For instance, during the first insecticide application decision (34 DAE, Fig. 2A), aphids were abundant and likely the predominant prey for the predator community. However, the successful reduction of aphid abundance after pymetrozine application may have imposed a risk of starvation to the aphid predators, which could either starve to death or leave the area. Thus, the reduction in predator abundance and predation observed upon sentinel prey was likely due to the predator dispersal to adjacent areas. Due to the lack of direct toxicity from the applied insecticide (i.e., pymetrozine and chlorantraniliprole proved through our laboratory study), dispersing predators could recolonize the field earlier than on areas treated with non-selective insecticides, and continue predation upon non-target pests. This was supported by the fact that predation on sentinel preys increased at 5 and 10 days after spray, returning to levels similar to the untreated control plots. Nonetheless, this outcome will not always be the same because it depends on the prey species impacted by the applied insecticide and the community of predators. Even though various predators were present during these two evaluation dates, it was observed predominance of ladybird beetles simultaneously with aphids (Fig. 2A), and ladybird beetles and lacewings with whiteflies (Fig. 2D). The non-selective insecticides not only reduced the predation at the application date, but their impact persisted after that. Lower predation rates happened in some occasions in the pre-application (−2 days) following the first sprays. Again, the impact from non-selective insecticides between application times was not consistent because it will depend on the residual effect of each insecticide molecule. Some of the non-selective insecticides tested, even though exhibiting high acute toxic to natural enemies, had shorter residual activity due to degradation. This is supported by data comparison of field results and the residue toxicity tested in the laboratory with the four predatory species (Table 2). For instance, among the non-selective insecticides used, malathion exhibited shorter residual effect than thiamethoxam and lambda-cyhalothrin + thiamethoxam. Besides being related to the toxicity of insecticide molecules, the residual effect between insecticide applications is also a result of other variables such as the environmental conditions (e.g., rainfall, UV radiation, temperature, etc.) acting upon active ingredient degradation (Ware et al., 1972; Fenner et al., 2013), the predator community (e.g. resistant or susceptible strains and life stages; Costa et al., 2018; Luna et al., 2018), and time interval between applications (data in this study). Therefore, despite the minor impact caused by selective insecticide upon predation, the expected outcome may vary due to the physical and biological variables affecting the 8

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Acknowledgements

been recommended against lepidopterans, beetles, whiteflies, leafminers, and thrips (Selby et al., 2013; Barry et al., 2015). Therefore, considering this broader spectrum in comparison to chlorantraniliprole and flubendiamide, which target lepidopteran larvae, a high rate of physiological selectivity become difficult to obtain with cyantraniliprole, since both insect pests and natural enemies have target ryanodine receptors. In spite of that, some studies have shown that cyantraniliprole has low risk for natural enemies (Beers et al., 2016; Amarasekare et al., 2016; Mills et al., 2016). Our study confirmed that pyriproxyfen, pymetrozine, and chlorantraniliprole have low impact on natural enemies as previously cited (Torres et al., 2003b; Jansen and DefranceWarnier, 2011; Rezaei et al., 2007; Moscardini et al., 2013; Barros et al., 2018; Barbosa et al., 2018). For pyriproxyfen, which mimics juvenile hormone, it is important to mention that all predators were exposed at adult stage, except green lacewing larvae. Pyriproxyfen acts by suppressing embryogenesis, proper molting, and adult formation (Itaya, 1987; Koehler and Patterson, 1991; Ishaaya and Horowitz, 1995). Other studies have shown compatibility of pyriproxyfen with adults of Cryptolaemus montrouzieri Mulsant (Coleoptera: Coccinellidae), Leptomastix dactylopii Howard (Hymenoptera: Encyrtidae) (Cloyd and Dickinson, 2006), Orius spp. (Delbeke et al., 1997; Nagai, 1990), and larvae of the green lacewing Chrysoperla carnea (Stephens) (Neuroptera: Chrysopidae) (Medina et al., 2003). Despite the lack of impact on adults, sublethal effects on reproductive output have been reported (Moscardini et al., 2013; Ono et al., 2017; Rimoldi et al., 2017; Barbosa et al., 2018). The non-selective insecticides studied here (malathion, dimethoate, thiamethoxam, and lambda-cyhalothrin) are neurotoxins acting irrespective of the target species feeding habit, developmental stage, etc. (Bloomquist, 1996; Yu, 2014). Thus, low survival of natural enemies right after application was expected, and reflected by a reduction in predation rates in the non-selective treated areas. However, despite the acute toxicity of the organophosphates, malathion and dimethoate, they exhibited low residual impact 5 days after application. Direct exposure to organophosphate insecticides result in high toxicity for natural enemies (Elzen, 2001; Moura et al., 2010; Iannacone et al., 2015; Barros et al., 2018), but some of organophosphate insecticides exhibit short residual effects because they posse fast degradation rates (Ware et al., 1972; Fenner et al., 2013). In contrast, plain neonicotinoids or in commercial mixture with pyrethroids were highly toxic to natural enemies and exhibited long residual effect. Thiamethoxam, here and in other studies, has behaved as a non-selective insecticide (Torres et al., 2002, 2003a; Barros et al., 2018). Beside acute toxicity, thiamethoxam exhibits systemic and prolonged residual effect against sucking insects and zoophytophagous predators, which may explain its effect against O. insidiosus (Maienfisch et al., 2001; Torres et al., 2003a; Torres and Ruberson, 2004). In summary, the impact of non-selective insecticides on the beneficial arthropods community in cotton ecosystem hinders the harmonious combination of these insecticides and biological control; however, the selective ones do not. Cautious insecticide recommendation considering the target pest species and selectivity to natural enemies proved to contribute significantly to cotton IPM. Thus, considering that pymetrozine, pyriproxifen and chlorantraniliprole allowed survival over 90% of the studied predators on treated cotton plants with them, and caused less impact on the action of biological control monitored in our field plots using sentinel preys, they should be preferred over nonselective insecticides in cotton IPM, followed by cyantraniliprole. The organophosphates, malathion and dimethoate, are expected to reduce acute toxicity to the studied predatory species after 5 days, but their broad-spectrum of control delays prey and predator recolonizations. Finally, thiamethoxam and the commercial mixture of lambda-cyaholothrin + thiamethoxam must be avoided irrespective of the interval after application.

We thank Dr. Jacques Hubert Charles Delabie (UESC/CEPLAC) for identifying ant species. This study was partially financed by the “Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brazil (CAPES)” through CAPES PROEX, through student grants to A.V.A.M. and D.M.P., by “Conselho Nacional de Desenvolvimento Cientifico e Tecnológico (CNPq)”, through research grants to C.S.A.S.T. and J.B.T., and by the “Fundação de Amparo a' Ciência e Tecnologia do Estado de Pernambuco (FACEPE)” through the research fund APQ-0168-5.01/15. Special thanks to the grower Hermógeno Timóteo for allowing us to access his field during the growing season, and the three reviewers and the associate editor for their appropriate and constructive suggestions and for their proposed corrections to improve the manuscript. Appendix A. Supplementary data Supplementary data to this article can be found online at https:// doi.org/10.1016/j.ecoenv.2019.109669. References AGROFIT (Sistema de Agrotóxicos Fitossanitários), 2017. Disponível Em. , Accessed date: 20 July 2017 http://agrofit.agricultura.gov.br/agrofit_cons/!ap_ingrediente_ativo_ rep_cons. Amarasekare, K.G., Shearer, P.W., Mills, N.J., 2016. Testing the selectivity of pesticide effects on natural enemies in laboratory bioassays. Biol. Control 102, 7–16. Barbosa, P.R.R., Torres, J.B., Michaud, J.P., Rodrigues, A.R.S., 2017. High concentrations of chlorantraniliprole reduce its compatibility with a key predator, Hippodamia convergens (Coleoptera: Coccinellidae). J. Econ. Entomol. 110, 2039–2045. Barbosa, P.R.R., Oliveira, M.D., Barros, E.M., Michaud, J.P., Torres, J.B., 2018. Differential impacts of six insecticides on a mealybug and its coccinellid predator. Ecotoxicol. Environ. Saf. 147, 963–971. Barros, E.M., Silva-Torres, C.S.A., Torres, J.B., Rolim, G.G., 2018. Short-term toxicity of insecticides residues to key predators and parasitoids for pest management in cotton. Phytoparasitica 46, 391–404. Barry, J.D., Portillo, H.E., Annan, I.B., Cameron, R.A., Clagg, D.G., Dietrich, R.F., Watson, L.J., Leighty, R.M., Ryan, D.L., McMillan, J.A., Swain, R.S., 2015. Movement of cyantraniliprole in plants after foliar applications and its impact on the control of sucking and chewing insects. Pest Manag. Sci. 71, 395–403. Beers, E.H., Mills, N.J., Shearer, P.W., Horton, D.R., Milickzy, E.R., Amarasekare, K.G., Gontijo, L.M., 2016. Nontarget effects of orchard pesticides on natural enemies: lessons from the field and laboratory. Biol. Control 102, 44–52. Birkhofer, K., Bylund, H., Dalin, P., Ferlian, O., Gagic, V., Hambäck, P.A., Stenberg, J.A., 2017. Methods to identfy the prey of invertebrate predators in terrestrial field studies. Ecol. Evol. 7, 1942–1953. Bloomquist, J.R., 1996. Ion channel as targets for insecticides. Annu. Rev. Entomol. 41, 163–190. Bueno, A.D.F., Carvalho, G.A., Santos, A.C.D., Sosa-Gómez, D.R., Silva, D.M.D., 2017. Pesticide selectivity to natural enemies: challenges and constraints for research and field recommendation. Ciência Rural. 47, e20160829. Bueno, A.D.F., Batistela, M.J., Bueno, R.D.F., França, N., Nishikawa, M.A.N., Liberio Filho, A., 2011. Effects of integrated pest management, biological control and prophylactic use of insecticides on the management and sustainability of soybean. Crop Protect. 30, 937–945. Costa, P.M.G., Torres, J.B., Rondelli, V.M., Lira, R., 2018. Field-evolved resistance to λcyhalothrin in the lady beetle Eriopis connexa. Bull. Entomol. Res. 108, 380–387. Cloyd, R.A., Dickinson, A., 2006. Effect of insecticides on mealybug destroyer (Coleoptera: Coccinellidae) and parasitoid Leptomastix dactylopii (Hymenoptera: Encyrtidae), natural enemies of citrus mealybug (Homoptera: pseudococcidae). J. Econ. Entomol. 99, 1596–1604. Crosariol Netto, J., Degrande, P.E., Melo, E.P., 2014. Seletividade de inseticidas e acaricidas aos inimigos naturais na cultura do algodão. Cuiabá, IMAmt 4p (Circular Técnica 14). Czepak, C., Fernandes, P.M., Cordeiro Albernaz, K., Daroszewski Rodrigues, O., Martins Silva, L., Alves da Silva, E., Divino Borges, J., 2005. Seletividade de inseticidas ao complexo de inimigos naturais na cultura do algodão (Gossypium hirsutum L.). Pesqui. Agropecuária Trop. 35, 123–127. Delbeke, F., Vercruysse, P., Tirry, L., de Clercq, P., Degheele, D., 1997. Toxicity of diflubenzuron, pyriproxyfen, imidacloprid and diafenthiuron to the predatory bug Orius laevigatus (Het.: anthocoridae). Entomophaga 42, 349–358. Desneux, N., Decourtye, A., Delpuech, J.-M., 2007. The sublethal effects of pesticides on beneficial arthropods. Annu. Rev. Entomol. 52, 81–106. Elzen, G.W., 2001. Lethal and sublethal effects of insecticide residues on Orius insidiosus (Hemiptera: anthocoridae) and Geocoris punctipes (Hemiptera: lygaeidae). J. Econ. Entomol. 94, 55–59. Eveleens, K.G., van den Bosch, R., Ehler, L.E., 1973. Secondary outbreak induction of beet armyworm by experimental insecticide applications in cotton in California. Environ. Entomol. 2, 497–503.

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