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Article

Arthropod Community Responses Reveal Potential Predators and Prey of Entomopathogenic Nematodes in a Citrus Orchard

1
Citrus Research and Education Center, UF-IFAS, Lake Alfred, FL 33850, USA
2
College of Plant Protection, Fujian Agriculture and Forestry University, Fuzhou 350002, China
*
Author to whom correspondence should be addressed.
Current Address: Department of Crop Science, Agricultural University of Athens, Iera Odos 75, 11855 Athens, Greece.
Agronomy 2022, 12(10), 2502; https://doi.org/10.3390/agronomy12102502
Submission received: 15 September 2022 / Revised: 5 October 2022 / Accepted: 10 October 2022 / Published: 13 October 2022
(This article belongs to the Special Issue Nematodes: Drivers of Agricultural Ecosystem Performance)

Abstract

:
The contributions of soil arthropods to entomopathogenic nematode (EPN) food webs are mainly studied in artificial conditions. We investigated changes in arthropod communities in a citrus orchard following soil inundation with Steinernema feltiae or Heterorhabditis bacteriophora. We hypothesized that arthropod taxa, which decline or increase in response to EPN augmentation, represent potential prey or predators of EPN, respectively. Soil was sampled periodically after nematodes were applied, DNA was extracted from organisms recovered by sucrose centrifugation, libraries were prepared, and the ITS2 and CO1 genes were sequenced using Illumina protocol. Species from 107 microarthropod (mites and collembola) families and 121 insect families were identified. Amplicon sequence variant (ASV) reads for H. bacteriophora were less than 10% of those for S. feltiae three days after inundation, whereas microarthropod ASVs were double in plots with H. bacteriophora compared to those with S. feltiae. Significantly fewer microarthropod and insect reads in S. feltiae compared to untreated plots suggest the possibility that S. feltiae preyed on mites and Collembola in addition to insects. The responses over time of the individual microarthropod species (MOTU) suggest that regulation (up or down) of these EPN resulted from a cumulative response by many species, rather than by a few key species.

1. Introduction

Entomopathogenic nematodes (EPNs) belong to two families, Steinernematidae and Heterorhabditidae, both with a worldwide distribution except for Antarctica. First noted a century ago [1], EPNs received little attention for several decades until their potential for biological control became increasingly apparent [2]. Now they are among the most well-studied soil taxa, both for insect management and as model systems for symbioses such as parasitism and mutualism [3]. All steinernematid and heterorhabditid species are obligately associated with bacterial species in the genera Xenorhabdus or Photorhabdus, respectively. The bacteria are also entomopathogens that are released into the insect hemocoel after the nematodes gain entry either through natural body openings or by penetrating the cuticle. Insects die from septicemia and the nematodes, and bacteria consume the tissue while completing several generations. Nematode development arrests at the 3rd stage when conditions in the cadaver deteriorate, and a cohort of tens of thousands of infective juveniles (IJs) emerges in search of new hosts. Several of the more than 100 described EPN species are currently formulated as inundative biological insecticides that are applied to soil or foliage to help manage a growing number of insect pest species [4]. Exotic EPN species have been employed successfully in classical biocontrol programs targeting invasive pest insects [5]. Conservation biocontrol tactics to better exploit EPN services have also been studied and proposed [6,7].
Conserving or enhancing biocontrol by augmented [8,9] or indigenous [10,11] EPNs would be desirable, given the high cost of producing them and the generally low persistence of most species following release. Smits [12] and Griffin [13] described a five-phase EPN inoculum progression model that exhibits a rapid, major decline immediately upon application, followed by further gradual decline and eventually a period of maintenance (at or below detectable levels) or local extinction. Physical forces affecting EPN survival [14,15,16] and efficacy [17,18] are recognized to some extent, but less is known about how food webs affect the post-application survival of commercial EPN [3]. While abiotic stressors of EPN, such as UV radiation and desiccation, are lethal initially, a myriad of EPN antagonists inhabit the surface and deeper soil horizons. Indeed, most common guilds of soil-dwelling organisms are thought to be capable of modulating EPN populations in some manner [13]. Nevertheless, the extent to which specific taxa drive measurable predator–prey dynamics is virtually unknown [19]. Plentiful laboratory assays have identified microarthropods—mites, collembola, monurans and diplurans—that readily graze and persist on nematodes [20,21,22,23]. Rarer are studies of microarthropod numeric responses to EPN in nature [24,25,26]. The roles of microarthropods [27] and non-pest insects [28] as hosts that support EPN persistence are virtually unknown. Nematophagous fungi and their associations with EPN have been subjects of numerous laboratory experiments [29,30] and field studies [31,32]. Bacterial ectoparasites [33,34] and free-living nematodes that scavenge within insect cadavers appear to be major, widespread EPN antagonists [25,35,36,37].
The capacity to study suites of diverse, cryptic organisms in nature expanded significantly with advances in qPCR technology [38,39], and the continued development and cost reduction of metagenomic tools now provide the potential to detect all species in an environmental sample for which a given gene region is represented in the molecular databases [40]. The enormous expansion in the breadth of taxonomic coverage afforded by metabarcoding of environmental DNA increases the opportunity to detect species that interact directly with EPN or are measurably affected by them indirectly. The technology also broadens the scope of possible inquiry. For example, comprehensive coverage of the soil community responses to EPN augmentation could reveal whether characteristics of some EPN species or genera make them broadly more susceptible to predation (less likely to persist) or more rhizosphere competent as efficient predators of diverse organisms.
Here, we describe changes in an orchard soil community as measured by metabarcoding of soil DNA following augmentation with two EPN species. Our objective was to identify potential antagonists and prey of EPN based on significant differences between populations in augmented and non-augmented plots. We used universal primers to build libraries from ITS2 rDNA and COI mtDNA to target arthropods and nematodes. We hypothesized that some predators or competitors of EPN would increase in abundance, whereas specific prey of EPN would measurably decrease following appreciable EPN augmentation. Therefore, significant differences between populations in different treatments should represent potential predators, prey, competitors or indirectly affected nontargets. We anticipated different food web responses to the two augmented species because we expected a more rapid decline in the numbers of amplified sequence variants (ASV) of Heterorhabditis bacteriophora (Poinar, 1976), compared to Steinernema feltiae (Filipjev, 1934) [41]. Compared to the control plots, we predicted an overall reduction in the number of insect (prey) ASV and an increase in those for microarthropods (predators) in the EPN-augmented plots. We also anticipated responses, both positive [42] and negative [43], by some nematode species.

2. Materials and Methods

The experiment was conducted on a 0.1 ha plot in a mature citrus orchard in Polk County, central Florida (28.240771083739954, −81.76575482177549). The experimental design was randomized complete block with 8 replications of three treatments, H. bacteriophora (Nemasys®, BASF Corportation), S. feltiae (Nemasys G®, BASF Corportation), and an untreated control. The experimental units were single citrus trees (24 trees in total). Entomopathogenic nematodes were applied to a square area two meters per side under the tree canopy, by spaying the soil surface with 300 infective juveniles per square centimeter (12 M IJs per tree). Compressed nitrogen was used to spray aliquots of nematodes suspended in 10 L water at 1.41 kg/cm2 pressure. Microjet irrigation occurred during the application and for one hour afterward.
Soil samples were taken from all 24 trees at 3, 7, 14, and 28 days after nematode application. A soil sampling tube was used to collect eight soil cores (dia 2.5 cm × 30 cm depth) from each plot, which were combined into a single composite sample of approximately 2000 mL volume. Each composite sample was gently mixed and then nematodes, soil microarthropods, insects and associated microorganisms were extracted by sucrose centrifugation from 250 cm3 of soil [44] and collected in falcon tubes of 15 mL. After aspirating excess water, soil samples were concentrated in Eppendorf tubes where DNA was extracted with DNeasy® PowerSoil Kit (Qiagen). The DNA concentrations were measured using the Qubit® dsDNA High-Sensitivity Assay Kit (Thermo Fisher Scientific, Waltham, MA, USA). Two libraries were created because two set of primers were employed to target two groups—nematodes and soil microarthropods. For the nematodes, the target region was ITS 2 of the rDNA gene using previously reported primers. The average amplicon length was 450 bp for steinernematids and 350 bp for heterorhabditids. The universal primers were AD58F (5′-TCGATGAAAAACGCGGCAA-3′; [40]) forward and AB28R (5′-ATATGCTTAAGTTCAGCGGGT-3′; [45]) reverse. For microarthropods, universal primers for COI of mitochondrial DNA were mlCOIintF (5′- GGWACWGGWTGAACWGTWTAYCCYCC; [46]) forward, and jgHCO2198 (5′- TAIACYTCIGGRTGICCRAARAAYCA-3′; [47]) reverse.
Following the Illumina protocols, library preparation consisted of two amplifications and two clean up steps. For the first amplification “amplicon PCR”, overhang adapter sequences were appended to the primer pair for compatibility with Illumina index and sequencing adapters. Samples were standardized at 5 ng/mL DNA concentration. For nematodes, samples were amplified with the following conditions: initial denaturation at 95 °C for 3 min, 30 cycles of denaturation at 98 °C for 20 s, annealing at 56.5 °C for 30 s, elongation at 72 °C for 60 s and terminal elongation at 72 °C for 10 min. The same PCR conditions were used for microarthropod amplification, with the only difference of an annealing temperature at 50 °C for 30 s. For all libraries, a single 25 μL PCR reaction containing 2.5 μL of template at 5 ng/μL (12.5 ng total), 12.5 μL of NEBNext® High-Fidelity 2X PCR Master Mix (New England biolabs), 1 μL of each 10 pM overhang primer and 8 μL of 10 mM Tris pH 8.5 was used. DNA extracted from a laboratory culture of the nematodes Steinernema glaseri (Steiner, 1929) and Heterorhabditis indica (Poinar, Karunakar & David, 1992) were used as positive controls, while negative controls consisted of purified, nuclease-free water instead of template.
PCR products were verified on 1% agarose gels after staining with SYBR™ Safe DNA Gel Stain. All amplicon PCR products were purified with 1.0 × HighPrep™ PCR post PCR clean up system (MagBio Genomics, Inc., Gaithersburg, MD, USA) and eluted in 50 μL of 10 mM Tris pH 8.5. For the following index PCR, amplicons were used as template for a limited cycle amplification adding dual-index barcodes: P5 and P7 Illumina sequencing adapters using Nextera XT Index Kit (FC-131-1001) for EPN and XT Index Kit (FC-131-1004) for microarthropods (Illumina, San Diego, CA, USA). The index PCR conditions were initial denaturation at 95 °C for 3 min, 8 cycles of denaturation at 98 °C for 30 s, annealing at 55 °C for 30 s, and elongation at 72 °C for 30 s and a terminal elongation at 72 °C for 10 min. Each 50 μL PCR reaction tube contained 5 μL of template, 25 μL of 2× KAPA HiFi HotStart ReadyMix (KAPA biosystems), 5 μL of Index Primers (N7XX) and 5 μL of Index 2 Primers (S5XX). The total number of 192 index PCR products purified with 1.1× magnetic beads, eluted in 25 μL and quantified using Qubit 3.0 fluorometer. Finally, libraries were normalized in equal molar concentrations of 4 nM and pooled together in a single library in aliquots of 10 μL. The library was sequenced using MiSeq 2 × 300 bp paired-end Illumina at the Interdisciplinary Center for Biotechnology Research (ICBR) of University of Florida.
Bioinformatics: ICBR delivered raw data in fastq format, which were demultiplexed and separated into respective sample identification codes. FASTQC v0.11 (Andrews et al., 2015) was used for quality assessment of each read, and then all the quality information was combined into a single viewable document using MULTIQC (Ewels et al., 2016). The constructed libraries of ITS 2 rDNA and COI mtDNA were used for nematode and microarthropod identification, respectively. In both datasets, R1 and R2 reads were combined and dereplicated with the ASV-based approach, in which DADA2 was the denoising method, through the QIIME2 v2019.4 pipeline, including removal of primer sequences, truncating sequences by length and removing chimeric sequences with a de novo approach according to Callahan [48], which resulted in a length of 350–450 bp for nematodes and 313 bp for microarthropods. We then generated count tables by mapping ASVs, assigning taxonomy by generating input files for taxonomy assignment in QIIME2 from the NCBI database. A standalone database was generated including all the non-redundant nucleotide sequences from all traditional divisions of GenBank (ftp://ftp.ncbi.nlm.nih.gov/blast/db/nr.gz; accessed on 20 December 2020.) employing an NCBI command-line tool (BLAST+) to integrate BLAST directly into our workflow. BLAST taxonomy was assigned to ASVs to create molecular operational taxonomic units (MOTUs) defined by the NCBI accession numbers. For statistical analyses, MOTU datasets were corrected according to the sample DNA quantity and then were log transformed. Analysis of variance was performed primarily on all three major groups (total sum of the reads) and the MOTUs within the groups (389 Microathropod MOTUs, 311 insect MOTUs and 20 nematodes species) applying a repeated measures approach (time, plot and treatment) where experimental plots (trees) were randomly nested within the three treatments. For each significant taxa, post hoc analysis was performed to determine differences between the means using Least Significant Difference (LSD-test) at which p-values were adjusted by a Bonferroni correction approach. To eliminate false positives, we analyzed only taxa that were detected in 75% or more of the sites. All statistical datasets were created in R (R Development Core Team). The ‘agricolae’ package [49] was used for the statistical analyses, and plots were reproduced by ‘Sigmaplot’ version 14.0 and ‘R studio’. Treatments’ effects on native nematodes and microarthropods were further explored with redundancy analysis using Canoco v.5 [50].

3. Results

The high-throughput sequencing produced two datasets, based on the two DNA loci. The ITS2 revealed 4,800,700 reads of which 51.7% (2,485,154) passed the quality filters and were denoised, merged and characterized as non-chimeric. Dereplication resulted in 6297 unique amplicon sequence variants (ASVs), of which 44% (2793 ASVs) were characterized as unidentified and 4.7% (301 ASVs) as Nematoda. Combining ASVs with the same accession number, removing all ASVs with less than 10 reads and setting a threshold of 75% coverage, we identified 18 species of nematodes that were the basis of further statistical analyses. The COI dataset yielded 7,060,355 reads that reduced to 5,691,737 (80.6%) after filtering, denoising, merging and chimera removal. Dereplication resulted in 6702 ASVs, of which 1.3% (92 ASVs) were characterized as unidentified, and by using the same restrictions as for ITS2, we produced 398 MOTUs of soil microarthropods from 108 families (93 mites, 13 collembolans and 2 diplurans) and 307 insect MOTUs from 122 families. All identified nematode, microarthropod and insect species are given in Supplementary Table S1.
Augmented EPN species differed in persistence. Three days following augmentation, an average of 7136 H. bacteriophora reads compared to 91,180 S. feltiae reads were detected in their respective plots. Between days 3 and 28, H. bacteriophora reads declined an additional 54% (3285) compared to 36% for S. feltiae (57,998) (Table 1).
Both nematode treatments increased the total nematode read abundance (Figure 1, top left panel). There were significant treatment–time interactions for both the total number of nematode reads (p = 0.002; adjusted R2 = 50.4; Supplementary Table S2) and those of the native nematodes (p = 0.002; adjusted R2 = 35.5; Supplementary Table S3): the addition of S. feltiae increased the read abundance of identified nematodes above that in the control plots for at least two weeks, whereas H. bacteriophora had no significant effects on the total nematode reads at any time (Figure 1, top right panel). The numbers of native nematode reads responded to EPN augmentation, declining below the levels in untreated plots on day 7 in plots amended with both species and on day 28 in plots amended with S. feltiae (Figure 1, bottom right panel; Supplementary Figure S1). Although the observed reads were fewer (p < 0.001) in plots treated with S. feltiae (46526 ± 7694) than those augmented with H. bacteriophora (96383 ± 27201), neither treatment differed significantly from the control (64400 ± 8400) (Figure 1, bottom left panel).
Four indigenous entomopathogenic nematodes were detected at relatively high frequency over time in the 24 sites, with Heterorhabditis indica (Poinar, Karunakar & David, 1992) occurring in 100% of the trees and 87.5% of the total samples, along with Heterorhabditis zealandica (Poinar, 1990) in 25%/15.6%, Steinernema glaseri (Steiner, 1929) in 83.3%/61.4% and Steinernema scapterisci (Nguyen & Smart, 1990) in 79.1%/42.7%, respectively. The identities were confirmed by phylogenetic analysis and, in some cases, by using species-specific qPCR primers/probes. The only nematode species with detectible responses to the treatments were bacterivores Acrobeles complexus (Thorne, 1925) (p < 0.003) and Acrobeloides saaedi (Siddiqi, De Ley and Khan, 1992) (p < 0.065) and a plant parasitic nematode Pratylenchus sp. (p < 0.068) (Figure 2). There were several positive associations between native EPN and bactivorous nematodes, including S. glaseri and Acrobeles sp. (Spearman’s ρ = 0.30, p = 0.003), H. indica and A. complexus (ρ = 0.41, p = 0.0001), H. indica and A. saeedi (ρ = 0.23, p = 0.02), Oscheius tipulae (Lam & Webster, 1971) and A. complexus (ρ = 0.23, p = 0.03) and Oscheius tipulae and Pseudoacrobeloides sp. (ρ = 0.29, p = 0.005).
The COI primers revealed 10 orders and 107 families of soil microarthropods comprising mites, collembolans, proturans and diplurans. As a group, microarthropods responded differently to the two inoculated EPN species. Microarthropod abundance and richness were greater in plots treated with H. bacteriophora than in those with S. feltiae (Figure 3, Table 2; Supplementary Figure S2), while neither treatment differed from the control. This pattern was mostly driven by the mites, which comprised 80% of microarthropod reads (Figure 3 and Figure 4). The S. feltiae treatment also reduced collembolans with respect to both H. bacteriophora and control, while no treatment differed in Collembola richness (Table 2).
Eight microarthropod families responded (p < 0.10) to the treatments with altered population dynamics. Ceratozetidae (Acari: Oribatida), Onychiuridae (Collembola: Poduromorpha), Tectocepheidae (Acari: Oribatida) and Laelapidae (Acari: Mesostigmata) exhibited population flux that was potentially driven by taxa that prey on EPN, whereas patterns for Tullbergiidae (Collembola: Poduromorpha), Japygidae (Diplura) and Eupodidae (Acari: Prostigmata) suggest the possibility that some taxa may serve as hosts that sustain EPN (Figure 5). Predictably, the population patterns of taxa within families were inconsistent (not shown), and just seven microarthropod MOTUs from the Oppiidae (Acari: Oribatida), Eupodidae (Acari: Prostigmata) and Tydeidae (Acari: Prostigmata) exhibited significant response to the treatments (Table 3). Two taxa increased in response to H. bacteriophora augmentation, while four species in S. feltiae plots declined. The difference in number of reads between those species that responded significantly to H. bacteriophora and S. feltiae was just 2.1% as numerous as the difference in the reads among the remaining species.
Augmented S. feltiae reduced the abundance of the ant Myrmica semiparasitica, whereas a geometrid moth Stamnodes affiliate increased in response to H. bacteriophora (Table 3). The effects of S. feltiae were apparent on the entire class of Insecta, which maintained population density throughout the trial in untreated plots but declined markedly in response to the steinernematid to about one-third of control levels by the end of the trial (Figure 6).

4. Discussion

Entomopathogenic nematode augmentation elicited responses by each of the three groups of soil organisms considered here. Compared to controls, microarthropod, insect and native nematode responses depended on the EPN species introduced into the plots. As anticipated, the post-application survival capacity of the augmented species was related to some of those patterns. Three days post-augmentation, the reads for H. bacteriophora were less than 10% of those for S. feltiae. Thereafter, the decline of both species was more gradual, but still more pronounced for H. bacteriophora than for S. feltiae. Duncan et al. [41] reported exogenous H. bacteriophora declining to levels that were 1% those of exogenous S. carpocapsae and S. riobrave within 5 days of application to soil beneath citrus trees. Numerous reports (reviewed by Strong [51]) indicate generally lower short-term persistence of heterorhabditids compared to steinernematids. The effect of EPN augmentation on the total abundance of nematodes and other organisms in soil can only be approximated by barcode reads because of the interspecific and life stage variability of tandem repeats [52,53]. Nevertheless, the negligible increase in the total nematode reads following application of H. bacteriophora compared to more than doubling in plots with S. feltiae was striking and suggests that the temporal impacts of EPN augmentation on food webs are highly species-specific and may be very different [26]. The total nematode reads in plots augmented with S. feltiae exceeded those in control and H. bacteriophora treatments for at least two weeks, and this was followed by reductions of native nematodes. Previous reports of EPN augmentation inducing a reduction of native EPN attributed competition or natural enemies and classical predator–prey dynamics as the likely causes [25,36,54]. Consequently, avoiding EPN augmentation immediately prior to seasonal recruitment of herbivorous larvae into soil is recommended to conserve the services of native EPN in Florida citrus [7]. Although H. bacteriophora inundations may have increased some soil mites early in the trial, we detected no increased natural enemy density in the S. feltiae treatments that might have reduced the numbers of native nematodes detected in those plots. The ability of exogenous EPN to reduce plant-parasitic nematodes has been reviewed by Kenney and Eleftherianos [55] and most plausibly attributed to allelopathy [56,57] and the induction of plant defense systems [58,59]. Plant defenses seem less likely than allelopathy to have affected the two bactivorous species shown to decrease here. Moreover, we anticipated, but did not find, an increase in some bactivorous nematode populations capable of competing with EPN for resources in insect cadavers [36,60,61]. Positive associations between EPN and bactivorous nematodes, such as those found here between bacterivores and the obligate and facultative [62] EPN S. glaseri, H. indica and O. tipulae, may require longer than 28 days to develop.
Our hypothesis that EPN augmentation would increase the total microarthropod numbers above those in controls was not supported; however, the higher microarthropod prevalence in plots treated with H. bacteriophora compared to S. feltiae may reflect higher rates of predation on the augmented heterorhabditid. Perhaps differences in rhizosphere competence of EPN species, such as those seen in this and previous studies [51], provide a more sensitive means of detecting organisms that regulate EPN as either predators or hosts. Indeed, the trends for both EPN treatments suggest not only that microarthropods preyed more on H. bacteriophora than S. feltiae, but that some mites, springtails and diplurans may have been hosts for S. feltiae. The feeding habits and behavior of soil mite species that prey on nematodes have been widely characterized under controlled conditions [21,22,63] and from field observations [20]. As seen in this study, Wilson and Gaugler [24] reported an inverse relationship between survival of H. bacteriophora and both mite and collembolan abundance in the field. Given the predatory nature of so many microarthropod species, the lack of a significant positive response by more than a single species to EPN augmentation suggested that many taxa contributed incrementally, along with unmeasured factors, to the rapid decline of H. bacteriophora. By contrast, there are few reports [25] consistent with the overall reduction of mites and springtails by EPN applications found here in the plots inundated with S. feltiae. Joharchi et al. [64] observed bulb mites Rhizoglyphus robini (Acari: Acaridae) in alfalfa to consume large numbers of stem nematodes Ditylenchus dipsaci (Tylenchida: Anguinidae). Later, Nermuť et al. [27] described EPN readily invading and killing R. robini, reporting mortality up to 30%, with as many as 30 infective juveniles (IJ) in parasitized individuals. However, they reported an inverse correlation between EPN size and ability to infect the mites, which argues against the likelihood that the relatively large S. feltiae could directly attack and kill most soil mites. Similarly, although more Japygidae were detected in the untreated plots, the high motility of most diplurans should impede infection by EPN. Collembolan predators of nematodes are also well documented. Laboratory studies by Gilmore [65] revealed 10 of 12 tested Collembola species fed on nematodes, Thimm et al. [66] verified nematode consumption from springtail gut contents and nematophagy under natural conditions was ascertained [67]. However, there are no reports of nematode predation on Collembola to explain the apparent response to S. feltiae in this study.
Metabarcoding revealed more than 100 insect taxa, of which a considerable number are not soil-dwelling insects. This merits further investigation, because barcoding of soil DNA is probably a useful practice to detect insects that are not only residing in soil. A similar approach is applied to detect vertebrates such as amphibians by filtering water in multiple locations of a river [68,69]. As there is no comprehensive record of soil insects in Florida citrus orchards, this work is the first to assess a community that potentially supports the rich and abundant EPN guild on the peninsula [15]. The predicted broadly negative response of insect ASVs to the S. feltiae treatment was like that of microarthropods where fewer total insect reads could reflect an accumulation of non-significant reductions in many taxa. Given the high mobility of most insects, the reduction may represent emigration due to predator avoidance [70,71] in addition to predation. The insect with the strongest response was possibly misidentified as Myrmica semiparasitica (Hymenoptera: Formicidae), a small, social parasitic ant with a reported distribution from southeastern Canada and New England to Ohio and Illinois. Regardless, the results agree with past reports showing that EPN readily infect Formicidae in the laboratory [72] and reduce Solenopsis (Hymenoptera: Formicidae) populations when applied to field colonies [73,74]. However, we are not aware of reports that entomopathogenic nematodes infect ants under natural conditions. A failure of insects to respond to H. bacteriophora is consistent with its more rapid disappearance than S. feltiae. A significant increase in response to H. bacteriophora by the herbivorous, non-subterranean geometrid moth Stamnodes affiliata (Lepidoptera: Geometridae) may also have been a misidentification or perhaps the result of an indirect effect such as a reduction of a natural enemy.
Our data highlight both the potential and a serious shortcoming of metagenomic tools to study soil communities [75]. The broad MOTU array delimited by barcoding provided a more accurate representation of the species richness and identity in this orchard than could be reasonably done using other methods, even by expert taxonomists. If identified, the ecological function of responsive species can then be studied in detail. For example, we found evidence that many fungi and the bactivorous nematodes Acrobeles complexus and Acrobeloides saeedi were suppressed by EPN augmentation, which, if verified by further studies, may be found to involve the same or different mechanisms reported to affect plant parasitic nematodes. Further exploration at this site for M. semiparasitica or similar ants could resolve the identity of that species and whether it truly sustains EPN in Florida orchards. Nevertheless, we were unable to identify candidate natural enemies of EPN, partly because so few MOTU were identified at higher resolution than family. At least one mite (accession JX863034.1) in the Oppiidae may have preyed heavily on H. bacteriophora, while several other responsive but unidentified species in Table 3 may have functioned as predators or prey depending on the EPN species introduced into the soil. The absence of genomic records for most microarthropod species will obscure their identity in the foreseeable future because, while 55,000 species of mites were described by the turn of the last century [76], estimates of their species richness range from a few to many millions of species [77]. Most families in the NCBI database have critically low coverage, with the vast majority of entries identified only at the family level. Despite this shortcoming, the metagenomic approach used here provided important insights into how soil communities respond to EPN augmentation. The difference in the rhizosphere competence of the two EPN appears to have been driven by superior predatory capacity of S. feltiae on mites and insects, which also extended the duration of non-target effects on other nematodes that are associated with elevated nematode abundance in soil [25,26,37]. Moreover, the minor (2.1%) contribution by significantly responsive species to treatment differences in the microarthropod abundance indicates that this major predator guild functions collectively and broadly, with few key species, to regulate a nematode equilibrium in soil.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/agronomy12102502/s1, Figure S1: Redundancy Analysis (RDA), response of nematodes; Figure S2: Redundancy Analysis (RDA), response of microarthropods Table S1: NCBI, taxa detection; Table S2: log(natural) total nematodes versus Treatment, sampling Day, replication; Table S3: log(natural) native nematodes versus Treatment, sampling Day, replication.

Author Contributions

Conceptualization, A.D., S.-Y.W. and L.W.D.; Data curation, A.D. and L.W.D.; Formal analysis, A.D. and L.W.D.; Investigation, A.D., S.-Y.W. and H.R.; Methodology, A.D., S.-Y.W. and H.R.; Project administration, L.W.D. and A.D.; Software, A.D.; Writing – original draft, A.D.; Writing – review & editing, L.W.D. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by International Cooperation Project of Fujian Province (2021I0006), the Strait Postdoctoral foundation of Fujian Province (2021A001) and the US-Egypt Project cycle 17 (no.172). This article is derived from subject data funded in part by NAS and USAID, and that any opinions, fundings, conclusions or recommendations expressed in it are those of the author alone, and do not necessarily reflect the views of USAID or NAS.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Steiner, G. Aplectana kraussei n. sp., eine in der Blattwespe Lyda sp. parasitierende Nematodenform, nebst Bemerkungen über das Seitenorgan der parasitischen Nematodenitle. Zentralblatt Bakteriol. Parasitenkd. Infekt. Krankheiten Hyg. 1923, 2, 14–18. [Google Scholar]
  2. Poinar, G.O.; Grewal, P.S. History of entomopathogenic nematology. J. Nematol. 2012, 44, 153–161. [Google Scholar] [PubMed]
  3. Stock, S.P. Diversity, Biology and Evolutionary Relationships. In Nematode Pathogenesis of Insects and Other Pests. Sustainability in Plant and Crop Protection; Campos-Herrera, R., Ed.; Springer: Cham, Switzerland, 2015. [Google Scholar] [CrossRef]
  4. Grewal, P.S.; Ehlers, R.U.; Shapiro-Ilan, D.I. Nematodes as Biocontrol Agent; Springer International Publishing: Cham, Switzerland, 2005; ISBN 0851990177. [Google Scholar]
  5. Parkman, J.P.; Hudson, W.G.; Frank, J.H.; Nguyen, K.B.; Smart, G.C. Establishment and Persistence of Steinernema scapterisci (Rhabditida: Steinernematidae) in Field Populations of Scapteriscus spp. Mole Crickets (Orthoptera: Gryllotalpidae). J. Entomol. Sci. 1993, 28, 182–190. [Google Scholar] [CrossRef]
  6. Lewis, E.E.; Campbell, J.F.; Gaugler, R. A conservation approach to using entomopathogenic nematodes in turf and landscapes. Conserv. Biol. Control 1998, 235–254. [Google Scholar] [CrossRef]
  7. Stuart, R.J.; El Borai, F.E.; Duncan, L.W. From Augmentation to Conservation of Entomopathogenic Nematodes: Trophic Cascades, Habitat Manipulation and Enhanced Biological Control of Diaprepes abbreviatus Root Weevils in Florida Citrus Groves. J. Nematol. 2008, 40, 73. [Google Scholar]
  8. Duncan, L.W.; Stuart, R.J.; El-Borai, F.E.; Campos-Herrera, R.; Pathak, E.; Giurcanu, M.; Graham, J.H. Modifying orchard planting sites conserves entomopathogenic nematodes, reduces weevil herbivory and increases citrus tree growth, survival and fruit yield. Biol. Control 2013, 64, 26–36. [Google Scholar] [CrossRef]
  9. Shields, E.J. Utilizing persistent entomopathogenic nematodes in a conservation or a more classical biological control approach. In Nematode Pathogenesis of Insects and Other Pests: Ecology and Applied Technologies for Sustainable Plant and Crop Protection; Springer International Publishing: Cham, Switzerland, 2015; pp. 165–184. ISBN 9783319182667. [Google Scholar]
  10. Hiltpold, I.; Toepfer, S.; Kuhlmann, U.; Turlings, T.C.J. How maize root volatiles affect the efficacy of entomopathogenic nematodes in controlling the western corn rootworm? Chemoecology 2010, 20, 155–162. [Google Scholar] [CrossRef] [Green Version]
  11. Campos-Herrera, R.; Blanco-Pérez, R.; Bueno-Pallero, F.Á.; Duarte, A.; Nolasco, G.; Sommer, R.J.; Rodríguez Martín, J.A. Vegetation drives assemblages of entomopathogenic nematodes and other soil organisms: Evidence from the Algarve, Portugal. Soil Biol. Biochem. 2019, 128, 150–163. [Google Scholar] [CrossRef]
  12. Smits, P.H. Post-application Persistence of Entomopathogenic Nematodes. Biocontrol Sci. Technol. 1996, 6, 379–388. [Google Scholar] [CrossRef]
  13. Griffin, C.T. Behaviour and population dynamics of entomopathogenic nematodes following application. In Nematode Pathogenesis of Insects and Other Pests: Ecology and Applied Technologies for Sustainable Plant and Crop Protection; Springer International Publishing: Cham, Switzerland, 2015; pp. 57–95. [Google Scholar] [CrossRef]
  14. Gaugler, R.; Bednarek, A.; Campbell, J.F. Ultraviolet inactivation of heterorhabditid and steinernematid nematodes. J. Invertebr. Pathol. 1992, 59, 155–160. [Google Scholar] [CrossRef]
  15. Campos-Herrera, R.; Pathak, E.; El-Borai, F.E.; Stuart, R.J.; Gutiérrez, C.; Rodríguez-Martín, J.A.; Graham, J.H.; Duncan, L.W. Geospatial patterns of soil properties and the biological control potential of entomopathogenic nematodes in Florida citrus groves. Soil Biol. Biochem. 2013, 66, 163–174. [Google Scholar] [CrossRef] [Green Version]
  16. Campos-Herrera, R.; El-Borai, F.E.; Rodríguez Martín, J.A.; Duncan, L.W. Entomopathogenic nematode food web assemblages in Florida natural areas. Soil Biol. Biochem. 2016, 93, 105–114. [Google Scholar] [CrossRef]
  17. Portillo-Aguilar, C.; Villani, M.G.; Tauber, M.J.; Tauber, C.A.; Nyrop, J.P. Entomopathogenic nematode (Rhabditida: Heterorhabditidae and steinernematidae) response to soil texture and bulk density. Environ. Entomol. 1999, 28, 1021–1035. [Google Scholar] [CrossRef]
  18. Kaspi, R.; Ross, A.; Hodson, A.K.; Stevens, G.N.; Kaya, H.K.; Lewis, E.E. Foraging efficacy of the entomopathogenic nematode Steinernema riobrave in different soil types from California citrus groves. Appl. Soil Ecol. 2010, 45, 243–253. [Google Scholar] [CrossRef]
  19. Campos-Herrera, R.; Stuart, R.J.; Pathak, E.; El-Borai, F.E.; Duncan, L.W. Temporal patterns of entomopathogenic nematodes in Florida citrus orchards: Evidence of natural regulation by microorganisms and nematode competitors. Soil Biol. Biochem. 2019, 128, 193–204. [Google Scholar] [CrossRef]
  20. Walter, D.E.; Ikonen, E.K. Species, guilds, and functional groups: Taxonomy and behavior in nematophagous arthropods. J. Nematol. 1989, 21, 315–327. [Google Scholar] [PubMed]
  21. Karagoz, M.; Gulcu, B.; Cakmak, I.; Kaya, H.K.; Hazir, S. Predation of entomopathogenic nematodes by Sancassania sp. (Acari: Acaridae). Exp. Appl. Acarol. 2007, 43, 85–95. [Google Scholar] [CrossRef]
  22. Oliveira, A.R.; De Moraes, G.J.; Ferraz, L.C.C.B. Consumption rate of phytonematodes by Pergalumna sp. (Acari: Oribatida: Galumnidae) under laboratory conditions determined by a new method. Exp. Appl. Acarol. 2007, 41, 183–189. [Google Scholar] [CrossRef]
  23. Denno, R.F.; Gruner, D.S.; Kaplan, I. Potential for entomopathogenic nematodes in biological control: A meta-analytical synthesis and insights from trophic cascade theory. J. Nematol. 2008, 40, 61–72. [Google Scholar]
  24. Wilson, M.; Gaugler, R. Factors limiting short-term persistence of entomopathogenic nematodes. J. Appl. Entomol. 2004, 128, 250–253. [Google Scholar] [CrossRef]
  25. Duncan, L.W.; Graham, J.H.; Zellers, J.; Bright, D.; Dunn, D.C.; El-Borai, F.E.; Porazinska, D.L. Food web responses to augmenting the entomopathogenic nematodes in bare and animal manure-mulched soil. J. Nematol. 2007, 39, 176–189. [Google Scholar]
  26. Greenwood, C.M.; Barbercheck, M.E.; Brownie, C. Short term response of soil microinvertebrates to application of entomopathogenic nematode-infected insects in two tillage systems. Pedobiologia (JENA) 2011, 54, 177–186. [Google Scholar] [CrossRef]
  27. Nermuť, J.; Zemek, R.; Mráček, Z.; Palevsky, E.; Půža, V. Entomopathogenic nematodes as natural enemies for control of Rhizoglyphus robini (Acari: Acaridae)? Biol. Control 2019, 128, 102–110. [Google Scholar] [CrossRef]
  28. Devi, G. Entomopathogenic Nematodes: Impacts on Non-target Invertebrates. Curr. J. Appl. Sci. Technol. 2022, 41, 1–12. [Google Scholar] [CrossRef]
  29. Timper, P.; Kaya, H.K.; Jaffee, B.A. Survival of entomogenous nematodes in soil infested with the nematode-parasitic fungus Hirsutella rhossiliensis (Deuteromycotina: Hyphomycetes). Biol. Control 1991, 1, 42–50. [Google Scholar] [CrossRef]
  30. Jaffee, B.A.; Strong, D.R. Strong bottom-up and weak top-down effects in soil: Nematode-parasitized insects and nematode-trapping fungi. Soil Biol. Biochem. 2005, 37, 1011–1021. [Google Scholar] [CrossRef]
  31. Jaffee, B.A.; Bastow, J.L.; Strong, D.R. Suppression of nematodes in a coastal grassland soil. Biol. Fertil. Soils 2007, 44, 19–26. [Google Scholar] [CrossRef]
  32. Pathak, E.; Campos–Herrera, R.; El–Borai, F.E.; Duncan, L.W. Spatial relationships between entomopathogenic nematodes and nematophagous fungi in Florida citrus orchards. J. Invertebr. Pathol. 2017, 144, 37–46. [Google Scholar] [CrossRef] [Green Version]
  33. El-Borai, F.E.; Duncan, L.W.; Preston, J.F. Bionomics of a Phoretic Association between Paenibacillus sp. and the Entomopathogenic Nematode Steinernema diaprepesi. J. Nematol. 2005, 37, 18–25. [Google Scholar]
  34. Enright, M.E.; McInerney, J.O.; Griffin, C.T. Characterization of endospore-forming bacteria associated with entomopathogenic nematodes, Heterorhabditis spp., and description of Paenibacillus nematophilus sp. nov. Int. J. Syst. Evol. Microbiol. 2003, 53, 435–441. [Google Scholar] [CrossRef]
  35. Ishibashi, N.; Kondo, E. Dynamics of the Entomogenous Nematode Steinernema feltiae Applied to Soil with and without Nematicide Treatment. J. Nematol. 1987, 19, 404–412. [Google Scholar] [PubMed]
  36. Duncan, L.W.; Graham, J.H.; Dunn, D.C.; Zellers, J.; McCoy, C.W.; Nguyen, K. Incidence of endemic entomopathogenic nematodes following application of Steinernema riobrave for control of Diaprepes abbreviatus. J. Nematol. 2003, 35, 178–186. [Google Scholar] [PubMed]
  37. Campos-Herrera, R.; Půža, V.; Jaffuel, G.; Blanco-Pérez, R.; Čepulyte-Rakauskiene, R.; Turlings, T.C.J. Unraveling the intraguild competition between Oscheius spp. nematodes and entomopathogenic nematodes: Implications for their natural distribution in Swiss agricultural soils. J. Invertebr. Pathol. 2015, 132, 216–227. [Google Scholar] [CrossRef] [PubMed]
  38. Torr, P.; Spiridonov, S.E.; Heritage, S.; Wilson, M.J. Habitat associations of two entomopathogenic nematodes: A quantitative study using real-time quantitative polymerase chain reactions. J. Anim. Ecol. 2007, 76, 238–245. [Google Scholar] [CrossRef]
  39. Campos-Herrera, R.; El-Borai, F.E.; Stuart, R.J.; Graham, J.H.; Duncan, L.W. Entomopathogenic nematodes, phoretic Paenibacillus spp., and the use of real time quantitative PCR to explore soil food webs in Florida citrus groves. J. Invertebr. Pathol. 2011, 108, 30–39. [Google Scholar] [CrossRef]
  40. Dritsoulas, A.; El-Borai, F.E.; Shehata, I.E.; Hammam, M.M.; El-Ashry, R.M.; Mohamed, M.M.; Abd-Elgawad, M.M.; Duncan, L.W. Reclaimed desert habitats favor entomopathogenic nematode and microarthropod abundance compared to ancient farmlands in the Nile Basin. J. Nematol. 2021, 53, 1–13. [Google Scholar] [CrossRef]
  41. Duncan, L.W.; McCoy, C.W.; Terranova, A.C. Estimating sample size and persistence of entomogenous nematodes in sandy soils and their efficacy against the larvae of diaprepes abbreviatus in Florida. J. Nematol. 1996, 28, 56–67. [Google Scholar]
  42. Campos-Herrera, R.; Barbercheck, M.; Hoy, C.W.; Stock, S.P. Entomopathogenic nematodes as a model system for advancing the frontiers of ecology. J. Nematol. 2012, 44, 162–176. [Google Scholar]
  43. Somasekhar, N.; Grewal, P.S.; De Nardo, E.A.B.; Stinner, B.R. Non-target effects of entomopathogenic nematodes on the soil nematode community. J. Appl. Ecol. 2002, 39, 735–744. [Google Scholar] [CrossRef]
  44. Jenkins, W.R.B. A rapid centrifugal-flotation technique for separating nematodes from soil. Plant Dis. Report. 1964, 48, 692. [Google Scholar]
  45. Curran, J.; Driver, F.; Ballard, J.W.O.; Milner, R.J. Phylogeny of Metarhizium: Analysis of ribosomal DNA sequence data. Mycol. Res. 1994, 98, 547–552. [Google Scholar] [CrossRef]
  46. Leray, M.; Yang, J.Y.; Meyer, C.P.; Mills, S.C.; Agudelo, N.; Ranwez, V.; Boehm, J.T.; Machida, R.J. A new versatile primer set targeting a short fragment of the mitochondrial COI region for metabarcoding metazoan diversity: Application for characterizing coral reef fish gut contents. Front. Zool. 2013, 10, 34. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  47. Geller, J.; Meyer, C.; Parker, M.; Hawk, H. Redesign of PCR primers for mitochondrial cytochrome c oxidase subunit I for marine invertebrates and application in all-taxa biotic surveys. Mol. Ecol. Resour. 2013, 13, 851–861. [Google Scholar] [CrossRef] [PubMed]
  48. Callahan, B.J.; McMurdie, P.J.; Rosen, M.J.; Han, A.W.; Johnson, A.J.A.; Holmes, S.P. DADA2: High-resolution sample inference from Illumina amplicon data. Nat. Methods 2016, 13, 581–583. [Google Scholar] [CrossRef] [Green Version]
  49. Mendiburu, F.; Yaseen, M. Agricolae: Statistical Procedures for Agricultural Research. R package version 1.4.0. 2020. Available online: https://myaseen208.github.io/agricolae/https://cran.r-project.org/package=agricolae.
  50. Ter Braak, C.J.F. Biometris--quantitative methods in the life and earth sciences. Plant Res. Int. Wageningen Univ. Res. Centre, Box 2009, 100, 6700. [Google Scholar]
  51. Strong, D.R. Populations of entomopathogenic nematodes in foodwebs. Entomopathog. Nematol. 2002, 225–240. [Google Scholar] [CrossRef]
  52. Bik, H.M.; Fournier, D.; Sung, W.; Bergeron, R.D.; Thomas, W.K. Intra-Genomic Variation in the Ribosomal Repeats of Nematodes. PLoS ONE 2013, 8, e78230. [Google Scholar] [CrossRef]
  53. Lopes, E.A.; Roberts, D.M.; Blok, V.C. Variable ITS-copy number at different developmental stages of Meloidogyne hapla and M. chitwoodi. Eur. J. Plant Pathol. 2019, 154, 843–848. [Google Scholar] [CrossRef]
  54. Millar, L.C.; Barbercheck, M.E. Interaction between Endemic and Introduced Entomopathogenic Nematodes in Conventional-Till and No-Till Corn. Biol. Control 2001, 22, 235–245. [Google Scholar] [CrossRef]
  55. Kenney, E.; Eleftherianos, I. Entomopathogenic and plant pathogenic nematodes as opposing forces in agriculture. Int. J. Parasitol. 2016, 46, 13–19. [Google Scholar] [CrossRef] [Green Version]
  56. Grewal, P.S.; Lewis, E.E.; Gaugler, R. Response of Infective Stage Parasites (Nematoda: Steinernematidae) to Volatile Cues from Infected Hosts. J. Chem. Ecol. 1997, 23, 503–515. [Google Scholar] [CrossRef]
  57. Pérez, E.E.; Lewis, E.E. Use of entomopathogenic nematodes to suppress Meloidogyne incognita on greenhouse tomatoes. J. Nematol. 2002, 34, 171–174. [Google Scholar] [PubMed]
  58. Jagdale, G.B.; Holladay, T.; Brannen, P.M.; Cline, W.O.; Agudelo, P.; Nyczepir, A.P.; Noe, J.P. Incidence and pathogenicity of plant-parasitic nematodes associated with blueberry (Vaccinium spp.) replant disease in Georgia and North Carolina. J. Nematol. 2013, 45, 92–98. [Google Scholar] [PubMed]
  59. Kamali, S.; Javadmanesh, A.; Stelinski, L.L.; Kyndt, T.; Seifi, A.; Cheniany, M.; Zaki-Aghl, M.; Hosseini, M.; Heydarpour, M.; Asili, J.; et al. Beneficial worm allies warn plants of parasite attack below-ground and reduce above-ground herbivore preference and performance. Mol. Ecol. 2022, 31, 691–712. [Google Scholar] [CrossRef] [PubMed]
  60. Campos-herrera, R.; El-borai, F.E.; Duncan, L.W. Wide interguild relationships among entomopathogenic and free-living nematodes in soil as measured by real time qPCR. J. Invertebr. Pathol. 2012, 111, 126–135. [Google Scholar] [CrossRef] [Green Version]
  61. Blanco-Pérez, R.; Vicente-Díez, I.; Pou, A.; Pérez-Moreno, I.; Marco-Mancebón, V.S.; Campos-Herrera, R. Organic mulching modulated native populations of entomopathogenic nematode in vineyard soils differently depending on its potential to control outgrowth of their natural enemies. J. Invertebr. Pathol. 2022, 192, 107781. [Google Scholar] [CrossRef]
  62. Dillman, A.R.; Chaston, J.M.; Adams, B.J.; Ciche, T.A.; Goodrich-Blair, H.; Stock, S.P.; Sternberg, P.W. An entomopathogenic nematode by any other name. PLoS Pathog. 2012, 8, e1002527. [Google Scholar] [CrossRef]
  63. Epsky, N.D.; Walter, D.E.; Capinera, J.L. Potential Role of Nematophagous Microarthropods as Biotic Mortality Factors of Entomogenous Nematodes (Rhabditida: Steinernematidae, Heterorhabditidae). J. Econ. Entomol. 1988, 81, 821–825. [Google Scholar] [CrossRef]
  64. Joharchi, O.; Nazari, A.; Halliday, B.; Ostovan, H. Observations on predation of Rhizoglyphus robini (Acari: Acaridae) on the alfalfa stem nematode, Ditylenchus dipsaci (Nematoda). Persian J. Acarol. 2015, 4, 329–335. [Google Scholar] [CrossRef]
  65. Gilmore, S.K. Collembola predation on nematodes. Search Agric. Entomol. Limnol. 1970, 1, 1–12. [Google Scholar]
  66. Thimm, T.; Hoffmann, A.; Borkott, H.; Munch, J.C.; Tebbe, C.C. The gut of the soil microarthropod Folsomia candida (Collembola) is a frequently changeable but selective habitat and a vector for microorganisms. Appl. Environ. Microbiol. 1998, 64, 2660–2669. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  67. Walter, D.E.; Stirling, G.R. Microarthropods in Australian sugarcane soils: A survey with emphasis on the mesostigmata as potential regulators of nematode populations. Acarologia 2018, 58, 673–682. [Google Scholar] [CrossRef]
  68. Pilliod, D.S.; Goldberg, C.S.; Arkle, R.S.; Waits, L.P. Factors influencing detection of eDNA from a stream-dwelling amphibian. Mol. Ecol. Resour. 2014, 14, 109–116. [Google Scholar] [CrossRef] [PubMed]
  69. Sasso, T.; Lopes, C.M.; Valentini, A.; Dejean, T.; Zamudio, K.R.; Haddad, C.F.B.; Martins, M. Environmental DNA characterization of amphibian communities in the Brazilian Atlantic forest: Potential application for conservation of a rich and threatened fauna. Biol. Conserv. 2017, 215, 225–232. [Google Scholar] [CrossRef] [Green Version]
  70. Zhou, J.; Xia, B.; Treves, D.S.; Wu, L.Y.; Marsh, T.L.; O’Neill, R.V.; Palumbo, A.V.; Tiedje, J.M. Spatial and resource factors influencing high microbial diversity in soil. Appl. Environ. Microbiol. 2002, 68, 326–334. [Google Scholar] [CrossRef] [Green Version]
  71. Jaffuel, G.; Krishnamani, S.; Machado, R.A.R.; Campos-Herrera, R.; Turlings, T.C.J. Potent Ant Deterrents Emitted from Nematode-Infected Insect Cadavers. J. Chem. Ecol. 2022, 48, 71–78. [Google Scholar] [CrossRef]
  72. Poole, M.A. Survey and Control Efficacy of Endoparasites of Solenopsis Richteri Forel and Solenopsis Invicta Buren in Mississippi; Mississippi State University: Starkville, MA, USA, 1976. [Google Scholar]
  73. Jouvenaz, D.P.; Lofgren, C.S.; Miller, R.W. Steinernematid Nematode Drenches for Control of Fire Ants, Solenopsis invicta, in Florida. Florida Entomol. 1990, 73, 190–193. [Google Scholar] [CrossRef]
  74. Morris, J.R.; Stewart, K.W.; Hassage, R.L. Use of the Nematode Steinernema carpocapsae for Control of the Red Imported Fire Ant (Hymenoptera: Formicidae). Florida Entomol. 1990, 73, 675–677. [Google Scholar] [CrossRef]
  75. Helder, J.; Heuer, H. Let’s be inclusive - the time of looking at individual plant parasitic nematodes is over, and new technologies allow for it. In Integrated Nematode Management: State-of-the-Art and Visions for the Future; CABI: Wallingford, UK, 2022; pp. 403–407. [Google Scholar]
  76. Walter, D.E.; Proctor, H.C. Mites: Ecology, Evolution, and Behaviour; CABI: Wallingford, UK, 1999. [Google Scholar]
  77. Skoracka, A.; Magalhães, S.; Rector, B.G.; Kuczyński, L. Cryptic speciation in the Acari: A function of species lifestyles or our ability to separate species? Exp. Appl. Acarol. 2015, 67, 165–182. [Google Scholar] [CrossRef]
Figure 1. Results of DNA metabarcoding of nematode communities. Upper panel: Stacked bar plots showing the relative abundance of nematode species (listed lower right) detected in a citrus orchard for 28 days following augmentation with Steinernema feltiae (Sf), Heterorhabditis bacteriophora (Hb) and an untreated control (Ctrl). Asterisks (*) indicate significant differences (p < 0.05) between the treatments. Lower left: Two bar plots of the nematode read abundance in each treatment: upper bar plot is of total nematode reads (augmented plus native species) and lower bar plot depicts reads of native species only. Lower center: Temporal trends in nematode read abundance in the treatments for 28 days following augmentation. Error bars are standard errors of the mean, bars with the same letters do not differ (p < 0.05).
Figure 1. Results of DNA metabarcoding of nematode communities. Upper panel: Stacked bar plots showing the relative abundance of nematode species (listed lower right) detected in a citrus orchard for 28 days following augmentation with Steinernema feltiae (Sf), Heterorhabditis bacteriophora (Hb) and an untreated control (Ctrl). Asterisks (*) indicate significant differences (p < 0.05) between the treatments. Lower left: Two bar plots of the nematode read abundance in each treatment: upper bar plot is of total nematode reads (augmented plus native species) and lower bar plot depicts reads of native species only. Lower center: Temporal trends in nematode read abundance in the treatments for 28 days following augmentation. Error bars are standard errors of the mean, bars with the same letters do not differ (p < 0.05).
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Figure 2. Read abundance of four indigenous nematode species in a citrus orchard for 28 days following augmentation of Steinernema feltiae (Sf), Heterorhabditis bacteriophora (Hb) or no augmentation (Ctrl). Error bars are SE of the means.
Figure 2. Read abundance of four indigenous nematode species in a citrus orchard for 28 days following augmentation of Steinernema feltiae (Sf), Heterorhabditis bacteriophora (Hb) or no augmentation (Ctrl). Error bars are SE of the means.
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Figure 3. Results of DNA metabarcoding of soil microarthropod communities. Upper panel: Stacked bar plots showing the relative abundance of microarthropod families (listed lower right) detected in a citrus orchard for 28 days following augmentation with Steinernema feltiae (Sf), Heterorhabditis bacteriophora (Hb) and an untreated control (Ctrl). Lower left: Bar plot of two dominant groups acari mites and springtails read abundance in each treatment. Lower center: Temporal trends in acari mites and springtails read abundance in the treatments for 28 days following augmentation. Error bars are standard errors of the mean, bars with the same letters do not differ (p < 0.05).
Figure 3. Results of DNA metabarcoding of soil microarthropod communities. Upper panel: Stacked bar plots showing the relative abundance of microarthropod families (listed lower right) detected in a citrus orchard for 28 days following augmentation with Steinernema feltiae (Sf), Heterorhabditis bacteriophora (Hb) and an untreated control (Ctrl). Lower left: Bar plot of two dominant groups acari mites and springtails read abundance in each treatment. Lower center: Temporal trends in acari mites and springtails read abundance in the treatments for 28 days following augmentation. Error bars are standard errors of the mean, bars with the same letters do not differ (p < 0.05).
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Figure 4. Pie chart of proportional composition of major microarthropod groups recovered from high-throughput sequencing of DNA recovered from soil in a citrus orchard for 28 days following augmentation of two EPN species or no augmentation.
Figure 4. Pie chart of proportional composition of major microarthropod groups recovered from high-throughput sequencing of DNA recovered from soil in a citrus orchard for 28 days following augmentation of two EPN species or no augmentation.
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Figure 5. Eight microarthropod family responses to augmentation with Steinernema feltiae (Sf), Heterorhabditis bacteriophora (Hb) and an untreated control (Ctrl). Plots in the left column exhibit potential predator epidemiology. Plots in the right column depict potential prey of entomopathogenic nematode species.
Figure 5. Eight microarthropod family responses to augmentation with Steinernema feltiae (Sf), Heterorhabditis bacteriophora (Hb) and an untreated control (Ctrl). Plots in the left column exhibit potential predator epidemiology. Plots in the right column depict potential prey of entomopathogenic nematode species.
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Figure 6. Results of DNA metabarcoding of insect communities. Upper panel: Stacked bar plots showing the relative abundance of insect families (listed lower right) detected in a citrus orchard for 28 days following augmentation with Steinernema feltiae (Sf), Heterorhabditis bacteriophora (Hb) and an untreated control (Ctrl). Lower left: Bar plot of the insect read abundance in each treatment. Lower center: Temporal trends in insect read abundance in the treatments for 28 days following augmentation. Error bars are standard errors of the mean and bars with the same letters do not differ (p < 0.05).
Figure 6. Results of DNA metabarcoding of insect communities. Upper panel: Stacked bar plots showing the relative abundance of insect families (listed lower right) detected in a citrus orchard for 28 days following augmentation with Steinernema feltiae (Sf), Heterorhabditis bacteriophora (Hb) and an untreated control (Ctrl). Lower left: Bar plot of the insect read abundance in each treatment. Lower center: Temporal trends in insect read abundance in the treatments for 28 days following augmentation. Error bars are standard errors of the mean and bars with the same letters do not differ (p < 0.05).
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Table 1. Abundance of Steinernema feltiae (Sf) and Heterorhabditis bacteriophora (Hb) for 28 days following augmentation in a citrus orchard.
Table 1. Abundance of Steinernema feltiae (Sf) and Heterorhabditis bacteriophora (Hb) for 28 days following augmentation in a citrus orchard.
Hb Sf
Sampling DayMeanSEMeanSE
3rd7135.822500.191,180.129,235.3
7th6085.631373.176,452.631,251.9
14th2244.3561681,742.249,325.8
28th3285.41373.557,997.726,907.1
Table 2. Motu richness (R) of major taxa in the plots augmented with Heterorhabditis bacteriophora (Hb), Steinernema feltiae (Sf) and the untreated controls (Ctrl). Means in rows with the same letters do not differ (p < 0.05).
Table 2. Motu richness (R) of major taxa in the plots augmented with Heterorhabditis bacteriophora (Hb), Steinernema feltiae (Sf) and the untreated controls (Ctrl). Means in rows with the same letters do not differ (p < 0.05).
Ctrl Hb Sf
GroupMeanStd Error MeanStd Error MeanStd Error
Microarthropods65.191.81ab65.531.98a59.631.88b
Mites53.881.74ab55.341.84a49.441.58b
Collembola5.750.25a5.440.22a5.310.24 a
Insects32.591.07a30.441.20ab26.780.87b
Nematodes8.940.20a8.530.27ab7.940.22b
Table 3. Significant responses of MOTUs in the four major groups (microarthropods, insects and nematodes) according to two-way repeated measures ANOVA. R squared values show proportion of variance that can be explained by the independent variable. Means comparison performed using Least Significant Difference (LSD-test) with p-values adjusted by the Bonferroni correction approach. Treatments with the same letter following mean read abundance of the untreated control (Ctrl), Heterorhabditis bacteriophora (Hb) and Steinernema feltiae (Sf) do not differ (p < 0.05). Abundance indicates the total read abundance of the family. Analysis was applied only to taxa occurring in more than 75% of the 24 treated plots (Plot freq), while “Total freq” indicates the frequency of occurrence in the 96 samples.
Table 3. Significant responses of MOTUs in the four major groups (microarthropods, insects and nematodes) according to two-way repeated measures ANOVA. R squared values show proportion of variance that can be explained by the independent variable. Means comparison performed using Least Significant Difference (LSD-test) with p-values adjusted by the Bonferroni correction approach. Treatments with the same letter following mean read abundance of the untreated control (Ctrl), Heterorhabditis bacteriophora (Hb) and Steinernema feltiae (Sf) do not differ (p < 0.05). Abundance indicates the total read abundance of the family. Analysis was applied only to taxa occurring in more than 75% of the 24 treated plots (Plot freq), while “Total freq” indicates the frequency of occurrence in the 96 samples.
AccessionR2/R2(adj) TreatmentSampling DayInteractionCtrlHbSfDescriptionFamilyAbundanceFreq in TreesTotal Freq
Microarthropods
JX836034.10.396/0.3160.0110.6880.740348.30b910.85a89.35bOppiidae sp. MYMCC093-11 voucher BIOUG01067-93 Oppiidae43,1520.750.43
MG316849.10.368/0.2840.0290.3860.131227.54a105.87ab50.25bEupodidae sp. BIOUG25723-A11 Eupodidae12,2770.960.68
MG320390.10.472/0.4030.0340.0080.640783.33ab933.56a597.27bTydeidae sp. BIOUG25166-E03Tydeidae74,0531.000.89
MN349530.10.282/0.1880.0340.1500.292525.53a721.48a304.87bEupodidae sp. BIOUG23551-E05 Eupodidae49,6601.000.96
MG321080.10.323/2340.0460.0950.82134.77a20.82ab12.66bEupodidae sp. BIOUG25167-C10 Eupodidae21840.750.36
MG317718.10.475/0.4070.0220.5550.08374.90ab98.40a10.90bTydeidae sp. BIOUG26106-F03 Tydeidae68510.710.33
Insects
GQ255183.10.472/0.4030.0170.5760.2446417.96a4665.52ab1819.52bMyrmica semiparasitica voucher GJ533 Formicidae82,66510.96
HM906951.10.393/0.3140.0210.1270.715908.27b2067.97a871.40abStamnodes affiliata voucher BIOUG<CAN>:CCGBOLD00082 Geometridae26,98810.98
Nematodes
NA0.360/0.2760.0030.6010.973410.9a262.4a140.5bAcrobeles complexusCephalobidae26,0391.000.94
NA0.648/0.6010.0650.5640.0381862.0a1672.2ab482.9bAcrobeloides saeediCephalobidae128,546.021.000.99
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Dritsoulas, A.; Wu, S.-Y.; Regmi, H.; Duncan, L.W. Arthropod Community Responses Reveal Potential Predators and Prey of Entomopathogenic Nematodes in a Citrus Orchard. Agronomy 2022, 12, 2502. https://doi.org/10.3390/agronomy12102502

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Dritsoulas A, Wu S-Y, Regmi H, Duncan LW. Arthropod Community Responses Reveal Potential Predators and Prey of Entomopathogenic Nematodes in a Citrus Orchard. Agronomy. 2022; 12(10):2502. https://doi.org/10.3390/agronomy12102502

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Dritsoulas, Alexandros, Sheng-Yen Wu, Homan Regmi, and Larry W. Duncan. 2022. "Arthropod Community Responses Reveal Potential Predators and Prey of Entomopathogenic Nematodes in a Citrus Orchard" Agronomy 12, no. 10: 2502. https://doi.org/10.3390/agronomy12102502

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