Abstract Natural enemies are valuable components of agroecosystems as they provide biological control services to help regulate pest populations. Promoting biocontrol services can improve sustainability by decreasing pesticide usage, which is a major challenge for the blueberry industry. Our research is the first to compare natural enemy populations in managed (conventional and organic) and unmanaged blueberry systems, in addition to the effects of non-crop habitat. We conducted our study in 10 blueberry orchards during the growing season across the major blueberry producing counties in Georgia, United States. To estimate the spatial distribution of natural enemies, we conducted suction sampling at three locations in each orchard: within the forested border, along the edge of blueberry orchard adjacent to forested border, and within the interior of the blueberry orchard. Natural enemies maintained higher abundance over the season in unmanaged areas when compared with organic or conventional production systems. In the conventional orchards, natural enemies were more abundant in the surrounding non-crop area compared with the interior of the orchard. Populations were more evenly distributed in less intensive systems (organic and unmanaged). Our results indicate spatial structure in natural enemy populations is related to management practice, and less intensive management can retain higher abundance of natural enemies in blueberry systems. Considerations must be made towards promoting ecologically based management practices to sustain natural enemy populations and potentially increase the delivery of biological control services. Blueberries, Vaccinium spp., are an important commodity in North America, and production continues to increase (Strik and Yarborough 2005). The state of Georgia has recently become one of the top producers and has shown consistent growth from 59 million lbs in 2011 to 96 million lbs in 2014 (Melancon 2014). Increased production and acreage presents a variety of challenges for pest management as many larval insects contaminate the fruit prior to harvesting. A primary pest of concern is the spotted wing drosophila (Drosophila suzukii Matsumura) (Diptera: Drosophilidae), which has quickly spread and infested fruit crops across North America (Asplen et al. 2015). Insecticide application rates have increased by 50% since the first detection of spotted wing drosophila (Diepenbrock et al. 2016). In order to effectively combat pest encroachment in a growing blueberry industry, sustainable approaches are needed to conserve and promote biocontrol services. Natural enemies can dramatically reduce pesticide usage, contributing to reduced input costs and environmental risk (Tscharntke et al. 2007). However, the vast majority of natural enemy surveys in blueberry orchards focus on ground-dwelling predators and were not conducted in the southeastern region. In order to improve biological control programs and sustainable pest management, knowledge of natural enemy community composition is needed for this major blueberry producing region. Currently, growers depend solely on the use of insecticides to control pest populations, which disrupts biological control and reduces the ability for natural enemies to suppress pests (Johnson 2009). Blueberries are produced using conventional practices, which include intensive use of synthetic, broad-spectrum pesticides (Boutin et al. 2008), or organic practices, which employ reduced-risk insecticides (Sciarappa et al. 2008). Organic management practices promote natural enemy diversity compared with conventional practices (Weibull et al. 2003, Crowder et al. 2010, Cardenas et al. 2015), where broad-spectrum insecticides often cause higher mortality on natural enemies than pests (Cardenas et al. 2015). Minimally managed and abandoned orchards are unique perennial systems that can provide insight on how production practices, such as pesticide use, effect natural enemy populations (Prischmann et al. 2005, Horvath et al. 2015). To our knowledge, previous studies have not examined ‘unmanaged’ blueberry orchards. However, other agriculture production systems, such as olive orchards and forage crops, show higher natural enemy abundance in unmanaged compared with managed systems (Prischmann et al. 2005, Horvath et al. 2015), likely a function of soil and chemical disturbances associated with management practices. Habitat management through the addition of vegetation and non-crop flowering plants is a tool used to build healthy populations of natural enemies within cropping systems (Fiedler et al. 2008, Walton and Isaacs 2011, Gareau et al. 2013, Blaauw and Isaacs 2015). Non-crop vegetation within and surrounding agroecosystems play a large role in the spatial structure of natural enemy communities where immigration depends on the availability of resources (Schellhorn et al. 2014). Alternative food resources and refuge from insecticide applications may be situated along forested borders, thus driving higher abundances of natural enemies towards the edge of the agroecosystem. Grower adoption and investment in non-crop habitats can enhance natural enemies (Landis et al. 2005, Isaacs et al. 2009, Fox et al. 2015) and potentially allow predators to forage throughout the agroecosystem from edge to interior. For instance, ground-dwelling predators are more abundant throughout the blueberry system when more resources, such as mulch, are provided between blueberry rows (O’Neal et al. 2005, Renkema et al. 2012, Jones et al. 2016). Despite large-scale growth and importance of the blueberry industry in the southeastern United States, information of the natural enemies present is lacking. The goal of our study was to characterize the natural enemy community structure, and to evaluate how different management practices shape abundance and distribution throughout the agroecosystem. Our approach compared managed with unmanaged systems, which is vital to understanding factors that contribute to supporting natural enemies without human disturbance, and may foster strategies to improve delivery of biocontrol services in managed systems. We hypothesize that natural enemy abundance decreases as management intensity increases. We also expect within intensive management systems, predators are less impacted towards the forested border. Our study objectives were to i) characterize natural enemies found within southeastern blueberry agroecosystems; ii) determine the impacts of management practice on natural enemy abundance; and iii) evaluate the spatial distribution of natural enemies related to management practice. Materials and Methods Study Area We located 10 commercial blueberry orchards distributed in five counties across South Georgia, United States (Fig. 1). All counties are situated along the Satilla River Estuary and our study area included a spatial extent covering approximately 5,645 km2. The selected blueberry orchards consisted of rabbiteye (Vaccinium ashei Reade) (Ericaceae: Ericales) and southern highbush (Vaccinium corymbosum Linnaeus) (Ericaceae: Ericales). Orchards ranged in size between 0.52 ha and 76.5 ha, which we calculated using ArcGIS Release 10.3.1. We compared three different blueberry management systems: conventional (n = 4), certified organic (n = 3), and unmanaged (n = 3) (Fig. 1). Management classifications were made based on intensity and type of insecticides applied. The four conventional sites utilized broad-spectrum synthetic insecticides including organophosphates and pyrethroids, and in some cases a spinosyn (i.e., Delegate; Dow AgroSciences LLC, Indianapolis, IN) with herbicides applied between the blueberry rows for weed management. The three organic sites utilized reduced-risk organically certified (OMRI listed) insecticides and mowed vegetation between blueberry rows, but did not apply herbicides. The three unmanaged sites did not utilize pesticides and varied from abandoned orchards to small-scale harvesting with vegetation present between orchard rows mowed infrequently. Non-crop habitats surrounding sites consisted mostly of coniferous forests with dense shrubbery and blackberry (Rubus spp). The presence of vegetation between blueberry crop rows and herbicide application was determined by visual observation and discussions with each grower at all 10 sites. Fig. 1. View largeDownload slide Map of research sites sampled in Georgia, USA with symbols to indicate distribution of management practices. Fig. 1. View largeDownload slide Map of research sites sampled in Georgia, USA with symbols to indicate distribution of management practices. Sampling Each orchard was sampled weekly along a transect containing three stations for a total of 30 samples per week. Transects include locations of 25 m into the crop (orchard interior), along the orchard margin or first crop row (orchard border), and 15 m within the bordering, non-crop forested habitat (forest). Each sample consisted of 30 s of suction sampling with a 27.2 cc modified reversed-flow leaf blower (SH 86 C-E; Stihl, Waiblingen, Germany) containing an average air velocity of 63 m/s with a mesh bag over the intake to collect natural enemy communities in the canopy of the blueberry orchard. One entire blueberry plant was suction sampled at each location, and one non-crop block of 2 m2 was suction sampled in the adjacent forest border. The samples were transferred to plastic bags and placed on ice until permanent storage at −20°C in the laboratory. Individual specimens were separated from samples, identified to taxonomical level (family or order), and preserved in 95% ethanol at −20°C. Analysis To characterize the structure of predator communities found in and around blueberry orchards, natural enemy counts were grouped by feeding habits and taxonomically as either Arachnids, insect predators, or parasitoids to compare the impact of management practices on general patterns of natural enemy abundance. Most arachnids were identified to family with the exception of immature spiders lacking key features. All insect predators were identified to family, and parasitoids were grouped as parasitic Apocrita. Prior to formal analysis of overall natural enemy abundance patterns, we tested for spatial autocorrelation between mean overall natural enemy counts and commercial orchard sites using Mantel’s test with coordinates specified as latitude and longitude for each field location (package = ‘ADE4’; R Core Team 2016). Analysis of natural enemy population variability (total natural enemy abundance) in blueberry agroecosystems was analyzed using generalized least squares (gls) fitted with REML to account for repeated measures of communities within orchards overtime (i.e., random error partitioned with orchard site as random variable; i.e., 1| orchard site) (Pinheiro and Bates 2000). The response variable, total natural enemy abundance, was natural logarithm transformed prior to the analysis. The best fitting error structure that produced spread of residuals was ‘weights = varPower().’ The analyses were performed using R version 3.3.1 (R Core Team 2016) and significant main effects, management practice and transect, were analyzed with linear contrasts for multiple comparisons of mean responses. Results We collected a total of 1,113 natural enemies from suction sampling, including: 857 arachnids, 128 insect predators, and 128 parasitoids (Table 1). Arachnids made up of Araneae, the true spiders, combined with Opiliones, harvestmen, were the numerically dominant predatory arthropod taxa with 12 families. Insect predators were composed of nine families and Hymenopteran parasitoids were made up of parasitic Apocrita (Table 1). The distribution of Arachnids as the dominate predator taxa was consistent across all three management practices (Table 1; Fig. 2). Table 1. Descriptive summary of taxa collected from suction sampling throughout the 2016 study Taxa Conventional Organic Unmanaged Total Arachnids 78% 73% 78% Araneae Salticidae 1.31 ± 0.27 3.60 ± 1.08 5.46 ± 0.96 219 Immature spiders 1.19 ± 0.24 2.00 ± 0.60 5.04 ± 0.80 182 Araneidae 0.73 ± 0.15 2.47 ± 0.46 3.92 ± 0.67 150 Oxyopidae 0.46 ± 0.15 0.47 ± 0.22 3.04 ± 0.58 92 Thomisidae 0.42 ± 0.11 1.40 ± 0.38 1.88 ± 0.30 77 Lycosidae 0.19 ± 0.10 0.20 ± 0.11 1.25 ± 0.33 38 Linyphiidae 0.15 ± 0.07 0.27 ± 0.15 0.92 ± 0.25 30 Clubionidae 0.12 ± 0.06 0.53 ± 0.22 0.67 ± 0.21 27 Tetragnathidae 0.27 ± 0.09 0.13 ± 0.09 0.50 ± 0.18 21 Theridiidae 0.12 ± 0.06 0.13 ± 0.09 0.29 ± 0.11 12 Ulobridae 0.00 ± 0.00 0.00 ± 0.00 0.08 ± 0.06 2 Gnaphosidae Opiliones 0.04 ± 0.04 0.07 ± 0.07 0.00 ± 0.00 2 Phalangiidae 0.00 ± 0.00 0.07 ± 0.17 0.06 ± 0.08 5 Insect predators 12% 12% 11% Reduviidae 0.38 ± 0.14 0.67 ± 0.47 0.83 ± 0.26 40 Carabidae 0.08 ± 0.05 0.33 ± 0.21 0.92 ± 0.32 29 Vespidae 0.12 ± 0.06 0.27 ± 0.12 0.79 ± 0.29 26 Coccinellidae 0.08 ± 0.08 0.00 ± 0.00 0.46 ± 0.19 13 Syrphidae 0.00 ± 0.00 0.33 ± 0.16 0.13 ± 0.07 8 Chrysopidae 0.12 ± 0.06 0.20 ± 0.14 0.04 ± 0.04 7 Mantidae 0.00 ± 0.00 0.00 ± 0.00 0.08 ± 0.06 2 Anthocoridae 0.00 ± 0.00 0.07 ± 0.07 0.04 ± 0.04 2 Geocoridae 0.00 ± 0.00 0.00 ± 0.00 0.04 ± 0.04 1 Parasitoids 10% 15% 11% Parasitica 0.65 ± 0.22 2.27 ± 0.64 3.21 ± 0.93 128 Taxa Conventional Organic Unmanaged Total Arachnids 78% 73% 78% Araneae Salticidae 1.31 ± 0.27 3.60 ± 1.08 5.46 ± 0.96 219 Immature spiders 1.19 ± 0.24 2.00 ± 0.60 5.04 ± 0.80 182 Araneidae 0.73 ± 0.15 2.47 ± 0.46 3.92 ± 0.67 150 Oxyopidae 0.46 ± 0.15 0.47 ± 0.22 3.04 ± 0.58 92 Thomisidae 0.42 ± 0.11 1.40 ± 0.38 1.88 ± 0.30 77 Lycosidae 0.19 ± 0.10 0.20 ± 0.11 1.25 ± 0.33 38 Linyphiidae 0.15 ± 0.07 0.27 ± 0.15 0.92 ± 0.25 30 Clubionidae 0.12 ± 0.06 0.53 ± 0.22 0.67 ± 0.21 27 Tetragnathidae 0.27 ± 0.09 0.13 ± 0.09 0.50 ± 0.18 21 Theridiidae 0.12 ± 0.06 0.13 ± 0.09 0.29 ± 0.11 12 Ulobridae 0.00 ± 0.00 0.00 ± 0.00 0.08 ± 0.06 2 Gnaphosidae Opiliones 0.04 ± 0.04 0.07 ± 0.07 0.00 ± 0.00 2 Phalangiidae 0.00 ± 0.00 0.07 ± 0.17 0.06 ± 0.08 5 Insect predators 12% 12% 11% Reduviidae 0.38 ± 0.14 0.67 ± 0.47 0.83 ± 0.26 40 Carabidae 0.08 ± 0.05 0.33 ± 0.21 0.92 ± 0.32 29 Vespidae 0.12 ± 0.06 0.27 ± 0.12 0.79 ± 0.29 26 Coccinellidae 0.08 ± 0.08 0.00 ± 0.00 0.46 ± 0.19 13 Syrphidae 0.00 ± 0.00 0.33 ± 0.16 0.13 ± 0.07 8 Chrysopidae 0.12 ± 0.06 0.20 ± 0.14 0.04 ± 0.04 7 Mantidae 0.00 ± 0.00 0.00 ± 0.00 0.08 ± 0.06 2 Anthocoridae 0.00 ± 0.00 0.07 ± 0.07 0.04 ± 0.04 2 Geocoridae 0.00 ± 0.00 0.00 ± 0.00 0.04 ± 0.04 1 Parasitoids 10% 15% 11% Parasitica 0.65 ± 0.22 2.27 ± 0.64 3.21 ± 0.93 128 Percentages represent the proportion of each functional group per management practice and values represent the mean (±1 SE) of each taxon observed over the season for all sites in the respective management practice. Total represents the counts pooled over spatial–temporal extent of study for all taxa observed. View Large Fig. 2. View largeDownload slide Natural enemy composition in blueberry orchards estimated from suction samples pooled over all samples. Primary pie chart represents the proportion of each taxa calculated from total counts (N = 1113) with insect predators separated into second pie chart. Fig. 2. View largeDownload slide Natural enemy composition in blueberry orchards estimated from suction samples pooled over all samples. Primary pie chart represents the proportion of each taxa calculated from total counts (N = 1113) with insect predators separated into second pie chart. Spatial autocorrelation was not found among our blueberry orchards for the abundance of natural enemies (r2 = 0.005, P = 0.4373). A combination of sampling date, management practice, and orchard sampling location (transect) contribute to explaining variability of natural enemy populations in blueberry orchards (Table 2). Although orchard size ranged from 0.52 ha to 76.5 ha, transects among all sites remained the same size and differences in orchard size did not significantly correlate with natural enemy populations (Table 2). No significant interaction between orchard size and management practice indicated that any effects of orchard size were independent of management practice (Table 2). Table 2. Analysis of natural enemy population variability in blueberry agroecosystems Variable df F-value P value Sampling date 1 0.25 0.6203 Management practice 3 19.46 <0.0001* Transect 2 3.48 0.0330* Orchard size 1 0.04 0.8417 Sampling date:management practice 2 3.64 0.0281* Management practice:transect 4 1.03 0.3909 Management practice:size 2 0.03 0.9713 Residual 180 Variable df F-value P value Sampling date 1 0.25 0.6203 Management practice 3 19.46 <0.0001* Transect 2 3.48 0.0330* Orchard size 1 0.04 0.8417 Sampling date:management practice 2 3.64 0.0281* Management practice:transect 4 1.03 0.3909 Management practice:size 2 0.03 0.9713 Residual 180 Response variable used was total natural enemy abundance combining all natural enemy taxa. Analysis model was a Generalized Least Squares (gls) fitted with REML to account for repeated measures of communities within orchard overtime (i.e., random error partitioned with date nested within orchard). Table summarizes fixed effects included in the analysis. Sampling date was entered as a continuous variable, and natural enemy abundance was natural logarithm transformed prior to analysis. Variables connected by ‘:’ represent interaction terms. *P value < 0.05. View Large Natural enemies accumulated over time in orchards were dependent upon management practice (Fig. 3). The beginning of the sampling period contained an average of 2 (±0.88), 2.67 (±0.60), and 4.1 (±1.12) predators per sample in conventional, organic, and unmanaged, respectively. A significant interaction between week and management practice (Table 2) is explained by natural enemies increasing over the season in the organic (slope est. = 0.12 (0.05), t-value = 2.16, P-value = 0.03) and the unmanaged systems (slope est. = 0.13 (0.05), t-value = 2.39, P-value = 0.02), when compared with conventional where populations remained low the entire season (Fig. 3). Fig. 3. View largeDownload slide Seasonal mean (±1 SE) natural enemy abundance from suction samples pooled across transect and site to over time. Symbols represent corresponding management practice where samples were collected during the blueberry growing and harvest season. Fig. 3. View largeDownload slide Seasonal mean (±1 SE) natural enemy abundance from suction samples pooled across transect and site to over time. Symbols represent corresponding management practice where samples were collected during the blueberry growing and harvest season. Management practice and within orchard transects significantly influenced natural enemy populations (Table 2; Fig. 4). Unmanaged blueberry sites contained the highest mean natural enemy populations per suction sample 9.92 (±0.94) followed by organic 5.16 (±0.71) and conventional 2.14 (±0.26). Orchard transects within management practices also showed significant differences in the natural enemy community. In conventional orchards, the highest natural enemy counts were in forest transects compared with the interior blueberry orchard (Fig. 4), whereas, in organic orchards, border transects had the highest natural enemy populations (Fig. 4). In unmanaged orchards, natural enemies were observed at similar abundance across the three transects (Fig. 4). Fig. 4. View largeDownload slide Mean (±1 SE) natural enemy abundance from suction samples pooled across weekly sampling period and site. Bars represent the sampling location (forested habitat, canopy of the blueberry orchard border, and canopy of the blueberry orchard interior) in the respective management practice (conventional, organic, and unmanaged). Fig. 4. View largeDownload slide Mean (±1 SE) natural enemy abundance from suction samples pooled across weekly sampling period and site. Bars represent the sampling location (forested habitat, canopy of the blueberry orchard border, and canopy of the blueberry orchard interior) in the respective management practice (conventional, organic, and unmanaged). Discussion Our study provides the first characterization of common natural enemy groups found in southeastern subtropical blueberry production. The blueberry agroecosystem in Georgia is one of the fastest growing systems in the region and with an emerging array of pests, this research is ideal and timely for determining the role natural enemies play in pest suppression. Our study demonstrates intensive management practices negatively impact natural enemy abundance and alter natural enemy distribution. Our results also indicate habitat management may improve natural enemy abundance and potential biocontrol service delivery for southeast systems. The abundance of natural enemies was significantly different among the three management practices we evaluated. Conventional practices contained the lowest abundance and no accumulation of natural enemies over the season (Fig. 3). In addition, some taxa of predatory arthropods were completely absent from conventional fields, yet apparent in both organic and unmanaged blueberry systems (Table 2). Studies show significantly higher natural enemy abundance in organic systems (Boutin and Jobin 1998, Koss et al. 2005, Crowder et al. 2010, Martin 2016), and a recent meta-analysis affirms that organic practices increase biodiversity by an average of one-third compared with conventional practices in a variety of crop types with limited information on orchard systems and subtropical regions (Tuck et al. 2014). The current study contributes to lacking information in orchard systems, while also determining the effects within a subtropical region based on extensive field based research. A bioassay study on the lethal effects of registered insecticides in blueberry systems found that reduced-risk insecticides used in organic practices had a lower toxicity to natural enemies than broad-spectrum insecticides used in conventional practices (Roubos et al. 2014). Not only do our findings further support a pattern suggesting intensive management is likely limiting the abundance of natural enemies in managed systems, but we reveal that management practices contain unique distributions of natural enemies. Intense management practices result in reduced biocontrol services within an agroecosystem due to edge effects, where natural enemies use natural habitat adjacent to agriculture fields for refuge and resources (Rand et al. 2006). In the current blueberry agroecosystem, the intensive systems support this edge effect of more natural enemies located along the edge of the agroecosystem rather than the interior, similarly depicted in other perennial systems (Picchi et al. 2016, Ingrao et al. 2017). These intensively managed systems can prevent or filter natural enemies from entering the crop interior due to lack of habitat refuge or insecticide application (Schroter and Irmler 2013). In our conventional systems, we found the highest abundance of natural enemies in the forested border, whereas organic systems displayed a tendency for higher natural enemy abundance at the edge of the orchard. Rand et al. (2006) predicted edge effects should be weaker in less intensive systems, which is revealed by the unmanaged systems we found in our blueberry system with an even distribution of natural enemies from the interior to the forested habitat. The ultimate goal for natural pest management is to regulate pests throughout the system, which is influenced by the availability of suitable high-quality habitat within agricultural landscapes (Landis et al. 2000, Sunderland and Samu 2000, Marshall and Moonen 2002, Blaauw and Isaacs 2015). Our study suggests management intensity alters biocontrol opportunities by redistributing natural enemies within conventional systems, and to a lesser extent in organic systems. Within field non-crop habitats can alleviate the negative effects of intensive management by providing refuge and resources for natural enemies throughout an agroecosystem (Schellhorn et al. 2014, Amaral et al. 2016, Landis 2016). Previous studies in blueberry systems have examined different ground cover amendments between crop rows revealing bare ground negatively impacts ground dwelling natural enemies (O’Neal et al. 2005, Renkema et al. 2012, Jones et al. 2016). While our current study lacks a balanced design of within orchard vegetation compared with orchards without vegetation in each of the management practices, initial effects on natural enemy patterns were revealed. Vegetation between rows was present in organic and unmanaged systems, whereas conventional systems used herbicides to suppress vegetative growth leading to bare ground between rows. Both herbicide application and mowing affect vegetation structure but to varying degrees; mowing in organic and unmanaged orchards maintains stable vegetation, whereas herbicide in conventional orchards removes all vegetation. Infrequent mowing provides additional habitat structure for building predator populations and potential pest suppression (Letourneau et al. 2011). In the blueberry orchards with vegetation between rows, predators were estimated at 8.09 (±0.67) per plant compared with the bare ground between blueberry crop rows of 2.14 (±0.26). Within field habitat management appears to influence natural enemy presence; however, further study on the combined effects of insecticide applications and habitat management is needed to clarify the interactive roles of these management tactics. These results suggest that enhancing habitat in and around fields through reduced herbicide use and infrequent mowing may improve biocontrol services in southeast blueberry systems. Future experiments will evaluate the effects of varying vegetation between blueberry rows and optimizing habitat and pest management techniques towards attracting diverse natural enemy communities. Of the major natural enemy groups, generalist predators were the dominant taxa observed in this system and are known to commonly contribute to biological control in agricultural systems (Symondson et al. 2002, Richardson and Hanks 2009, Cardenas et al. 2015, Picchi et al. 2016). Salticidae and Araneidae were the most numerically abundant spider taxa observed across all management practices in this system (Fig. 2). Each taxon displays different foraging modes. Salticids, or jumping spiders, are hunting spiders that utilize a mobile foraging strategy to actively seek out prey with a greater diet breadth than other spider groups (Nyffeler 1999). Araneids, or orb-weaver spiders, are web-weaver spiders that utilize a ‘sit-and-wait’ strategy and depend on mobile prey that are abundant in the environment (Nyffeler 1999). The two most prevalent insect predators were Reduviidae, which consume prey through piercing-sucking mouthparts, and Carabidae, which consume prey through chewing mouthparts. Within blueberries systems, the combined feeding methods from these four generalist predatory taxa, along with specialist parasitoids, may help regulate a diversity of pests in the environment (Symondson et al. 2002). Foraging tactics vary among these groups, as each mode of feeding potentially partitions ecological niches in the environment (Gable et al. 2012). Continuing research will aim at uncovering feeding links between predators and key pests to determine which taxa effectively contribute to biological control. Information on predator diet will provide a foundation of knowledge to understand and promote biological control options in blueberry production. Overall, our study expands knowledge on natural enemies associated with southeastern subtropical U.S. blueberry agroecosystems and encourages the use of ecologically based management systems. Building ecologically based management systems requires comprehensive knowledge of the natural enemies present and the biological control services they provide. With the information provided in our study, we have identified the dominant predator taxa and can discern the impacts of management practice on natural enemy abundance and distribution. 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Environmental Entomology – Oxford University Press
Published: Feb 1, 2018
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