FIGURE 3 | (A) Plant and orthopteran species co-occurrence network in the permanent mesic grasslands of the French Jura Mountains. Points (edges) correspond to species and lines (vertex) to significant positive co-occurrence between two species. Point size is proportional to species degree (i.e., the total number of significant positive co-occurrences with the species). Colors show species membership to the five modules revealed by the modularity analysis. Abbreviation corresponds to the three first letters of the genus and species names following Supplementary Table S1 (online Supplementary Material). (B) Species importance for the modular structure of the network. Values on the y-axis are standardized effect sizes. Negative values indicate species with negative impact on modularity (i.e., the network becomes more modular when the species is removed) and positive values indicate species with positive impact. (C) Zoom on the five species with the highest negative and positive impact on modularity, respectively. Colors show species module membership.

Chorthippus parallelus and Chorthippus biguttulus. Poa trivialis, Trifolium repens and Taraxacum officinale were the dominant plant species.

After trimming species lacking positive co-occurrences, 82 plant and 9 orthopteran species remained. These represented 42 and 41% of the total number of plant and orthopteran species, respectively. The resulting network had a relatively high modularity (0.36), but a low nestedness value (0.29) (**Figure 3A**). Our permutation analyses revealed a significantly higher modularity than expected by chance (SES = 18.8; P < 0.001) with five groups of co-occurring species. To the contrary, the observed nestedness was significantly lower than expected by chance (SES = −5.2; P = 0.01). The most connected plant species (i.e., species having numerous significant positive co-occurrences with other species) were Tragopogon orientalis, Leucanthemum vulgare, Festuca rubra and Anthoxanthum odoratum in module 1, Lathyrus pratensis, Vicia cracca and Alchemilla monticola in module 2, Prunella vulgaris and Cynosurus cristatus in module 3. Orthopterans were present in module 1 (Chorthippus biguttulus, Mecostethus parapleurus, Stenobothrus lineatus and Stethophyma grossum) and 2 (Chrysochraon dispar, Euthystira brachyptera, Metrioptera roeselii and Omocestus viridulus) and in module 4 with Chorthippus albomarginatus. Species with the strongest positive influence on modularity were found in modules 2 and 3 (e.g., Metrioptera roeseli) while those with the strongest negative influence on modularity belonged to module 1 (**Figures 3B,C**).

Null-model tests on co-occurrence data revealed a significantly higher phylogenetic and functional distance among plants than expected by chance in modules 3 and 5, respectively (**Table 2A**). By contrast, the same analysis revealed a significantly lower functional distance than expected by chance in module 4 for multiple trait, SLA and LDMC (**Tables 2A,B**). Plant species in this module had a higher average SLA with a lower variance than any other modules (**Figure 4A**). Similarly, the three species in module 5 were phylogenetically less related than expected by chance. Null-model tests on abundance data without considering network structure revealed a lower functional distance among species than expected by chance for multiple traits, LDMC and seed mass (**Table 3A**). For orthopterans, null-model tests on co-occurrence data were limited to modules 1 and 2 where several species were present and revealed no significant pattern in functional or phylogenetic data (**Tables 2A,C**). The same was true for abundance data (**Table 3B**). This agrees with the lack of significant changes of functional traits among modules except for a marginally significant change in egg deposition strategy (**Figure 4B**). Nevertheless, orthopterans in module 1 tended to be generalists with broad environmental range and good dispersal capacity. In module 2, species were preferentially habitat specialists with intermediate dispersal capacity and

TABLE 2 | Null model analysis of plant and orthopteran functional and phylogenetic distances in the five species groups (Modules 1–5) revealed by the modularity analysis.

(A) Functional distances based on multiple traits. (B) Null-model analysis of plant functional distances based on individual traits. (C) Null-model analysis of orthopteran functional distance based on individual traits. SES, standardized effect size; P = P-values after 9,999 permutations of the distance matrices. Significant negative or positive SES are in boldface.

#### TABLE 3 | Abundance-based null model analysis of plant and orthopteran functional and phylogenetic distances for the whole dataset.

(A) Plants. (B) Orthopterans. SES, standardized effect size; P = P-values after 9,999 permutations of the distance matrices. Significant negative or positive SES are in boldface.

changed their diet during life cycle and preferentially lay eggs in plants. This group was composed by species characteristic of mountain grasslands such as Metrioptera roeseli. Finally, Chorthippus albomarginatus, the only orthopteran in its module, is a habitat specialist with a low dispersal capacity.

Variance partitioning of plant and orthopteran abundance data revealed that spatial variables were good predictors of species distribution in all five modules as well as for the entire dataset (**Figure 5**). Agricultural practices were significant predictors of species abundance in modules 2, 4, and 5 as well as for the entire dataset. Soil variables were not significant predictors of species abundance within modules but showed a weak yet significant correlation to abundance data for the entire dataset.

### DISCUSSION

### Structure and Drivers of the Plant-Orthopteran Co-occurrence Network

The organization of the plant-orthopteran co-occurrence network in the grasslands of the Jura Mountains was strongly modular. Other examples of modular co-occurrence networks were found among soil microbes (Barberan et al., 2012; Banerjee et al., 2015). However, such organization was not encountered in plants and arbuscular mycorrhizal fungi (AMF) co-occurrence networks (Encinas-Viso et al., 2016). Contrary to this plant-AMF network where random encounters appear to drive species assembly, our results show that the interaction of multiple assembly rules can explain the modular organization of the plant-orthopteran co-occurrence network. For instance, environmental filtering, limiting similarity and neutral processes alternatively explain plant species coexistence within the different modules. To the contrary, within-guild interactions cannot explain the distribution of orthopteran species among modules. It follows that the distribution of orthopterans into modules most likely reflected that of plants as a result of biotic interactions (herbivory, refuges, reproduction sites). This modular structure is likely to shape the response of plant and orthopteran community assembly to future changes, for example,

the whole network. Stars and bold typeface indicate significance ∗∗∗P < 0.001; ∗∗P < 0.01; ∗P < 0.05).

(

by limiting the negative impact of land-use changes to individual modules leaving other modules un-impacted. Moreover, a limited number of plant or orthopteran species had a disproportionate positive or negative importance for the modular structure of the network. Species with positive importance for the modular structure were generally less connected to other species than species with negative importance. These species are likely to have particular importance for the structure and functioning of grassland ecosystems (Olesen et al., 2007). Our analyses further revealed a complexity in the processes underlying species co-occurrences. For instance, within-guild processes appear to dominate the co-occurrence of plant species while that of orthopterans is best explained by bottom–up processes (i.e., interactions with plants). Below we provide more detailed explanations about how our results support this conclusion for plants and orthopterans, respectively.

In plants, functional trait analyses revealed that different assembly rules operate in the different modules. In module 4, where the functional distances among species were lower than expected by chance, all species had high SLA and low LDMC. This module was composed by seven plant species including Rumex obtusifolius and Aethusa cynapium. Species in this module are ruderal species able of rapid resource acquisition and are characteristics of grasslands where grazing intensity is high (Cruz et al., 2010). It is likely that species coexistence within this module results from the interplay of the environmental filtering effect of grazing and the competitive exclusion of species unable of rapid resource acquisition. This agrees with Tilman's Resource Ratio Hypothesis (Tilman, 1982; Miller et al., 2005) where resource acquisition rate determines species coexistence. Species in module 2 were phylogenetically more similar than expected by chance. This result suggests that environmental or biotic filtering forces species to share similar eco-evolutionary features. However, these features were not related to the four investigated traits. To the contrary, plant species co-occurrences were best explained by the limiting similarity process in module 3 where species were functionally less similar than expected by chance. In module 5, the lower phylogenetic relatedness than expected by chance can also be explained by the limiting similarity process. However, this process was not related to the selected functional traits. Species in module 1 show neither significant functional or phylogenetic convergence or divergence nor clear changes in mean functional traits. Such a pattern could result from neutral processes where ecological drift and historical (Fukami, 2015) and spatial contingencies are the main drivers of species assembly. For instance, Lau et al. (2015) showed that phylogenetic founder effect can determine the structure of interaction networks.

In orthopterans, the lack of significant convergence of functional and/or phylogenetic distance among species and the relative low importance of environmental variables suggests that species assembly is not the result of strong environmental filters or competitive interactions. However, changes in functional traits and more specifically in egg deposition strategy suggest that the distribution of orthopteran species into modules results from trophic and other vertical interactions with plants. For instance, species in module 2 tended to lay eggs more frequently in plants as opposed to soil. These species were preferentially encountered in higher elevation grasslands where the microclimate provided by plants could protect eggs from the more constraining environmental conditions (e.g., late freeze). Other types of interactions with plants could also explain the distribution of orthopterans into modules. For instance, plants provide orthopterans with food resources, reproduction and habitat sites and refuge against predators (Pellissier et al., 2011; Ibanez et al., 2013). More generally, co-evolution between plants and orthopterans constitutes another likely explanation for the distribution of orthopterans into modules. For example, it has been shown that the diversification of frugivorous vertebrates

was associated with plant fleshy fruit production (Fleming et al., 1987).

### Species Importance for Network Structure

Our analyses further highlighted plant and orthopteran species with particular importance for the structure of the co-occurrence network. Species such as Metrioptera roeseli and Anthriscus sylvestris had a positive influence on modularity. In other words, the network would become less modular if these species go extinct. These species were found in modules 3 and 4. Species co-occurrence in these two modules was determined by different assembly rules (limiting similarity and filtering, respectively) suggesting that assembly rules are not strong determinant of species role for network structure. However, a common feature of these species is that they share few links with species from other modules. Following the terminology of Olesen et al. (2007) for bipartite interaction networks, these species could be referred to as module hub. Management plans specifically targeting these species are likely to maximize the modularity of the whole system and thereby its capacity to retain the negative impact of perturbations within one or few modules. By contrast, species such as Leucanthemum vulgare and Festuca rubra had a negative influence on network structure (i.e., the network would become more modular without these species). All of these species belong to module 1. They also tended to have more links than species with positive influence on modularity and were frequently linked to species from different modules. Theoretical studies have shown species interaction networks to be robust to the extinction of poorly connected species but to be sensitive to the loss of highly connected species (Sole and Montoya, 2001; Dunne et al., 2002b). As a result, the extinction of these highly connected species is likely to induce cascading effect within the network.

#### Differences with Abundance Data

The rules underlying species assembly differed between cooccurrence and abundance data. Null model analyses suggest that plant abundance was strongly determined by seed mass and LDMC. Species with lower seed mass and LDMC such as Poa trivialis reached higher abundances. This result likely reflects a strong competition for space where species producing large propagule numbers and capable of rapid colonization and resource exploitation are dominant. To the contrary, phylogenetic or functional patterns could not explain the abundance of orthopteran species. Here, the two dominant species shared lower elevation sites with Chorthippus albomarginatus dominating in predominantly grazed grasslands and Chorthippus biguttulus dominating in predominantly mowed grasslands. In higher elevation sites, Metrioptera roeselii became dominant most likely because of better adaptations to the more constraining abiotic conditions such as a change of feeding regime during its development or its preference for laying eggs in the vegetation. Finally, RDAs showed that the overall abundance of plants and orthopterans was significantly impacted by agricultural practices and spatial variables. This agrees with previous results obtained for plants in the same system (Mauchamp et al., 2014). Interestingly, the impact of agricultural practices was only significant in modules 2, 4, and 5. It is therefore likely that species in these modules will retain most of the impact of changes in agricultural practices such as intensification leaving other species not or poorly impacted (Krause et al., 2003; Teng and McCann, 2004).

## CONCLUSION

The combination of co-occurrence network analysis, functional and phylogenetic analyses and multivariate analyses of abundance data constitutes a powerful tool to understand the drivers of species assembly. We highlighted a complexity of processes related to the modular structure of the plantorthopteran co-occurrence network that differs from those explaining species abundance. We also showed that the modular structure of the network is likely to determine how changes in agricultural practices will influence plant and orthopteran communities. The next step is to understand the importance of this modular structure for the long-term maintenance of grassland ecosystem structure and functions as well as to develop tools to integrate network structure into models to improve their capacity to predict future changes.

### AUTHOR CONTRIBUTIONS

FG gathered species data. BF gathered functional and phylogenetic data. AM conducted phylogenetic analyses. BF and FG conducted the numerical analyses of the data. All authors contributed to writing.

### FUNDING

This research takes place in the Long Term Ecological Research (LTER) site Jurassian Arc (http://zaaj.univ-fcomte.fr/?lang=en), which supports long-term interdisciplinary research on the dynamics of mountain socio-ecological systems in the Jura Mountains. It benefited from a post-doctoral fellowship (BF) funded by the Conseil Régional de Franche-Comté. The Comité Interprofessionnel de Gestion du Comté (CIGC) provided financial support to data collection.

### ACKNOWLEDGMENTS

We thank Leslie Mauchamp for data collection, the farmers who participated in this project and François Dehondt and Frédéric Mora (Conservatoire Botanique National de Franche-Comté – Observatoire Régional des Invertébrés) for their help in orthopteran species identification.

### SUPPLEMENTARY MATERIAL

The Supplementary Material for this article can be found online at: http://journal.frontiersin.org/article/10.3389/fpls.2016.01224

#### REFERENCES

fpls-07-01224 August 12, 2016 Time: 15:24 # 11

**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2016 Fournier, Mouly and Gillet. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# Impact of Grassland Reseeding, Herbicide Spraying and Ploughing on Diversity and Abundance of Soil Arthropods

Wei Liu1,2,3, Junling Zhang3 , Stuart L. Norris2 and Philip J. Murray2 \*

1 Collaborative Innovation Center of Jiangxi Typical Trees Cultivation and Utilization, Jiangxi Agricultural University, Nanchang, China, 2 Sustainable Soil and Grassland Systems, Rothamsted Research, Okehampton, UK, 3 College of Resources and Environmental Sciences, China Agricultural University, Beijing, China

In order to determine the interactive effect of reseeding, herbicide spraying and ploughing on soil fauna communities, we conducted a grassland reseeding experiment combined with pre-reseed management to examine how with the whole reseeding process affects soil faunal composition. Sampling occasions and exact treatments were as follows: (1) before chemical herbicide spray; (2) after spray but before ploughing; (3) after ploughing but before reseeding; and (4) after 1 year of recovery. Our results demonstrate that, Acari and Collembola were the two soil fauna taxa with the highest abundance and accounted for around 96% of the relative total abundance among the various managements. Herbicide application tended to increase soil invertebrate abundance. Conversely, subsequent ploughing significantly reduced soil invertebrate abundance and had an obvious negative effect on soil primary and secondary decomposers, which were mainly due to the variations of Acari (especially Oribatida) and Coleoptera group abundance. Moreover, reseeding also reduced the individual number of the groups mentioned above, and favored those predators with a larger body size and individual weight. After 1 year recovery, Collembola abundance recovered to the pre-treatment levels, while with Arthropod and Acari groups were still fluctuating.

#### Edited by:

Ivan Hiltpold, Western Sydney University, Australia

#### Reviewed by:

Karl Kunert, University of Pretoria, South Africa Stephen Goldson, AgResearch, New Zealand

\*Correspondence: Philip J. Murray<EMAIL_ADDRESS>
#### Specialty section:

This article was submitted to Agroecology and Land Use Systems, a section of the journal Frontiers in Plant Science

> Received: 31 May 2016 Accepted: 27 July 2016 Published: 09 August 2016

#### Citation:

Liu W, Zhang J, Norris SL and Murray PJ (2016) Impact of Grassland Reseeding, Herbicide Spraying and Ploughing on Diversity and Abundance of Soil Arthropods. Front. Plant Sci. 7:1200. doi: 10.3389/fpls.2016.01200 Keywords: soil fauna community, herbicide, ploughing, reseeding, arthropods

## INTRODUCTION

The soil fauna account for a large part of the global biodiversity (Kremen et al., 1993) and play key roles in many ecosystems (García et al., 2010; Carrillo et al., 2011; Basset et al., 2012) because they directly or indirectly influence soil function (Diekötter et al., 2010). For example, approximately 90% of aboveground primary production, in terrestrial ecosystems, enters the belowground system (Gessner et al., 2010) where the soil biota undertake the decomposition and mineralization of soil organic matter (Bernard et al., 2012).

The perennial nature of grasslands means that interactions between the plant and the soil are crucial in regulating soil processes (Murray et al., 2012). The perenniality of grassland ecosystems implies that they generally have a relatively stable and permanent plant cover which provides a secure habitat for abundant and diverse soil invertebrate fauna that contribute to effective soil functioning. Alongside this, grasslands tend to have a high turnover of root and shoot material

than in other ecosystems and this, together with animal inputs, results in a relatively high level of organic matter content. This in turn allows grassland to support numerous and diverse biota, important for soil function (Murray et al., 2012). Soil fauna within grazed grassland break down both the labile and recalcitrant plant compounds releasing the nutrients bound up within them, so that they can be exploited by the plant (Wardle, 1999) and the biogeochemical cycling continues (Wall et al., 2010).

Although grasslands generally provide a stable soil environment, agricultural grassland management practices such as reseeding can affect sward structure and plant species composition (Celaya et al., 2007; García et al., 2010) and, probably more importantly, the soil structure and habitat. Therefore, such interventions in these systems can have a knock-on effect on the associated soil fauna (Gibson et al., 1992; Dennis et al., 1998, 2001, 2008). The soil fauna has been shown to be sensitive to changes in soil conditions (Vasconcellos et al., 2013) and soil management practices can also have an effect on the energy channels (bacterial feeding channel and fungal feeding channel) and soil food webs (Doblas-Miranda et al., 2008; Maharning et al., 2009; Strickland and Rousk, 2010). For example, in cropping systems, conventional tillage is thought to promote the bacterial energy channel in the soil food web by the redistribution of plant residues within the soil during ploughing; in comparison, no tillage systems are thought to promote the fungal energy channel and the immobilization of plant nutrients (Hendrix et al., 1986). Types of tillage also had conflicting effects on soil arthropods, for example, Petersen (2002) showed that conventional ploughing reduced the collembolan population more than the non-inverting tillage does in upper soil stratum, while the two tillage treatments resulted in similar population changes for most collembolan species when take the whole soil horizon into considered. Studies involving herbicide application also had distinct effects. Lins et al. (2007) studied the effects of different herbicides on Collembola, and found that the use of atrazine and 2,4-D significantly decreased Collembola diversity but it depended on the handling time in a no-till soil preparation system. Nevertheless, Greenslade et al. (2010) found that herbicides have no significant effect on surface-active arthropods although Collembola were more affected than Formicidae in the short term. Some soil faunal groups (e.g., spiders, harvestmen) and some ground beetles are known to react strongly to such changes in microhabitat conditions and are subsequently often used as indicators of the effects of management practices (Hillyard and Sankey, 1989; Bell et al., 2001; Rainio and Niemelä, 2003). However, knowledge of such interactions occurring between the faunal community is limited, because the factors responsible for this high diversity of soil animals on small spatial scales are still not fully understood (Maraun et al., 2011). This applies especially to the high α-diversity, which implies the existence of a large number of niches in a very small area (Maraun et al., 2007), possibly because below-ground animal taxa are generalists that inhabit wide niches. In this study we determine the impact of perturbation (herbicide, ploughing), during grassland reseeding on the soil fauna and its subsequent recovery.

### MATERIALS AND METHODS

### Study Site Description and Experimental Design

The study site was located at the North Wyke Farm Platform (NWFP) in the South West of England (50◦ 460 5500N, 3◦ 550 1 00W) and is fully described in Orr et al. (2016). The vegetation is permanent grassland dominated by perennial ryegrass (Lolium perenne L.) and creeping bent (Agrostis stolonifera L.); the soil is classified as clayey pelo-stagnogley developed from located mainly under gentle low lying slopes (Hallsworth series, Harrod and Hogan, 2008). The main properties of the soil were organic carbon 3.7%, nitrogen 0.5% and phosphorus 0.1%, with a clay content of 38%, bulk density of 0.99 g cm−3 and a pH of 5.3 (Harrod and Hogan, 2008). Average annual rainfall at the site is 1085 mm (± 8.5), average air temperature is 9.8◦C (± 0.65); yearly total sunlight is 1419 h (± 38) and average soil temperature is 10.9◦C (± 0.77; Crotty et al., 2012).

The main aim of this study was to determine the impact of perturbation, during grassland management (reseeding, herbicide, ploughing) on the soil faunal composition. Four field permanent grasslands were chosen (**Figure 1**) were due to be reseeded. Prior to reseeding all the fields were under the same management regime, receiving 200 kg N per annum. In June 2013 the were sprayed with glyphosate (Glyphosate 360, Dow Agrosciences, Hitchin, UK), 6 weeks later the fields were ploughed and a seedbed prepared with subsequent reseeding in August 2013.

### Soil Sampling

Soil samples were collected four times during the study: (1) before chemical herbicide spraying (designated S1, 26th June), (2) after spraying but before ploughing (designated S2, 3th July), (3) after ploughing but before reseeding (designated S3, 24th July), and (4) after 1 year of recovery (designated S4, 26th August, 2014). Intact soil cores (8 cm diameter, 10 cm deep; weighing on average 1.2 ± 0.02 kg, wet weight) were taken from the four fields. Overlaying the NWFP is a GPS defined 50 m grid and on each sampling occasion, six grid locations were randomly selected and a single soil core was collected at each point. Each individual core was stored within an individual Sun bag (Sigma-Aldrich, St. Louis, MO, USA). Post-extraction the invertebrates from each field were amalgamated to provide a single sample for each field for each sampling occasion. The soil characteristics for each field are given in **Table 1**.

### Invertebrate Extraction and Separation

The cores were placed on a Tullgren funnel system (Burkard Manufacturing, Co., Ltd, Rickmansworth, UK; mesh 5 mm) and were collected in a saturated salt solution. The cores were held in the funnels for 14 days; invertebrate collections were sorted, identified and counted under a microscope (Crotty et al., 2014). These were as follows the four main Collembola orders comprised Entomobryomorpha, Poduromorpha, Neelipleona and Symphypleona, the four main Orders of soil dwelling Acari comprising Astigmata, Mesostigmata, Oribatida and

Data are mean values ± SE (n = 6). Significant differences among grassland managements within each variable were tested using Duncan's multiple range test (P < 0.05) and are indicated by different letters.

Prostigmata, where possible, these were further identified to a higher taxonomic level (Supplementary Table S1). All other invertebrates collected were identified to Order level, apart from the Coleoptera where the majority were identified to Family level – (i.e., Carabidae, Chrysomelidae, Cuculionidae, Elateridae, Ptilidae, and Staphylinidae. Diptera were sorted to Order level apart from Tipulidae larvae which were analysed separately.

Trophic level and Acari/Collembola grouping were determined according to Crotty et al. (2014). Trophic 0 (T0) represents herbivores. Trophic 1 (T1) represents primary decomposers. Trophic 2 (T2) represents secondary decomposers. Trophic 3 (T3) represents micro-predator. Trophic 4 (T4) represents macro-predator. In this study, for the Acari, the primary decomposers (T1) comprised Ixodida (Ixodes) and Oribatida (Astigmata); Secondary decomposers (T2) contained Oribatida (Brachypyline and Macropyline), Prostigmata (Anystina, Heterostigmata, Parasitengonina, and Raphignathina); Micro-predators (T3) included the Mesostigmata (Gamasina, Uropodidae). The Collembolan fauna was comprised of the T0 Herbivores Symphypleona (Arrhopalitidae, Bourletiellidae, Dicyrtomidae, Mackenziellidae, Sminthuridae, Sminthurididae, Sphyrothecinae, and Sturmiidae); Primary decomposers (T1) Folsomia and Neelipleona (Neelidae); Secondary decomposers (T2) contained Actaletidae, Entomobryomorpha (Entomobryidae and Isotomidae), Poduromorpha (Brachystomellidae, Hypogastruridae, Onychiuridae, Poduridae, and Tullbergiidae).

#### Data Analysis

Soil faunal taxonomic richness (S) was represented by the number of taxonomic groups at each sampling occasion. All data were presented as mean ± standard error, unless otherwise stated. All statistical analyses were performed using SPSS 13.0 (SPSS, Inc., Chicago, IL, USA). Canonical correspondence analysis (CCA; model choice depending on length of first gradient) was performed to analyse the influence of soil management and environmental factors with respect to the soil fauna community

composition. Principal component analysis (PCA) was explored to analyze the influence of field management and sample time on soil fauna community structure. Ordination analyses and hypothesis testing were conducted in CANOCO for Windows v. 4.5 (ter Braak and Šmilauer, 2002). The species data matrix used in CCA were derived from the original individual number data. To meet the assumptions of normality and homogeneity, the data were transformed if necessary by arcsine, square root, or log10(x+1).

#### RESULTS

There was a significant increase in total invertebrate abundance (**Figure 2**) at S2 (P < 0.05) followed by a significant reduction post-ploughing (S3, P < 0.05) where the lowest abundance was recorded. After 1 year (S4) the total abundance had recovered to pre-treatment levels. Although, the total abundance recovered to previous levels, the total biomass was greater at S4 (**Figure 2**). The Shannon diversity index (H'), Richness (soil fauna Taxon number, S) and Evenness index (E) were used to analyse impacts of sampling time on diversity of soil fauna communities (**Figure 3**). There was no significant difference in H' over the first three sampling occasions, but it was significantly (P < 0.05) greater than at S4 1 year later post-reseeding. There was a significant (P < 0.05) increase in E after ploughing which was maintained through to the following year. Taxon richness was greatest after the spray application with a significant (P < 0.05) reduction due to ploughing, however there was a significant (P < 0.05) recovery over the growth of the reseeded pasture back to pre-ploughing levels.

In terms of individual number and relative abundance of each trophic level, the secondary decomposers were the most abundant group (**Figure 4**). The micro-predators (T3) were the second most abundant group in this study. At S4, 1 year postreseed, the proportion of this group was significantly greater than in previous samplings.

Acari and Collembola were the two most abundant soil fauna groups in our study, making up over 90% of the total soil faunal community. The Collembola population was significantly reduced by ploughing, but had recovered 1 year later (S4). The Acari populations were also reduced by ploughing, but different trophic groups showed different recovery patterns. The decomposer population failed to recover, but the predaceous mites did recover previous population levels (**Figure 5**). PCA analysis of the soil fauna community versus sample times showed a significant effect of sample time on soil fauna community and the different taxonomic groups (**Figure 6**). Most data from S1, S2, and S3 were distributed mainly along the x axis, the S4 was separated from most of points along the y axis. Acari had a positive correlation with S2 and S1, Collembola was positive correlated with S2 and S4.

The significance of soil chemical variables in relation to the soil fauna major groups was explored using CCA (**Figure 7**). The Acari were positively correlated with soil pH whilst the Collembola and Coleoptera were positively correlated with soil total carbon content, total C/N ratio and soil bulk density.

#### DISCUSSION

Soil invertebrate communities can be affected by fertilization, tillage regimes, or other grassland management (Zhan et al., 2014; Zhu and Zhu, 2015). In this study, the Acari were the numerically dominant soil invertebrates in this study. The Acari covened most trophic groups; primary decomposers, secondary decomposers and micro-predators in this study. This was due to them encompassing a broad range of feeding guilds, including both specialized and polyphagous predators, parasites, herbivores, fungivores, microbivores, detritivores, scavengers, and omnivores (Krantz and Lindquist, 1979; Lindquist, 1979; Walter, 1987). The most abundant groups were the Oribatida and Mesostigmata. The Oribatid Brachychthonioidea were the numerically most abundant and represented between 24.5% (at S4) and 84.5% (at S3) of total soil fauna in this study with a mean value of 58.8% relative abundance. This result was similar to some studies conducted in Canada, which found that the members of Brachychthoniidae dominate the oribatid mite community in fescue grassland of southern Alberta (Clapperton et al., 2002; Osler et al., 2008). The Oribatida have been reported to be one of the most numerically dominant arthropod groups in the organic horizons of most soils (Norton, 1985), and feed on a wide variety of particulate matter including living and dead plant and fungal material, lichens and carrion (Siepel, 1990). The Mesostigmata was the second most dominant Acari group in this study and these have been shown to be the numerically dominant predators in soil and litter of grassland ecosystems (Behan-Pelletier and Kanashiro, 2010; Crotty et al., 2014). Mesostigmata primarily feed on nematodes, Collembola, soft-bodied mites, insect larvae, and small insects, and they respond rapidly to increased prey in the habitat (Behan-Pelletier and Kanashiro, 2010).

Collembola can occupy all the trophic levels in belowground detritus food-webs (Moore et al., 1988) and together with Acari usually account for around 95% of the microarthropods in soils (Seastedt, 1984). Our findings confirmed this and our results showed that plant residue improvement (after herbicide spraying, S2) could lead to an increase in the abundance of the Collembola, possibly due to the fact that, although they can occupy all trophic levels most Collembola tend to be either microphages, feeding on soil microflora, and/or detritivores, scavenging on dead organic matter and plant litter (Bardgett et al., 1993).

At the outset of the study, there had been no gross perturbation for many years and consequently the soil faunal community was in a stable condition. After the herbicide application (S2), the total number of soil invertebrates peaked (approximately 230000 individuals per m2 ). Similar to some previous studies. Greenslade et al. (2010) found that herbicides had negligible effects on ants and springtails in an Australian wheat field due to having less exposure in surface soil and hydrophobic structure of fauna body. Lins et al. (2007) pointed out that Acari and Collembola could use herbicides to breed themselves until the decomposition product occurs.

The increasing amount of dead material favored the oribatid mites Brachypyline and Macropyline and the Collembola all of which are among the most important decomposers and provide food source for other soil invertebrates (Norton, 1985; Siepel, 1990). The comminution of the dead plant material by these organisms can impact on the habitat in ways that facilitate microbial activity (Eisenhauer et al., 2007). The increased numbers of herbivores and decomposers, also promoted the

groups. Bars represent stacked mean values (n = 24). Different lowercase letters represent significant differences among sample times (P < 0.05) using one way ANOVA test and Duncan's multiple range test. Divergence analysis was listed in table, different lowercase of each row represented significant difference among sample times in given Acari/Collembola groups.

abundance of some micro-predators such as Mesostigmatid mites (Supplementary Table S1; **Figure 8**).

After ploughing (S3), there were significant reductions of soil invertebrate individual number and biomass. Total soil invertebrate number decreased from approximately 23000 to 61000 individuals per m2 and total arthropod biomass decreased from 9680 to 5280 mg per m2 . This could be attributed to the greater impact of ploughing on the larger arthropods such as the Coleoptera and Diptera. Both mites and Collembola have been used as bioindicators of soil quality due to their high sensitivity to disturbances (Prasse, 1985; Hopkin, 1997), and both these groups declined sharply in number with ploughing. Ploughing influences the distribution of resources. Thus, the fauna in the deeper horizon is enriched by a surviving fraction of the surface fauna which to some extent compensates for the mortality due to abrasion, etc. On the other hand, the less abundant fauna of deeper soil layers are translocated to the surface layers where they are more exposed to drought and other microclimatic extremes (Petersen, 2002).

After reseeding (S4), and after all fields had had 1 year of recovery, the total soil invertebrate number and biomass increased (total number from approximately 61300 in S3 to 125000 individuals per m2 in S4; total biomass from 5280 in S3 to 29300 mg per m2 in S4). Here, the Collembola populations recovered to their pre-treatment levels. Although, the Acari populations appeared to recover, when broken down the decomposer populations remained low, but the predatory mites significantly increased showing a significant increase in the predator/prey ratio at this time point (**Figure 4** and Supplementary Table S2), indicating the relative instability of the community.

The CCA indicates that soil invertebrate groups as Acari, Collembola, Coleoptera, Diptera, and other taxa are influenced by the soil pH value, bulk density, soil total carbon and nitrogen content, and total C/N ratio. Similar results have been reported by other authors, who concluded that a pH close to neutral is optimal for Acari (Bedano et al., 2006). Soil total carbon content, total C/N ratio and bulk density showed a strong relationship with arthropod groups such as Collembola and Coleoptera. Consistent

FIGURE 6 | Principal component analysis (PCA) of the soil fauna community and major soil fauna groups. S1 represent sample time 1, before herbicide spray; S2 represent sample time 2, after spray and before plough; S3 represent sample time 3, after plough and before seed; S4 represent sample time 4, after seed.

with some previous studies from Europe (Brennan et al., 2006; García et al., 2010).

#### CONCLUSION

Herbicide application tended to increase soil invertebrate abundance due to the plant residue improvement, less exposure and edibility of herbicide for some soil arthropod. Whereas subsequent ploughing significantly reduced soil invertebrate number and biomass due to its disturbance effects. Ploughing had an obvious negative effect on soil primary and secondary decomposers. This change was mainly due to the Acari (especially Oribatida) and some Coleoptera group abundance variations.

Reseeding also reduced individual numbers in groups, and favored those predators with larger body size and individual weight. Over the following year, different arthropod groups responded differently, with Collembola populations recovering to pre-treatment levels. However, the Acari populations still appeared to be in flux 1 year on.

Wagg et al. (2014) showed that loss of soil biodiversity together with the simplification of communities negatively impacts on many ecosystem functions. Thus, maintenance of a healthy soil food web is key to maintaining and in increasing agricultural productivity (Crotty et al., 2015). This study highlights how common agricultural practices impact on soil fauna communities, this impact might cause some ecological function change of soil, and how different components of the community respond differently to the disturbances caused.

#### AUTHOR CONTRIBUTIONS

PM and JZ conceptualized the study, WL collected, processed, and identified samples with help from SN. WL primarily interpreted the data with contributions from PM and JZ. WL and PM wrote the manuscript and all authors were involved in reviewing, revision and final approval of the manuscript.

#### FUNDING

This study was funded as part of a BBSRC China Partnering Award (BB/I024933/1). The North Wyke Farm Platform is a BBSRC supported National Capability (BB/J0004308). Funding was also supplied through the National Natural Foundation of China (31400528), the European Union within the Project EcoFINDERS (FP7-264465) and the Natural Science Foundation of Jiangxi (20151BAB214018) and the Chinese Ministry of Agriculture (201103004). The Australasian Congress of Grassland Invertebrate Ecology provided financial assistance for open access publication fees.

#### ACKNOWLEDGMENTS

fpls-07-01200 August 9, 2016 Time: 12:6 # 8

We thank Xiaoliang Li for statistical help. Special thanks go to Professor Junling Zhang and Jinping Gai at China Agricultural

#### REFERENCES

University for assistance in manuscript modification. This paper is as part of a series of articles from the ninth Australasian Congress of Grassland Invertebrate Ecology (ACGIE) and received sponsorship from ACGIE/Hawkesbury Institute for the Environment, Western Sydney University, Australia.

#### SUPPLEMENTARY MATERIAL

The Supplementary Material for this article can be found online at: http://journal.frontiersin.org/article/10.3389/fpls.2016.01200

stricta grassland in upland Scotland. Agric. Ecosyst. Environ. 86, 39–57. doi: 10.1016/S0167-8809(00)00263-2

Hopkin, S. P. (1997). Biology of Springtails. New York, NY: Oxford University Press.

peltifer (Koch) (Acari, Oribatida, Camisiidae). Biol. Fertil. Soils 9, 139–144. doi: 10.1007/BF00335797

**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2016 Liu, Zhang, Norris and Murray. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

fpls-07-01200 August 9, 2016 Time: 12:6 # 9

# Detection of Invertebrate Suppressive Soils, and Identification of a Possible Biological Control Agent for Meloidogyne Nematodes Using High Resolution Rhizosphere Microbial Community Analysis

Nigel L. Bell1 \*, Katharine H. Adam1 , Rhys J. Jones1 , Richard D. Johnson2 , Yeukai F. Mtandavari1 , Gabriela Burch1 , Vanessa Cave3 , Catherine Cameron3 , Paul Maclean4 , Alison J. Popay1 and Damien Fleetwood5

1 Soil Biology Team, AgResearch Ltd, Ruakura Research Centre, Hamilton, New Zealand, 2 Plant/Fungal Interactions Team, AgResearch Ltd, Grasslands Research Centre, Palmerston North, New Zealand, 3 Bioinformatics and Statistics Team, AgResearch Ltd, Ruakura Research Centre, Hamilton, New Zealand, 4 Bioinformatics and Statistics Team, AgResearch Ltd, Lincoln Research Centre, Christchurch, New Zealand, 5 Biotelliga Ltd, Institute for Innovation in Biotechnology, Auckland, New Zealand

#### Edited by:

Ivan Hiltpold, University of Delaware, USA

#### Reviewed by:

Raquel Campos-Herrera, University of the Algarve, Portugal Ziga Laznik, Biotechnical Faculty, Slovenia

> \*Correspondence: Nigel L. Bell<EMAIL_ADDRESS>
#### Specialty section:

This article was submitted to Agroecology and Land Use Systems, a section of the journal Frontiers in Plant Science

> Received: 31 May 2016 Accepted: 07 December 2016 Published: 26 December 2016

#### Citation:

Bell NL, Adam KH, Jones RJ, Johnson RD, Mtandavari YF, Burch G, Cave V, Cameron C, Maclean P, Popay AJ and Fleetwood D (2016) Detection of Invertebrate Suppressive Soils, and Identification of a Possible Biological Control Agent for Meloidogyne Nematodes Using High Resolution Rhizosphere Microbial Community Analysis. Front. Plant Sci. 7:1946. doi: 10.3389/fpls.2016.01946 White clover (Trifolium repens) is the key legume component of New Zealand pastoral agriculture due to the high quality feed and nitrogen inputs it provides. Invertebrate pests constrain white clover growth and this study investigated rhizosphere-associated fungal controls for two of these pests and attempts to disentangle the underpinning mechanisms. The degree of suppressiveness of 10 soils, in a latitudinal gradient down New Zealand, to added Meloidogyne hapla and Costelytra zealandica scarab larvae was measured in untreated soil. Most of the soils showed no suppressive activity against these pests but two showed activity against M. hapla and two against C. zealandica. Rhizosphere fungi responsible for pest suppressive responses were elucidated via next-generation sequencing. In the M. hapla-suppressive soils nematode-trapping Orbiliomycetes fungi were present in significantly greater abundance than non-suppressive soils and their abundance increased further with addition of M. hapla. A comparison of plant growth and the rhizosphere fungal community between untreated and irradiated soil was carried out on 5 of the 10 soils using Pyronota as the scarab larvae. Soil irradiation either: reduced (by 60–70%); increased (16×) or made no difference to white clover growth across the five soils tested, illustrating the range of microbial impacts on plant production. In one of the M. hapla suppressive soils irradiation resulted in a significant increase in nematode galling suggesting that Orbiliomycetes fungi were indeed responsible for the suppressive effect. Lack of consistent changes in soil macronutrients and pH post-irradiation suggest these were not responsible for plant or invertebrate responses. The use of next generation sequencing in controlled pot trials has allowed identification of a potential biological control organism and bioindicator for M. hapla suppression.

Keywords: Trifolium repens, white clover, rhizosphere, grass grub, manuka beetle, next generation sequencing, ¯ Mi-Seq, biological control

### INTRODUCTION

fpls-07-01946 December 22, 2016 Time: 17:9 # 2

New Zealand agriculture is dominated by pastoral grazing systems used to grow animals for their meat, milk, or wool (Statistics New Zealand, 2015). Pastures in these systems largely consist of grass/legume mixtures of various sorts with the majority of mixtures being Lolium (mostly L. perenne)/Trifolium (mostly T. repens) (Li et al., 2011). In these mixtures the grass provides the bulk of the grazing ruminant's diet with the legume supplying high protein forage and nitrogen fixation capability. Pastures occur across a broad range of soil and climate conditions the length and breadth of the country (Cullen et al., 2008) so face a range of biotic and abiotic challenges and interact with a wide range of soil microbes. Of the biotic challenges to pastures, invertebrates, including root-feeders, represent a significant check on plant growth (see Goldson et al., 2015).

Invertebrates with contrasting scales and types of impact on T. repens include scarab beetles (such as Costelytra zealandica and Pyronota spp.) and nematodes, such as Meloidogyne hapla. Scarab larvae consume plant root tissue (Kain and Atkinson, 1977), reducing root mass and impinging on root function which can result in plant death when they occur at sufficiently high populations densities (East et al., 1980). M. hapla juveniles invade root tissue immediately behind the root growing point and establish a permanent feeding site by means of induction of giant cells which are created via plant growth regulator stimulation of the plant tissue (Moens et al., 2010). The resulting galls (or "knots," which give them the common name root-knot nematodes) impair root function but usually only result in plant death if accompanied by other stressors such as low soil nutrient status or water deficit.

The rhizosphere is the area of soil directly in contact with plant roots or their secretions and as such is the site of intense interactions between the plant and soil microbes. This zone is also the first point of contact between plants and invertebrate root-feeders, with plant secretions being used as food signals for root-feeders (see van Dam and Bouwmeester, 2016). It is therefore likely that at least some of the microbes in this zone would be adapted to utilizing soil invertebrates as a food resource (either as closely associated root residents or as recruits in response to plant damage, as occurs in disease responses (see Berendsen et al., 2012), making the rhizosphere an important area to target in the search for biological control (biocontrol) agents against pest invertebrates. Traditionally, invertebrate pathology studies have uncovered microbial biocontrol agents by examining diseased individuals and this has been successful for bacteria against C. zealandica in New Zealand (Grimont et al., 1988), and for some Meloidogyne species overseas (see Davies, 2009). A rhizosphere-based approach to detecting biocontrol agents would, alternatively, need to consider which microbes increase in abundance in response to herbivore feeding on, or invasion of, roots. Those microbes responding most strongly would then be good candidates for biocontrol agents that are also rhizospherecompetent, an important consideration for persistence of agents in the soil. Along with potential biocontrol agents, a rhizospherebased approach may identify bioindicators of pest suppression. Such bioindicators could be used to quantify the need, or not, for control measures to be implemented as part of operations such as pasture renewal or crop rotations (e.g., Ophel-Keller et al., 2008).

A culture-dependant method for a rhizosphere-based approach to detecting organisms responsible for soil pest suppression would clearly underestimate the diversity of potential biocontrols and bioindicators. Culture dependant techniques also require either: some prior knowledge of an existing pest suppression mechanism; or that a wide variety of culturing isolations be employed to find any causative mechanism. Culture-independent techniques, by contrast, allow for enumeration of the majority of microbes in soil and would provide clearer evidence of potentially useful biocontrols or bioindicators. Techniques such as high-throughput sequencing are rapidly developing and have recently moved from 454 pyrosequencing to the Illumina Mi-Seq platform (Derakhshani et al., 2016) which can generate up to 150-bp sequencing reads with a total throughput of 1.5–2 Gb per run. Such technologies have facilitated analysis of environmentally derived samples from a variety of ecosystems, including soil, and can measure very small changes in community structure across different samples (Schmidt et al., 2013).

The focus of this study was the below-ground biotic challenge to T. repens presented by root feeding invertebrates and the changes that this challenge evokes within the rhizospheric fungal microbiota. We have utilized next generation sequencing to explore the fungal microbiota present in the rhizosphere of T. repens across a range of New Zealand soils and in the face of challenges from these invertebrate pests. We hypothesize that near-isogenic T. repens plant performance will differ in different soils from across New Zealand and that this will be linked to interactions between components of the rhizosphere microflora and soil dwelling root pests. A substantial comparison of the high resolution microbial communities will form the basis of a separate paper.

### MATERIALS AND METHODS

#### Pot Trials

Soil samples were collected from 10 sites previously characterized by Wakelin et al. (2013) that represented a wide range of geographical locations and soil characteristics, primarily pH and nitrogen levels (**Figure 1**). In addition, half the sites were on brown soil type and half on recent soils, while four sites were dairy farms and six were sheep and beef farms. From each site 200 mm × 200 mm × 200 mm cubes of soil were excised between January and February 2014 or August and September 2014 for Experiments 1 and 2, respectively. The top 15 mm of plant matter and soil was removed from each cube and the remainder stored in sealed buckets at 4◦C. Collection and manipulation of soil was performed with gloves and implements rubbed with 70% ethanol to sanitize.

Soil was passed through a 4 mm sieve and mixed by hand to homogenize. Nematodes were extracted and counted from 100 g of each soil using the method of Bell and Watson

(2001). The extraction ran for 72 h, after which the resulting nematode suspension was reduced to a final volume of 20 ml by a combination of beaker settling and aspiration. The total number of nematodes and plant parasitic nematodes were counted in a Doncaster dish (Doncaster, 1962) under a stereo-microscope at 40–80× magnification; plant parasitic nematodes were identified to genera based on the keys of Siddiqi (2000) for Tylenchida and Bongers (1994) for other groups. To allow for valid comparison across treatments, results are presented as nematodes per 100 g of dry soil. Further subsamples from each soil were sent to Hills Laboratory (Hamilton) for soil nutrient analysis [pH, Olsen P, Sulfate S, K, Ca, Mg, Na, total N and cation exchange capacity (CEC), see http://www.hill-laboratories.com/file/fileid/15530 for methods].

Initial moisture of each soil was determined from three 10 g samples oven dried at 80◦C for 24 h. Water holding capacity (WHC) was determined by adding 180 g of each soil into small pots (50 mm × 50 mm × 120 mm), weighing the combination of pots with soil, soaking for 24 h, draining for 72 h and reweighing. The 100% WHC of the system was calculated as the total weight of water held in the system (including initial soil moisture).

Pots were filled with 180–200 g soil per pot, depending on soil, with capillary mat inserted at the base of the pots to assist with water and soil retention. Pots were designated to one of three treatments: clover-only control; clover with M. hapla added; or clover with root-feeding scarab larvae added. For the larvaeinoculated pots a plugged hole and wire mesh were incorporated into the pot (**Figure 2**) to allow for introduction of the larva and to prevent larvae consuming the entire clover root system, respectively. Pots were arranged in a randomized split plot design with soils allocated to the whole-plots and treatments to the subplots.

Near-isogenic white clover seed (S9) was obtained from a breeding population developed within AgResearch derived from cv. Crau. A near-isogenic seedline was selected in an attempt

to reduce between-plant variability in growth and reaction to imposed treatments. Seeds were scarified by abrasion with 'wet and dry' sandpaper then surface sterilized by soaking for 15 min in 10N H2SO4 containing a drop of Tween 80, then washing five times in sterile milliQ water. Seeds were sprouted on moist sterile filter paper at 20◦C for 3 days prior to planting into pots. A single plant was sown into each pot. Aseptic techniques were used during planting to prevent cross contamination between soils. Plants were grown at isothermal 20◦C under high pressure

sodium vapor lamp lighting on a 16 h light and 8 h dark cycle. M. hapla and scarab larvae were added 5 weeks after sowing clover plants into pots.

MilliQ water was initially added to each pot to bring moisture levels up to 70% WHC. Once a week each pot was reweighed and returned to 70% WHC. Between each weekly weighing pots were checked daily and any that appeared dry were watered with 3– 5 ml. Following inoculation of the plants with M. hapla or scarab larvae watering was reduced to 60% WHC in Experiment 1 but maintained at 70% WHC in Experiment 2.

Meloidogyne hapla stock populations [confirmed as such by ITS sequencing (555 bp sequence 99% match to M. hapla (GenBank reference: LC030360), query coverage 100%, see Rohan et al., 2016 for PCR methodology)] were established and maintained on tomato plants (Solanum lycopersicum cv. 'Rutgers') under glass house conditions. After 4 months galled tomato roots were excised from the tomato plants, and nematode eggs were collected following Aalders et al. (2009). The resulting inoculum consisted of 1089 (± 31 SEM) eggs and 20 (± 6) J2 juvenile M. hapla per ml with 346 (± 38) of the eggs being embryonated. A 1 ml aliquot of inoculum was added to each nematode-treated pot via a 20 mm deep hole made 10 mm from the base of the plant, followed by addition of 1 ml of sterile water. The hole was then filled in from surrounding soil to prevent desiccation of inoculated nematodes.

#### Next-Generation Sequencing

DNA was extracted from rhizosphere samples using a PowerSoil R DNA Isolation Kit (MO BIO Laboratories, Carlsberg, CA, USA). Stored soil fractions were thawed and then centrifuged at 7000 × g for 5 min. The supernatant was decanted and discarded. For each sample, 0.25 g of pellet was placed in a sterile 2 ml tube and the contents of one PowerSoil R tube added. DNA was then extracted according to the kit manufacturer's instructions with one exception: a 3 min mix using a bead-beater was substituted for the post-Soln C1 vortexing step. DNA extracts were quantified using a NanoDrop 2000C spectrophotometer (Wilmington, DE, USA) and then stored at −20◦C for PCR reactions.

Amplification of fungal ribosomal internal transcribed spacer (ITS) sequences were performed in reaction mixtures that included 0.2 µM of each primer using iProof HF polymerase (Bio-Rad Laboratories, Hercules, CA, USA) and the manufacturers instructions. PCR cycling conditions were: 95◦C for 3 min followed by 35 cycles of 95◦C/30 s, 46◦C/30 s, and 72◦C/60 s; followed by 72◦C/9 min final extension. For amplifying fungal ITS sequences, ITS3\_KYO2F and ITS4R primers (Toju et al., 2012) were used with appended Illumina sequences:

ITS3\_KYO2\_miseqF TCGTCGGCAGCGTCAGATGTGTAT AAGAGACAG GATGAAGAACGYAGYRAA ITS4\_miseqR GTCTCGTGGGCTCGGAGATGTGTATAAGA GACAG TCCTCCGCTTATTGATATGC

PCR products were purified using a GeneJET PCR Purification Kit (ThermoScientific, Lithuania) and purified product was quantified using a NanoDrop 2000C spectrophotometer (Wilmington, DE, USA). ITS products were then normalized to 0.1 ng/µl using ultrapure water. For each normalized sample, 5 µl aliquots were made up to 25 µl volumes in half-skirt 96-well plates using ultrapure water containing a 467 bp exotic control sequence (synthetic zebrafish sequence appended with Illumina clamps) added to a ratio of 1:50 control sequence-to-sample DNA (i.e., 20 pg:1 ng in 25 µl volumes). Prepared plates were sent to New Zealand Genomics Limited (NZGL, Massey University, Palmerston North, New Zealand) for second PCR amplification and sequencing on an Illumina MiSeq platform.

#### Experiment 1

For each soil each treatment (clover-only control; clover with M. hapla added; or clover with root-feeding scarab larvae added) was replicated 12 times giving a total of 360 pots. Second instar C. zealandica larva were collected from soil at a site near Tokoroa (lat/long 175.90, −38.19) in the Waikato district, and stored at 4 ◦C. A single pre-weighed larva was added to each pot (giving an equivalent of 400 larvae/m2 ) within 24 h of being collected and larvae were re-weighed at harvest when numbers of live and dead larvae were recorded. M. hapla inoculum consisted of 1089 ( ± 31 SEM) eggs and 20 ( ± 6) J2 juvenile M. hapla per ml with 346 ( ± 38) of the eggs being embryonated.

Clover plants were harvested after 9 weeks growth (4 weeks after M. hapla and C. zealandica inoculation). Plants were removed from pots and tipped onto a sterile surface. Soil was gently removed by hand to leave a 2 mm zone of soil around the roots (considered rhizosphere soil). C. zealandica larvae were removed, weighed and stored at 4◦C. Total plant, shoot and root length were measured then roots were separated from stems and the stem/leaf component dried at 80◦C for 48 h and dry weight recorded. All root material and associated soil was placed in a 50 ml Falcon tube with 25 ml sterile saline and vortexed at high speed for 15 s. The partially washed root material was then transferred to 20 ml fresh saline and revortexed for 15 s. The two soil-containing wash fractions were combined and a 0.5 ml aliquot from each sample was mixed with 60% glycerol and stored at −80◦C for further analysis. The remaining soil suspension was stored at −20◦C for rhizosphere DNA extraction.

Root length was recorded and the number of Meloidogyne galls assessed microscopically on roots in the control and nematode inoculated treatments. During the course of nematode assessment a score was assigned for degree of root rotting on a 0–3 scale with 0 being no rotting, 1 minor rotting symptoms, 2 moderate rot, and 3 severe rot including roots truncated due to root rotting. No attempt was made to determine the cause of root rots.

#### Experiment 2

Soil samples for the second trial were collected from five of the sites used in Experiment 1 (Soils 1, 4, 7, 9, and 10). Half the volume of each soil was sterilized by irradiation using 25–32 kGy followed by 15–17 kGy doses (MSD Animal Health, Upper Hutt, New Zealand). A spread plate technique using Tryptic Soy Agar and Potato Dextrose Agar (TSA and PDA) was used to test sterility of soils using a 1 g soil sample in 9 ml sterile water to

prepare the dilution series and agar plates were incubated for 72 h at 20◦C.

To limit macronutrient differences between irradiated and non-irradiated samples, soils were mixed with pumice. Initial moisture content was determined using 10 g samples of each soil (three replicates per soil). To determine 100% WHC of each soil: pumice mix, an equivalent of 20 g dry soil and 127 g dry pumice were weighed into pots in three replicates per soil and soaked in water for 72 h before being suspended over a tray to drain for 24 h. Final weights per replicate were averaged and used to calculate 70% WHC.

Six treatments were initiated for each soil: non-irradiated or irradiated soil, each with or without the addition of M. hapla or Pyronota (manuka beetle) or an untreated control ( ¯ Pyronota larvae were substituted for C. zealandica due to the lack of availability of C. zealandica at the time of the experiment. Both are root-feeding scarabs). Each treatment consisted of 10 replicates giving sixty pots per soil. The pots where Pyronota were added were as for the C. zealandica treatment in Experiment 1. The capillary mats for all sterile pots were autoclaved at 121◦C for 20 min while the pots were soaked in 95% ethanol for 1 min. Each pot was filled with a mixture of 20 g dry weight equivalent soil and 127 g autoclaved 4 mm graded pumice, then watered to 70% WHC.

Seed preparation was done similarly to the first trial. The seedlings were aseptically planted, one seedling per pot, and watered with 2 ml of sterile water. Moisture of the soil:pumice mix was maintained at 70% WHC by watering every second day with sterile water for the duration of trial. All M. hapla egg methods were as for Experiment 1 with inoculum containing an average of 3,923 eggs (27% of eggs embryonated) and 26 J2 juveniles per ml.

Pyronota sp. beetle larva were collected from a site near Ohakune in the central North Island (lat/long 175.37, −39.39) on 13 November 2014, and individually weighed before aseptically adding them to pots as per C. zealandica in Experiment 1. Due to the late stage of larval development (L3), and to ensure sufficient larval feeding and damage to detect soil differences, two larvae were added to each pot. The larvae were added one at a time to each pot, allowing sufficient time for the first larva to bury itself into the soil/pumice mix before adding the second larva so as to minimize the possibility of larval combat. Plants were harvested during week 9 of the trial and processed and analyzed as for Experiment 1.

#### Data Analyses

All plant and invertebrate data analyses were carried out in GenStat version 16. Unless otherwise stated, data were analyzed by split plot ANOVA with soils applied at whole-plot level and treatments at the subplot level. Shoot dry weight was loge (n+5) transformed prior to analysis to stabilize the variance (5 is half the minimum non-zero value). M. hapla gall data was analyzed using split-plot REML (GenStat version 16), again with soils applied at whole-plot level and treatments at the subplot level. REML was used as the data is unbalanced with missing data for dead plants and this makes the analysis conditional on plant survival. That is, if galling had affected plant survival the means would be negatively biased. Gall data was loge (n+1) transformed prior to analysis to stabilize the variance. For Experiment 1 the gall data was analyzed with root length as a co-variate. The proportion of plants without root rot (i.e., score = 0) was analyzed as split-plot using Generalized Linear Mixed Model – Binomial distribution with Logit link. The proportion of total number of plants without rot was calculated including dead plants, chosen because dead plants are likely to have had root rot (i.e., root rot is not independent of plant death).

For Illumina sequences the reads were joined using PEAR (Zhang et al., 2014) version 0.9.6 using a quality cut off of 30, a minimum joined length of 250 bp and a maximum joined length of 480 bp and a minimum overlap of 10. The sequences were assigned to the different amplicons based on exact matches to the flanking primers (minus the Illumina adapters).

The headers of the sample files were edited to add the sample name to each read. All samples were then pooled into a single file. This file was dereplicated using the Mothur (Schloss et al., 2009) program unique.seqs. In-house Ruby scripts were then applied to modify the headers of the reads to be used with the clustering program Swarm (Mahé et al., 2014). After clustering the putative OTUs were filtered based on abundance and prevalence as follows: an OTU was kept if it was present in 2% of the samples with an abundance >0.1% or in 5% of the samples with an abundance >0.01%, furthermore an OTU was kept if it represented 0.001% of the overall population in all samples together.

The representative sequence for each of the OTUs were annotated using the assign\_taxonomy.py script from Qiime (Caporaso et al., 2010), where the uclust consensus taxonomy assigner was used to annotate the 16S amplicon sequences with the greengenes (McDonald et al., 2012) 13\_8 database, and BLAST was used to annotate the ITS amplicon sequences with the UNITE (Kõljalg et al., 2005) 02.03.2015 release.

The OTU counts were converted into percentages of total OTU counts less the OTU corresponding to the T. repens reads. After treatment and other sample information was added, the OTU percentages were loaded into R (R Core Team, 2015) version 3.2.1 as tab separated values. Boxplots and t-test were done on subsets of the data with the default settings.

### RESULTS

### Experiment 1

There was a wide range of pH and macronutrient levels across the soils used in this study (**Table 1**), with broad agreement between levels measured here and those by Wakelin et al. (2013) from the same soils, with the exception of pH in soil 9. The northernmost soils (1 and 2) had the greatest CEC values while soil 5 was notable for a high level of Mg and soil 8 for low total N.

The nematodes found in the soils prior to sowing were within the ranges normally seen in pasture soil, with potentially plant damaging populations of Pratylenchus present in soil 3 in Experiment 1 and of Heterodera and Pratylenchus in soil 7 for Experiment 2. Sequencing of the ITS region of Meloidogyne

TABLE 1 | Macronutrient levels and pH in soils prior to sowing plants for Experiment 1 (soil number, pH and Total N data in parentheses are from Wakelin et al., 2013).

observed in soil extracts prior to sowing (**Table 2**) showed the presence of M. trifoliophila in soil 3 and Meloidogyne fallax in soil 4. No usable sequence information was obtained from Meloidogyne specimens in soil 2, but morphological observations of root galls from clovers growing in the soil at field sampling and of J2 juveniles in the soil extract prior to sowing suggest these were also M. trifoliophila. None of the populations of other plant feeding nematode genera were likely to be having a significant effect on clover growth, with the possible exception of the Pratylenchus population in soil 3. In addition to the plant feeding nematodes listed in **Table 2**, Criconematidae were observed from soil 10 and Tylenchorhynchus from soil 9 (both 10/100 g dry soil).

There was a large range of shoot and root growth across the soils (**Figure 3**) which illustrates the range of white clover productivity across New Zealand. There was no clear pattern for either soil type (brown or recent) or grazing system (dairy or sheep and beef) as drivers for these growth differences. Geographically, there was a tendency for lower shoot and root production in more northerly soils, with the greatest production from the southernmost soils. With temperature and moisture not limiting factors in these pot trials other factors such as soil nutrients and pest invertebrates (e.g., nematodes) and diseases were likely drivers of growth differences. Unsurprisingly, there were positive correlations between soil P and K and clover shoot and root growth but these were not significant. There was a significant negative correlation between soil CEC and root length (r = −0.736, P < 0.05) (**Table 1**; **Figure 3**).

Addition of C. zealandica larva or M. hapla eggs to pots significantly reduced clover shoot weight in only one of the soils (**Figure 3**). However, C. zealandica feeding significantly reduced root length compared to control plants in all the South Island soils. It is likely that the mesh inserted in the C. zealandica pots ensured there was sufficient root system remaining to support similar shoot growth to the control plants. There were some significant differences in the weight of C. zealandica initially added to soils (**Table 3**). Soils 5 and 8 were inoculated with

TABLE 2 | Total nematodes and plant feeding genera per 100 g dry soil and soil moisture of subsamples after sieving and prior to being used to fill pots.

larvae that were significantly heavier than those in soils 4 and 7. However, those differences had disappeared by the time of harvest. Significantly fewer grubs survived the 4 week duration between inoculation and harvest of the experiment in soils 4 and 10 than most other soils.

Inoculation with M. hapla did not result in significant changes in clover shoot growth in any of the soils (**Figure 3**). However, it is notable that the only soils where M. hapla inoculation resulted in significant reductions in root length were from the southern South Island where clover-feeding Meloidogyne have

TABLE 3 | Experiment 1: Mean Meloidogyne nematode root galls (back-transformed data with loge-transformed data in parentheses) and weight of C. zealandica larvae at inoculation into pots (Initial) and at harvest (Final).

Lsd values are to compare: across soils (soil) or treatments across soils (treatment∗soil). Astrices denote significant difference to control for nematode data and significant difference to the soil with the greatest survival rate for C. zealandica.

until recently only been rarely encountered in pastures (personal observation).

Inoculation with M. hapla significantly increased root galling in all but soils 5, 7, and 9 (**Table 3**). It is not clear what was responsible for that effect in soil 5 but in soils 7 and 9 fungal community analysis by high-throughput ITS sequencing showed that there were significantly greater abundances of Orbiliomycetes fungal sequences in those than in other soils. Addition of M. hapla further increased abundance of these fungi (**Figure 4**).

For root rotting score there was no significant difference between the control and M. hapla inoculated soil so results were pooled. Mean root rot scores were generally low to minor severity (**Table 4**). There were significant differences in root rotting incidence between soils, with soils 1 and 10 having the lowest proportion of plants without any signs of rot and this was significantly different to all other soils.

### Experiment 2

A second trial was set up to validate the results from Experiment 1 and to directly test the impact of the overall soil microbial content by using a pumice/soil mixture to reduce abiotic effects and comparing biotic with sterilized soil. A different scarab beetle was also used to measure insect effects – in this case a Pyronota sp. scarab due to the lack of available C. zealandica larvae.

From extractions carried out before sowing clover there was a greater abundance of total nematodes in all but soil 10 compared to the samples collected for Experiment 1 (**Table 2**). These differences in initial nematode population numbers and plant feeding genera present between Experiments 1 and 2 reflect differences in the time of year sampling was carried out and concomitant greater soil moistures. Heterodera and Pratylenchus spp. were observed at moderate to high populations in all but soil 1. Meloidogyne spp. were observed in two soils, neither of which had this genus present in samples taken for Experiment 1. Morphology of J2 juvenile tails and galls suggested the Meloidogyne from soil 1 were M. trifoliophila. The Meloidogyne sp. present in soil 10 was identified from tail morphology as the grass-feeding M. naasi. Some of the individuals observed were heavily encumbered by the nematode-pathogenic bacteria Pasteuria sp.

The pumice used to dilute soils had notably greater pH and Na levels than any of the soils used in this experiment, so that these parameters were elevated in the soil:pumice mix used (**Table 5**). Irradiation produced no consistent differences in macronutrient levels in the pumice: soil mix. The largest changes due to irradiation were in Olsen P in soils 1, 4 and 10; K in soils 9 and 10; and Ca in soil 1. pH was generally increased after irradiation (by 0.1–0.3), except for soil 10 where no change in pH was observed. Compared to soils alone used in Experiment 1 (**Table 1**) the soil:pumice mix used in Experiment 2 resulted in a reduction in the magnitude of differences in the pH and macronutrient parameters amongst the five soils. Spread plating of irradiated soils showed no microbial growth.

For all soils combined there was a significant reduction in clover shoot weight in irradiated (ln shoot weight = 3.94 g) compared to non-irradiated (4.12 g) soil (lsd 5% = 0.179 g). For control soils irradiation significantly reduced shoot growth in soils 4 and 9 but significantly increased white clover shoot growth in soil 1 and resulted in no significant difference in the remaining two soils (**Figure 5**). Changes in shoot weight in irradiated vs. non-irradiated soil for invertebrate treatments largely mirrored those for the control with the exception of the nematode treatment in soil 7 where plants in irradiated soil produced significantly greater shoot mass than those in nonirradiated soil.

For all non-irradiated soils combined there was no significant effect of invertebrate treatment on shoot growth. However, in irradiated soils there was a significant decrease in white clover shoot dry weight in the manuka beetle treatment (ln shoot ¯ weight = 3.49 g) compared to the control (4.24 g) and M. hapla

TABLE 4 | Experiment 1: Arithmetic mean root rot score and back-transformed proportion of control roots without rot (Logit transformed data ± SEM in parentheses) for Experiment 1.

(4.10 g) treatments (lsd 5% = 0.309) (**Figure 5**). For individual soils the only significant decreases in shoot growth compared to control occurred in M. hapla treatment in non-irradiated soil 7 and in the manuka beetle treatment in irradiated soils 1, 4, ¯ and 7.

Irradiation significantly increased root length over all soils combined (116.0 mm) compared to non-irradiated soil (91.1 mm, lsd 5% = 4.71), which was largely due to the increases in root length due to irradiation of soils 1 and 7 (**Figure 5**). Manuka ¯ beetle significantly reduced root length for all soils combined (99.3 mm), compared to the control (106.9 mm) but this was not the case with the M. hapla treatment (104.5 mm, lsd 5% = 5.77), with no interaction due to irradiation (P = 0.825). The only significant difference in root length, compared to control soil, due to invertebrate pests for individual soils was in non-irradiated soil 7 where the M. hapla treatment gave a decrease in root length. It is possible the combined populations of Heterodera and Pratylenchus in soil 7 (**Table 2**) had an impact on clover root and shoot growth, in addition to the added M. hapla.

For soils 4 and 9 inoculation of plants with M. hapla resulted in significantly more nematode galls in both irradiated and non-irradiated soil, compared with the non-irradiated control soil (**Table 6**). In soils 1, 7, and 10 only inoculation into irradiated soil resulted in increased galling. In contrast to the other two soils with this effect, the addition of M. hapla to soil 7 also increased root rotting (**Table 7**), and both clover root and shoot growth were significantly reduced in this treatment (**Figure 5**).

The proportion of the sequences that were of Orbiliomycetes fungi was much lower in this experiment that in the previous one (**Figure 6**), with their proportion approximately in line with the soil dilution rate (ca. 6×) for soils 7 and 9 but much lower than that in soil 4. As for Experiment 1 these abundances increased in response to added M. hapla but in this case none of the increases were significant.

The initial weights of Pyronota larvae added to pots was not significantly different between soils or treatments (data not shown), however final weights and, therefore weight change of larvae at the end of the experiment were significantly different amongst some soils and treatments (**Table 6**). In soils 1, 4, and 9 there was an increase in final weight of larvae in irradiated vs. non-irradiated soil, which was significantly so for soil 4. Significantly less beetle larvae survived in non-irradiated soil 1 (0.9) compared to non-irradiated soil 7 (1.7, lsd 5% = 0.61) but

TABLE 5 | Macronutrient levels and pH in pumice alone, soil alone or soil:pumice mix (Mix) prior to sowing plants for Experiment 2.

there was no significant difference in beetle survival amongst irradiated soils. Some larvae had developed through to pupae and adults at the end of the experiment and were discounted from the analysis of final weights.

Irradiation eliminated root rot from all soils (mean score = 0.0) which was significantly less than the overall score in control (0.8) which in turn was significantly less than in nematode treated soil (1.0, lsd 5% = 0.2). This effect was significant for soil 7. Soil 9 was the only one of the five soils in which root rot was not observed in any of the treatments (**Table 7**). Similar to root rot the number of rhizobial nodules was significantly reduced in irradiated soil inoculated with M. hapla (0.05/ mm root) compared to control (0.16/mm) and M. hapla treated non-irradiated soil (0.15, lsd 5% = 0.029). The only individual soil for which this did not hold true was soil 1 where nodules/ mm root in irradiated soil inoculated with M. hapla was not significantly different to control or M. hapla-inoculated non-irradiated soil (**Table 7**).

### DISCUSSION

Invertebrate pests had deleterious effects on T. repens root and/or shoot growth in some soils, across both experiments. In a minority of soils, however, invertebrate pests had no significant impacts on plant growth or damage in either experiment. For M. hapla it appears Orbiliomycetes fungi were responsible for this effect. The M. hapla suppressive effects observed in soils 7 and 9 are, to our knowledge, the first report of nematode suppressive soils from New Zealand. Certainly there has been no reported in situ association between Orbiliomycetes fungi and Meloidogyne in this country, and few worldwide (Singh et al., 2012). Orbiliomycetes fungi are a monophyletic group which include the genera Arthrobotrys, Drechslerella, and Dactylellina (Li et al., 2005). The use of culture independent next generation sequencing in this study has enabled the relationship between these fungi and a damaging plant-feeding pest to be revealed much more readily than would have been possible with culturedependant techniques.

Although, many studies have tried to isolate and utilize nematode-trapping fungi as biocontrol agents for plant-feeding nematodes, they have yet to be utilized commercially (Degenkolb and Vilcinskas, 2016). This may be because the fungi that have thus far been worked with have been selected mainly on their ability to be readily cultured which is clearly an important determinant for any potential marketable biocontrol agent. However, because these fungi are often facultative parasites such an approach may overlook those fungi that are actually reacting to the nematodes of interest, and this is an area where next generation sequencing, as shown in this study, can be a useful guide to selection of potential biocontrol agents for specific nematodes. Additionally, the results presented here support the need for future work directed at the use of Orbiliomycetes as bioindicators for nematode suppressive soils. Such bioindicators could be used to inform the decision making process of land managers contemplating actions which could disrupt existing biocontrol mechanisms (e.g., soil cultivation). As mentioned earlier a substantial comparison of the high resolution microbial communities will form the basis of a separate paper.

For soil 7 irradiation removed the nematode-suppressive effect. Although addition of M. hapla to pots of this soil did not significantly increase root galling in either experiment it did significantly increase root rotting and this increase was associated with significantly reduced root length. It is possible the invasion of added M. hapla into roots created entry points for disease organisms. Once microbes were eliminated by irradiation a significant increase in galling was observed, likely due to elimination of Orbiliomycetes fungi but this was not associated with a decrease in root length. It is possible the impact of eliminating root pathogens was greater than that of the relatively

small amount of galling caused by nematodes. White clover is a very good host for the resident M. trifoliophila in soil 3 (Mercer and Miller, 1997), as illustrated in this case by the relatively large amount of galling observed on plant roots from the control treatment. The M. fallax observed in soil 4 prior to sowing is also hosted by white clover (Rohan et al., 2016) but in this case appears to have been present in too few numbers initially to be able to establish a population causing noticeable galling in the control treatment, as was also the case for the putative M. trifoliophila in soil 2.

Along with the resident and added invertebrates, the microbial flora of soils can have a profound impact on plant growth and in this study positive, negative, and neutral soil microbiota impacts on T. repens were all observed. Clearly, irradiation had a considerable impact on white clover growth in soil 1, significantly increasing both root and shoot growth. It appears

#### TABLE 6 | Experiment 2: Mean number of Meloidogyne root galls and weight of Pyronota larvae at inoculation into pots (Initial) and at harvest (Final).

Astrices denote significant difference to control for nematode data and significant difference to the soil with the greatest survival rate for Pyronota.

TABLE 7 | Experiment 2: Arithmetic mean root rot score and nodules/plant.

Astrices denote significant difference to control.

pathogenic microbes in that soil were having a large impact on potential productivity with this soil having the greatest root rot scores of any of the soils. There have been few studies of the causes of root rotting in New Zealand pasture plants. The soils with the lowest proportion of rot-free plant roots were from Northland (soil 1) and Southland (soil 10), with root rot incidence likely helping to explain the poor growth of plants in soil 1. Skipp and Christensen (1983) recorded the incidence of potential root-rotting fungi on white clover roots during a survey of New Zealand pastures and found that Codinea fertilis predominated in root pieces from two soils in Northland (close to soil 1 in the current study) and that Bimuria novae-zelandiae predominated in soils of Southland (close to the current soil 10). Wakelin et al. (2016) found a significant negative association between a Pythium clade and T. repens shoot growth. Whether, these are the causative agents of the root rotting observed in the current study will be clarified by the next generation sequencing results to be carried out on white clover endosphere samples which will be reported in a future paper.

Other than soil 1 irradiation either significantly reduced (soils 4 and 9) or had no significant effect (soils 7 and 10) on shoot growth for the control treatments. It appears these effects are due to changes in the microbial flora such that in soils 4 and 9 elimination of predominant beneficial microbes reduced plant growth whereas irradiation impacts on both beneficial and deleterious microbes in soils 7 and 10 resulted in no change in plant growth. Changes in soil nutrient levels post-irradiation are not able to explain the plant growth effect observed because they are not consistently associated with either increases or decreases in plant growth. At the rates of irradiation used here (ca. 40 kGy) Buchan et al. (2012) observed a decrease in NO3- N (from ca. 4 to 0 µg N/g dry soil) and an increase of NH4-N (from 1 to 8–12 µg) compared to untreated soil, probably due to the elimination of nitrifying bacteria. They also observed that elimination of microbes by irradiation increased pools of labile carbon. It had been expected that these changes would occur in the soils used here and that these would affect plant growth consistently across all soils (NH4 driving either an increase or decrease in T. repens growth depending on its concentration in

soil (Britto and Kronzucker, 2002). However, this did not occur which suggests that any effects that occurred due to changes in nutrient status were, at least to some extent, overridden by changes in microbial communities and their effect (positive or negative) on plant growth. The soil dilution method used in Experiment 2 would have minimized differences in nutrients due to irradiation, compared to non-irradiated controls.

Wakelin et al. (2016) used microwaving to sterilize a range of New Zealand soils and found that of 10 soils they tested all but one gave a significant positive response in T. repens growth in sterilized soil. Over all soils they found that control soil produced 28.6% more T. repens shoot weight than sterile soils. Included in their soil set was soil 9 which, with their sterilization technique, showed a T. repens growth increase of ca. 25% in response to soil sterilization. This contrasts with the >200% reduction in growth in irradiated compared to untreated from the current study. There are likely a range of reasons for this difference between studies including temporal (the soils were sampled in different years), spatial (diseases, for instance, can be patchily distributed) and the severity of the treatment imposed. In the current study virtually all microbes were eliminated while the Wakelin et al. (2016) method was less severe and may have retained some beneficial microbes which then minimized the negative effects of the sterilization treatment. Root length in all soils were greater in Experiment 2 than Experiment 1, with many root systems reaching the bounds of the pot depth (120 mm). Dilution of the field soil with pumice appears, then, to have had one of the desired effects of reducing the loading, and therefore impact, of root pathogens or other deleterious microbes.

Although, survival of C. zealandica in soil 10 was very low this was not reflected in a significantly lower weight gain of those grubs that did survive, suggesting that quality of the food resource was not the cause of the grub's demise. Indeed, there was a significant reduction in root length of plants growing in soil 10 with grubs which indicates the grubs survived sufficiently long to eat a large proportion of roots but subsequently succumbed. Similarly, there was lower survival of grubs in soil 4 than in many other soils but in this case there was no significant reduction in root length, suggesting grubs may have succumbed more rapidly than in soil 10. Grubs in soil 4 were significantly smaller than those in soil 10 at inoculation to pots which may help explain why they succumbed more rapidly to whatever was the cause of death of these grubs. There was no correlation between C. zealandica and any of the fungi sequenced (data not shown) so it is likely these effects are due to other microbes such as the bacteria Serratia entomophila which is known to cause disease in these insects (Hurst et al., 2000). There was no similar effect of these two soils on Pyronota sp. survival in the second trial, suggesting the host specificity of whatever microbe was responsible for C. zealandica deaths did not extend to Pyronota. Pyronota sp. had no significant impact on either roots or shoots in any of the non-irradiated soils but did significantly decrease shoot growth in soils 1, 4, and 7 post-irradiation suggesting that any control exerted within control soils was eliminated by irradiation.

This study has clearly shown the effects of soil biology on plant growth can be profound. The in situ interactions between soil microflora and fauna that occur in the rhizosphere deserve closer attention, especially in New Zealand soils where they are little studied. Insights that can be gained from such studies will form the basis for developments in biocontrol, bioindicators and the agronomic practices that support beneficial interactions.

#### AUTHOR CONTRIBUTIONS

fpls-07-01946 December 22, 2016 Time: 17:9 # 14

NB, DF, and RDJ conceived the project and gained grant funding. NB, KA, RJ, RDJ, YM, GB, AP, and DF had substantial contribution to the acquisition and interpretation of data. VC, CC, and PM had substantial contribution to data analysis and interpretation. All authors had substantial contributions to the drafting, revising, final approval, and agreement on the manuscript.

#### FUNDING

This study was funded from New Zealand Ministry of Business, Innovation and Employment contracts C10X1309 (Smart Ideas Fund) and LINX0804.

### REFERENCES

#### ACKNOWLEDGMENTS

We gratefully thank Steve Wakelin for his advice on site selection, rhizobia and his technical assistance, along with Kelly Styles and Libby Mehrtens. We also thank Chelve Rohan and Lee Aalders for supply of M. hapla from culture and Craig Anderson and Andrew Griffiths for supplying near-isogenic seed. Ruy Jaurequi provided valuable assistance to the analysis of the Hi-Seq data. Pauline Hunt's abilities in creating **Figures 1** and **2** are gratefully acknowledged. This study was made possible by interested farmers allowing us to collect soil, C. zealandica and Pyronota and by their helpful discussion on the management of their soils. We thank the two reviewers for their helpful suggestions on the manuscript.

**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2016 Bell, Adam, Jones, Johnson, Mtandavari, Burch, Cave, Cameron, Maclean, Popay and Fleetwood. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

fpls-07-01946 December 22, 2016 Time: 17:9 # 15

# Grasslands, Invertebrates, and Precipitation: A Review of the Effects of Climate Change

Kirk L. Barnett\* and Sarah L. Facey

Hawkesbury Institute for the Environment, Western Sydney University, Penrith, NSW, Australia

Invertebrates are the main components of faunal diversity in grasslands, playing substantial roles in ecosystem processes including nutrient cycling and pollination. Grassland invertebrate communities are heavily dependent on the plant diversity and production within a given system. Climate change models predict alterations in precipitation patterns, both in terms of the amount of total inputs and the frequency, seasonality and intensity with which these inputs occur, which will impact grassland productivity. Given the ecological, economic and biodiversity value of grasslands, and their importance globally as areas of carbon storage and agricultural development, it is in our interest to understand how predicted alterations in precipitation patterns will affect grasslands and the invertebrate communities they contain. Here, we review the findings from manipulative and observational studies which have examined invertebrate responses to altered rainfall, with a particular focus on large-scale field experiments employing precipitation manipulations. Given the tight associations between invertebrate communities and their underlying plant communities, invertebrate responses to altered precipitation generally mirror those of the plants in the system. However, there is evidence that species responses to future precipitation changes will be idiosyncratic and context dependent across trophic levels, challenging our ability to make reliable predictions about how grassland communities will respond to future climatic changes, without further investigation. Thus, moving forward, we recommend increased consideration of invertebrate communities in current and future rainfall manipulation platforms, as well as the adoption of new technologies to aid such studies.

Keywords: climate change, drought, insects, invertebrate communities, irrigation, rain-exclusion shelters, rainfall

### INTRODUCTION

Grasses cover more of the earth's surface than any other vegetation type (Tscharntke and Greiler, 1995; Wang and Fang, 2009) and are often of high economic, ecological and biodiversity value, providing forage for livestock and high levels of carbon storage (Lee et al., 2014; Lenhart et al., 2015). Many grasslands exist in seasonal states of water limitation, and are highly responsive to changes in water availability in terms of biomass and composition (Knapp et al., 2002; Fry et al., 2014; Lenhart et al., 2015). Climate models predict changes in precipitation patterns, in terms of

#### Edited by:

Michael Rostás, Lincoln University, New Zealand

#### Reviewed by:

Ruth Nicola Wade, University of York, UK Kimberly La Pierre, University of California, Berkeley, USA Anne-Violette Lavoir, University of Nice Sophia Antipolis, France

> \*Correspondence: Kirk L. Barnett<EMAIL_ADDRESS>
#### Specialty section:

This article was submitted to Agroecology and Land Use Systems, a section of the journal Frontiers in Plant Science

> Received: 16 March 2016 Accepted: 26 July 2016 Published: 05 August 2016

#### Citation:

Barnett KL and Facey SL (2016) Grasslands, Invertebrates, and Precipitation: A Review of the Effects of Climate Change. Front. Plant Sci. 7:1196. doi: 10.3389/fpls.2016.01196

the total amount and the frequency and intensity of rainfall events (IPCC, 2013), therefore leading to alterations in grassland plant composition and primary production.

Invertebrates are the most diverse and abundant constituent of terrestrial ecosystem fauna (Stork et al., 2015). Often overlooked, these organisms contribute to structuring grassland communities, through activities such as pollination and nutrient cycling (Whiles and Charlton, 2006) and contribute to shaping grasslands through top-down processes. For instance, herbivores can modify plant species richness by altering competitive dynamics between plant species (Olff and Ritchie, 1998). Likewise, plant community composition plays a bottom-up role in structuring arthropod communities (Perner et al., 2005; Hertzog et al., 2016), as do abiotic factors like temperature and water availability (e.g., Bale et al., 2002). Thus, both grassland plant and invertebrate communities can be directly impacted by alterations in climate. In addition, precipitation changes can have indirect impacts on both plants and invertebrates as the interactions occurring between the two communities are also climate-sensitive; the effect of herbivory on plant diversity varies across precipitation gradients, for instance (Olff and Ritchie, 1998).

It is in our interest to understand how climate changedriven alterations in precipitation will affect valuable grassland systems and the invertebrate communities they both support and rely on. Over the past 20 years, multiple experiments and observational studies have addressed the responses of grasslands to changes in precipitation, with a subset of these also examining invertebrate responses across a range of precipitation scenarios and spatial scales (summarized in **Table 1**). To our knowledge, there has been no synthesis of the relevant literature examining insect responses to precipitation changes, making a review of these studies timely. In this mini-review, we look at the effects of altered precipitation patterns – including reductions and increases in average rainfall, and changes in rainfall frequency – on grassland invertebrates and the plant communities they inhabit. We focus on findings from field-based/observational studies and precipitation manipulation experiments conducted in grasslands, including steppe and savannah habitats.

#### INVERTEBRATE RESPONSES TO PRECIPITATION CHANGE

#### Direct Impacts

In general, terrestrial arthropods are sensitive to changes in moisture, given their high surface-to-volume-ratio (Kimura et al., 1985). Under reduced rainfall, most aboveground arthropods avoid desiccation behaviorally by migrating, hiding in the soil, or, in a few cases, building a shelter (Willmer, 1982; Zalucki et al., 2002; Berridge, 2012). Structurally speaking, soft-bodied arthropods (isopods and myriapods) lack the waxy cuticle found in arachnids and insects that prevents or reduces evaporation (Berridge, 2012). This, in combination with differences in excretion-related water losses (Horne, 1968), suggests that softbodied arthropods will be more vulnerable to reductions in water availability, and, in some cases, to increases (Sylvain et al., 2014). Thus, changes in rainfall could be expected to affect hard and soft-bodied groups differently, resulting in shifts in the arthropod community.

On the other end of the spectrum, average increases in rainfall may negatively impact arthropods by disrupting flight, reducing foraging efficiency and increasing migration times (Peng et al., 1992; Drake, 1994; Kasper et al., 2008). Some arthropods can vary their behavior to combat the effects of extreme rainfall events and flooding by shelter-seeking and utilizing submersion tolerance strategies (Lambeets et al., 2008). The effects of increased rainfall on arthropods are also dependent on invertebrate morphology and are group-specific, with larger winged insects like Lepidopterans having a much higher degree of 'unwettability' (i.e., requiring greater volumes of water to become wet) than smaller winged insects (Wagner et al., 1996). Altered rainfall frequency can be positive or negative for invertebrates depending on the size of the event (Nielsen and Ball, 2015), but on the whole is expected to impact more rain-sensitive orders like Lepidoptera (Palmer, 2010).

Arthropods that spend all or some of their life stages belowground have evolved behaviors to manage water stress in times of drought and flood (Verhoef and Witteveen, 1980). Under reduced water availability, most soil invertebrates combat fluctuating moisture by relocating to places that are more favorable within the soil-matrix. Such movement, however, is dependent on suitable soil moisture and texture (Lees, 1943; Brust and House, 1990). Some invertebrates build earthen chambers, controlling the microclimate, similar to shelterbuilders aboveground (Haile, 2001; Barnett and Johnson, 2013). Prolonged drought conditions may favor those species capable of such behaviors. Similarly, larvae with morphological adaptations to flooding may fare better in areas predicted to experience increases in rainfall. Species that have evolved in flood-prone environments in particular, like the cranberry root grub, with water-repellent hairs along its body that can trap air (King et al., 1990; Villani et al., 1999), may stand to have competitive advantages over flood-intolerant species. Thus, invertebrates both above and belowground have evolved a range of behavioral and morphological adaptations to alterations in water availability. Differences in the use of such strategies between species and functional groups will likely lead to alterations in invertebrate community composition.

### Indirect (Plant-Mediated) Impacts

Invertebrate Responses to Plant Quantity and Quality There is strong evidence in the literature for resource quantitydriven changes in invertebrate herbivore populations under altered precipitation regimes. Reduced rainfall results in reduced plant biomass, aboveground net primary productivity (ANPP), forage quality and cover, with increases in canopy light penetration and root:shoot ratios (Fay et al., 2003; Wu et al., 2011), leaving less plant biomass to support herbivores; however there is strong evidence that this response is ecosystem dependent (Byrne et al., 2013). Accordingly, declines have been reported – across various ecotypes – in the abundances of Orthoptera (Kemp and Cigliano, 1994); earthworms and scarabs (Davis et al., 2006;

TABLE 1 | A summary of the major precipitation manipulation experimental platforms assessing both plant and invertebrate responses to altered rainfall regimes.

Climate classifications follow the Global Agro-Ecological Zones set out by the Food and Agriculture Organization (gaez.fao.org). 1Balcones Canyonlands National Wildlife Refuge (Marble Falls, TX, USA). 2Oldfield Community Climate and Atmospheric Manipulation (Oak Ridge, TN, USA). 3Drought and Root herbivore Impacts on Grassland (Richmond, NSW, Australia).

Mariotte et al., 2016); belowground herbivores (Staley et al., 2007); and across herbivore communities generally (Lee et al., 2014). Plant quality changes could also play a role in these declines. In a feeding experiment, army worm larvae reared on droughted Yorkshire fog grass took longer to develop and had higher mortality rates than those feeding on non-droughted grass, due to lower soluble protein content (Walter et al., 2012). While some trends can be identified in the responses of invertebrates to reductions in rainfall, there is a high degree of variation between species. For instance, gastropod species in a UK study had highly individual responses to changes in water availability, with some benefitting from drought and others instead occurring in greater abundance under supplemented rainfall (Sternberg, 2000).

Increases in average precipitation (to a degree – the negative effects of flooding in grasslands have been reviewed elsewhere – see Plum (2005)) may result in benefits to invertebrate herbivores, except in cases where increased moisture facilitates pathogens and disease (Grant and Villani, 2003). On the whole, increases in precipitation lead to increases in ANPP (Zaller and Arnone, 1999; Byrne et al., 2013). Consequently, studies have reported improved grasshopper nymph survival (Guo et al., 2009) and increased abundance and richness of grasshoppers (Lenhart et al., 2015). However, in contrast to the increases in grasshopper abundance reported in Lenhart et al. (2015) two other studies reported reductions in grasshopper survival under similar increased rainfall treatments (Barton et al., 2009; Guo et al., 2009).

Hence, a recurrent theme in the literature is that the responses of herbivorous invertebrates to altered precipitation will likely be idiosyncratic in nature, making it difficult to make generalized predictions about the directions of their responses under different scenarios (González-Megías and Menéndez, 2012; Nielsen and Ball, 2015). The responses of herbivores to both reduced and increased water availability are likely to be linked to the responses of their individual food-plant(s), as well as the invertebrate specie's own physiological precipitation optimum (Schowalter et al., 1999).

#### Invertebrate Responses to Plant Community Composition

The responses of a grassland plant community to alterations in rainfall depend on the type of grassland (i.e., average water state – mesic, xeric etc.; Heisler-White et al., 2009), as well as the plant functional types (PFTs) that dominate the system (Collins et al., 2012; Andrey et al., 2014). For example, under altered rainfall frequency, with longer dry periods between more intense rainfall events, mesic grasslands generally experience a decrease in ANPP, whereas xeric grasslands show an increase (Fay et al., 2002, 2003; Heisler-White et al., 2009). In terms of PFTs, grasslands dominated by C4 grasses tend not to show stimulations in ANPP under increased rainfall, perhaps because they are likely to be less water limited than their C3 counterparts (Niu et al., 2008; Wu et al., 2011; Wilcox et al., 2015). Indeed, there is evidence that herbivorous insects consume relatively more C4 plants in years with reduced rainfall frequencies (Warne et al., 2010), possibly due to improved quality or increased quantities of these plants under such scenarios. Thus, we could expect that reorganizations occurring at the plant community level in response to altered rainfall regimes will have consequences for herbivores, particularly for specialist feeders which may be reliant on the presence of just one or two plant species.

So far, experimental evidence directly linking precipitationmediated changes in plant diversity to changes in the herbivore community is lacking. However, a 5-year field experiment by Suttle et al. (2007) showed that whilst increased summer rainfall enhanced plant biomass, increased dominance and reduced grassland plant species richness had eventual negative consequences for the invertebrate community. Specifically, herbivore and consumer abundance declined and the invertebrate food web became simplified, potentially pointing to the loss of more specialized herbivores. This study demonstrates the importance of longer-term studies in detecting plant community shifts as opposed to more immediate biomass responses. Furthermore, Wilcox et al. (2016) recently showed that short-term plant community shifts in response to increased water availability may be misleading when considering shifts over a decadal time scale.

#### Secondary Consumer Responses to Altered Rainfall

Alterations occurring in the abundance and diversity of primary consumers can flow up through the food chain to affect populations of predators and parasitoids (Suttle et al., 2007; Lee et al., 2014), which may themselves be more sensitive to climatic change (Voigt et al., 2003). Buchholz et al. (2013) found reductions in semi-dry grassland spider and carabid diversity and abundance under water-limited conditions. However, at a similar site 3 years earlier, the same authors found no change in spider species richness, composition or abundance under precipitation manipulation (Buchholz et al., 2010). Similarly, in a Chinese steppe, reduced rainfall caused declines in herbivore abundance with no corresponding decline in secondary consumers (Zhu et al., 2014). Clearly, as with herbivores, there will be differences in the individual responses of higher trophic levels to changes in precipitation patterns.

#### Precipitation-Sensitive Species Interactions

The idiosyncratic nature of invertebrate responses can be at least partially explained by complex precipitation-driven alterations in the interactions occurring between species within the system. The handful of studies which have tackled pairwise species interactions under precipitation manipulations have found complex, unpredictable responses with the potential to affect multiple trophic levels. For instance, spatially separated above- and belowground herbivores may influence each other through their effects on the shared host plant, such as by altering secondary chemistry (Johnson et al., 2012). Staley et al. (2007) found that enhanced summer rainfall increased the abundance of leaf mining moths on wild basil, but not when root herbivores were present. The negative effects of root herbivores on leaf miner pupal size reduced the parasitism rates of moths above ground, indicating the potential for precipitation-altered species interactions to have knock-on consequences for higher trophic levels.

In a separate study, detritivorous tenebrionid beetles belowground had negative effects on the abundances of generalist sap sucking and chewing herbivores when summer precipitation was supplemented, similar to the findings of Staley et al. (2007) (González-Megías and Menéndez, 2012). In contrast, the presence of belowground herbivores had positive impacts on aboveground leaf-mining flies, restoring their pupal weight and development time to ambient levels, when reared under drought conditions on milk-thistle (Staley et al., 2008). Taken together, these studies suggest that belowground organisms could serve to moderate the effects of reduced or increased water availability on aboveground herbivores, which may otherwise be expected to decrease or increase in abundance, respectively, in response to such rainfall regimes. As with the responses of individual species, the directions of the responses of the interactions between multiple species may also prove to be species- and system-specific. Further work is needed in the area to determine whether or not generalizations can be made, and to determine whether other interactions such as competition may also be affected by alterations in precipitation.

#### INVERTEBRATE-MEDIATED FEEDBACKS ON PLANT COMMUNITIES

At the ecosystem scale, invertebrate herbivores generally exert weak control over grassland plant communities (Whiles and Charlton, 2006; Coupe et al., 2009), though their impacts on plant species richness, for instance, may be stronger during herbivore outbreaks (Olff and Ritchie, 1998). Altered precipitation has the capacity to change the relative strength of the interactions occurring between grassland plant and invertebrate communities, by altering the abundance and composition of species within the system. In a Canadian grassland, invertebrates caused short-term reductions in plant cover, increases in root mortality and altered plant composition compared with pesticide treated plots (Coupe et al., 2009). The effects of the invertebrate community only became apparent under naturally occurring drought conditions. This suggests that invertebrate herbivores may exacerbate the negative effects of drought for grassland plants, and that grasslands may become more vulnerable to herbivores under drought.

FIGURE 1 | A summary diagram of the general trends expected or found in the literature (theoretical, experimental, and observational studies) for plant, primary consumers (herbivores, detritivores etc.) and secondary consumers (predators and parasitoids), in response to altered precipitation regimes. Arrows: N indicates increases in the given metric, Hrepresents declines and NH denotes more varied results. References are given by the numbers on the diagram: (1) Barnett and Johnson (2013), (2) Buchholz et al. (2013), (3) Coupe et al. (2009), (4) Davis et al. (2006), (5) Fay et al. (2002), (6) Fay et al. (2003), (7) Guo et al. (2009), (8) Heisler-White et al. (2009), (9) Kasper et al. (2008), (10) Lambeets et al. (2008), (11) Lee et al. (2014), (12) Lenhart et al. (2015), (13) Masters et al. (1998), (14) Palmer (2010), (15) Staley et al. (2007), (16) Staley et al. (2008), (17) Suttle et al. (2007), (18) Walter et al. (2012), (19) Warne et al. (2010), (20) Zhu et al. (2014).

In an American temperate old-field study, experimentally increased rainfall caused declines in grasshopper abundance, which translated into a 15% reduction in grasshopper-inflicted plant damage for every 1 cm of increase in mean monthly precipitation (Barton et al., 2009). Conversely, in a limestone grassland, the plant community sustained an increase in biomass under supplemented rainfall scenarios, despite a significant increase in the abundance of Auchenorrhyncha herbivores (leaf, plant, and frog hoppers; Masters et al., 1998). Assuming that this greater abundance of insects inflicted comparable levels of damage on a per capita basis as those in ambient plots, this would suggest that grassland plants may be able to maintain increased growth despite higher levels of herbivory under increased rainfall scenarios. These two studies demonstrate that the strength of indirect, invertebrate community-mediated effects of altered precipitation on grasslands will depend on the identities of both the plant community and invertebrate species involved.

### CONCLUSION AND FUTURE DIRECTIONS

Depending on the underlying water-status of the ecosystem, alterations in rainfall may have generally negative direct and indirect consequences for invertebrates (summarized in **Figure 1**). Changes in precipitation will also have the potential to cause impacts spanning multiple trophic levels, moderating the outcomes of species interactions. Reductions in rainfall may exacerbate the negative effects of herbivores for the plant communities they inhabit, though other players in the system might alter this response (e.g., Staley et al., 2008). In order to better understand how grassland invertebrates – and the important ecological processes they underpin – will respond to altered precipitation, we highlight the following four areas for future research:

realistic predictions about how grassland communities will respond to future changes (Beier et al., 2012). Such studies are needed in order to capture changes in the direction of responses over time and lags in the manifestation of responses – particularly given the potential for short-term studies to have misleading results compared with those over longer timescales (Suttle et al., 2007; Wilcox et al., 2016).

Such studies will not be without logistical difficulty, though future developments in technology will help to ease this, including improvements in long-term, sensor-based data gathering. Continued development of DNA-based methods like metabarcoding will assist community-level studies by reducing time-consuming work and taxonomic expertise (Cristescu, 2014). Results from studies like those suggested above will provide critical information about grassland community responses for use in theoretical modeling approaches such as structural equation modeling, enabling the testing of theories at scales not yet possible experimentally. Such experimental and modeling approaches, carried out with broader geographical and precipitation-scenario representation, will be necessary in order for us to form more accurate predictions about the fate of ecologically important grassland ecosystems under climate change.

### AUTHOR CONTRIBUTIONS

KB and SF contributed equally in drafting, writing, and approving the final manuscript.

### ACKNOWLEDGMENT

This mini-review was produced as part of a series of articles from the Ninth Australasian Congress of Grassland Invertebrate Ecology, with sponsorship from the Australasian Congress of Grassland Invertebrate Ecology.

### REFERENCES

fpls-07-01196 August 3, 2016 Time: 13:40 # 7

**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2016 Barnett and Facey. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# The Importance of Testing Multiple Environmental Factors in Legume–Insect Research: Replication, Reviewers, and Rebuttal

Scott N. Johnson\*, Andrew N. Gherlenda, Adam Frew and James M. W. Ryalls

Hawkesbury Institute for the Environment, Western Sydney University, Penrith, NSW, Australia

Keywords: atmospheric change, biological nitrogen fixation, climate change, insect–plant interactions, legumes, pastures

## THE CASE FOR TESTING MULTIPLE ENVIRONMENTAL FACTORS

Investigating the impacts of predicted changes in our atmosphere and climate change on insect– plant interactions is a widely pursued area of research. To date, the majority of experimental studies have tested the impacts of single environmental factors on insect–plant interactions, but meta-analyses have clearly illustrated the importance of investigating multiple factors in tandem (Zvereva and Kozlov, 2006; Robinson et al., 2012). In particular, environmental change factors often interact with each other which can either strengthen or mitigate the effects of environmental factors acting alone (Robinson et al., 2012). For example, the positive effects of elevated atmospheric carbon dioxide concentrations (e[CO2]) on plant growth are stronger under high nitrogen (N) conditions compared to low N conditions (+32 and +19%, respectively; Robinson et al., 2012). Likewise, from the limited number of studies available, Robinson et al. (2012) showed that e[CO2] had different impacts on plant nitrogen, plant biomass, and secondary metabolites under elevated air temperature (eT) conditions. This does not invalidate single factor studies, of which we have published numerous examples, but this is an important consideration for making realistic predictions about how plants and insects will respond to future climates (Facey et al., 2014).

#### LEGUME–INSECT INTERACTIONS

A key feature of legumes is their capacity for biological nitrogen fixation (BNF), which they accomplish via symbiotic relationships with soil bacteria which associate with the plant in discrete root nodules. Given that insect herbivores are frequently nitrogen limited (Mattson, 1980), concentrations of N in legumes derived from BNF are likely to be crucial determinants of plant– herbivore interactions. Legumes differ markedly from non-legume plants in their responses to environmental change because BNF is often significantly affected (Robinson et al., 2012). Moreover, e[CO2] and eT appear to have contrasting effects on BNF; e[CO2] tends to promote BNF via several mechanisms (Soussana and Hartwig, 1996), including larger numbers of N2-fixing symbiotic bacteria in the rhizosphere (Schortemeyer et al., 1996), increased nodulation (Ryle and Powell, 1992) and enhanced nitrogenase activity (Norby, 1987). In contrast, eT tends to have an inhibitory effect on BNF because of the low tolerance of N2-fixing bacteria to higher temperatures (Zahran, 1999; Whittington et al., 2013). These generalizations are, of course, contingent on nutrient availability in the soil (e.g., Edwards et al., 2006).

Given this, one might assume that e[CO2] and eT might have contrasting impacts on insect herbivores of legumes since they affect nitrogen concentrations in the plant

#### *Edited by:*

Michael Rostás, Lincoln University, New Zealand

*Reviewed by:* Federico Tomasetto, AgResearch Ltd., New Zealand

*\*Correspondence:* Scott N. Johnson<EMAIL_ADDRESS>
#### *Specialty section:*

This article was submitted to Agroecology and Land Use Systems, a section of the journal Frontiers in Plant Science

> *Received:* 15 March 2016 *Accepted:* 26 March 2016 *Published:* 22 April 2016

#### *Citation:*

Johnson SN, Gherlenda AN, Frew A and Ryalls JMW (2016) The Importance of Testing Multiple Environmental Factors in Legume–Insect Research: Replication, Reviewers, and Rebuttal. Front. Plant Sci. 7:489. doi: 10.3389/fpls.2016.00489 tissues in a divergent manner. This seems to be the case, with e[CO2] either having no adverse effects (e.g., Karowe and Migliaccio, 2011) or, more often, a beneficial impact on herbivore performance (e.g., Johnson and McNicol, 2010), particularly for aphids (Guo et al., 2013, 2014; Johnson et al., 2014). However, our recent work with lucerne (Medicago sativa) has shown that the positive impacts of e[CO2] on pea aphids (Acyrthosiphon pisum) were negated under eT because eT caused decreases in nodulation and amino acid concentrations in the foliage (Ryalls et al., 2013, 2015). Testing multiple environmental factors, including soil nutrients, therefore seems to be particularly relevant for investigations into how legume herbivores will respond to atmospheric and climate change research.

### THE CHALLENGES: REPLICATION AND REVIEWERS

Why are there so few multi-factorial experiments in climate change research? Put simply, constraints on replication are the biggest obstacles faced by investigators. Pseudoreplication (a term first coined in Hurlbert, 1984) is particularly common in climate change research (Newman et al., 2011). For example, 49 of the 110 climate change studies reviewed by Wernberg et al. (2012) had pseudoreplication issues. This usually arises because when environmental factors are applied to controlled chambers, glasshouses, or FACE (Free Air CO2 Enrichment) rings, the unit of replication for those treatments is the chamber, greenhouse, or ring, respectively (Lindroth and Raffa, in press). Subunits (e.g., individual plants) are not independently subjected to the treatment, and therefore not true replicates. As a result, statistical tests are based on artificially high degrees of freedom, resulting in a larger F statistic, potentially leading to type I errors (i.e., false positives; Lindroth and Raffa, in press). For this reason, many reviewers for scientific journals automatically reject manuscripts if any part of an experiment is pseudoreplicated without necessarily considering whether the biological conclusions of the study are really compromised by pseudoreplication (Davies and Gray, 2015). This is possibly an overzealous interpretation of the case by Hurlbert (1984), the authority on the subject, who states that "there should be no automatic rejection of [such] experiments" (Hurlbert, 2004). In a recent and comprehensive article, Davies and Gray argue convincingly that reviewers erroneously and dogmatically reject papers that have pseudoreplication issues which is slowing the pace of ecological research. While Davies and Gray (2015) focussed on non-manipulative experiments in natural systems, many of the points were germane to multi-factorial climate change research. In particular, many contemporary statistical tests, such as nested designs and random/mixed effect models, account for the lack of independence between pseudoreplicates so may help in some cases (Chaves, 2010; Leather et al., 2014; Davies and Gray, 2015). Of course, such statistical approaches could only help where a treatment combination was repeated in more than one chamber, glasshouse, or FACE ring.

### COMPARING EXPERIMENTAL APPROACHES—POTENTIAL FOR REBUTTAL?

How do researchers attempt to overcome the pseudoreplication problem experimentally? The simplest way is to avoid it altogether by fully replicating environmental treatments. However, using even the bare minimum of replicates (e.g., N = 4) would require 16 separate chambers, glasshouses, or rings for an e[CO2] × eT experiment. Many researchers cannot readily access this number of identical facilities or monopolize them for that matter. Repeating the experiment several times and using experimental run as the source of replication is another approach (e.g., Johnson et al., 2011), but this can be logistically demanding in time and cost. Even when fully replicated, the degrees of freedom in these studies are often so low that they are susceptible to type II errors, whereby "real responses" are not statistically detected (e.g., the "false negative").