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Linking Soil Organisms Within Food Webs to Ecosystem Functioning and Environmental Change Jeff R. Powell* Contents 308 309

1. Introduction 2. Overview of the Soil Food Web 3. Impacts on Soil Food Web Dynamics Associated with Human Activities 3.1. Biodiversity loss 3.2. Invasive species 3.3. Climate change 3.4. GM crops 4. Alternative Approaches: Seeing the Forest for the Trees 4.1. Nematode faunal analysis 4.2. Modeling food web dynamics 5. Missing and Ambiguous Components of Current Soil Food Web Knowledge 5.1. Resolution 5.2. Integration of the detritivore and herbivore food webs 5.3. Role of technology in resolving soil food webs 6. Summary and Conclusions Acknowledgments References

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Agronomists, ecologists, ecosystem scientists, and various other researchers are recognizing the value of studying responses of soil biota to environmental perturbations because of their functional roles in ecosystem processes and varying sensitivities to environmental perturbations. In this chapter, I provide a descriptive overview of trophic interactions in soil and selected examples of current research on soil biotic responses to human-associated disturbance [biodiversity loss, invasive species, climate change, and genetically modified (GM) crops]. In many cases, researchers generally use population estimates of

*Department of Integrative Biology, University of Guelph, Guelph, Ontario, Canada N1G 2W1 Advances in Agronomy, Volume 96 ISSN 0065-2113, DOI: 10.1016/S0065-2113(07)96007-1

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2007 Elsevier Inc. All rights reserved.

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functional groups as a surrogate for food web interactions and, from these, infer that responses could cascade through food webs to impact ecosystem functioning. I then review alternative approaches to monitoring soil food web dynamics, approaches that focus on estimating the emergent properties of food webs themselves. Because these emergent properties are directly linked to nutrient cycling and energy flow, they should provide a more robust indication of ecosystem functioning in response to environmental perturbations. The first, nematode faunal analysis, is an empirical approach that utilizes a subset of soil organisms representing multiple functional groups and incorporates information regarding organism life history to estimate emergent properties of the existing soil food web, such as productivity and sensitivity to disturbance. The second is a modeling approach that attempts to predict how localized changes within a food web will influence the overall stability and productivity of the food web. Finally, I address some shortcomings in our current understanding of soil food web structure and resolution, and promising avenues for addressing these shortcomings.

1. Introduction The study of soil biodiversity arose primarily out of research necessitated by the impacts of agricultural pests, with most research focusing on plant–pathogen interactions and the potential for biological control of herbivores (Baker and Cook, 1974). Researchers placed emphasis primarily on promoting plant health, isolating and culturing microorganisms, taxonomy and classification, and characterizing microbial succession (Baker and Cook, 1974; Garrett, 1981; Wall et al., 2005). The study of trophic interactions in soil emerged as a discipline in the 1970s when research revealed the important roles played by trophic interactions in ecosystem processes such as nutrient cycling, litter decomposition, and energy flow (Anderson et al., 1978; Cole et al., 1978; Coleman et al., 1976, 1978a,b; Herzberg et al., 1978). This sparked a number of microcosm and field studies in the 1980s that shed light on soil food web structure, mapped the flow of energy through food webs, and quantified rates of nutrient mineralization and immobilization as influenced by trophic interactions in soil (Andre´n et al., 1990; Hunt et al., 1987; Ingham et al., 1985, 1986a,b; Petersen and Luxton, 1982). Data from a handful of field studies, conducted primarily in the late 1980s and the early 1990s, parameterize current models of soil food web dynamics; the current template for the organization of soil food webs is derived from a Georgia cropping system (Hendrix et al., 1986), a Colorado pasture (Hunt et al., 1987), a Swedish cropping system (Andre´n et al., 1990), a Dutch cropping system (de Ruiter et al., 1993), a Dutch Scots pine forest (Berg, 1987), and, most recently, an Arctic Tundra system (Doles, 2000).

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Recent and current uses of this template generally fall into three interrelated categories: (1) estimating the current and predicted responses of communities and ecosystems to environmental change, (2) the formation and revision of ecological concepts, and (3) manipulating trophic interactions to manage agricultural pests. Agronomists and ecosystem scientists are recognizing the value of studying responses of soil biota because of their functional roles and varying sensitivities to environmental perturbations. Ecologists recognize the utility of studying soil food webs due to the small spatial scales at which the interactions occur and the similarities with, and differences from, aboveground terrestrial, aquatic, and marine food webs. Studies on entomopathogenic nematodes, the parasites and predators of plant-feeding nematodes, predatory mites, and invertebrate seed predators highlight the biological control potential of trophic interactions in soil. Each category shares a common need to quantify and interpret the dynamics that are occurring in soil. However, as will be demonstrated here, the ways that soil food web dynamics are perceived and estimated are evolving. Some focus on changes in the abundance and strengths of interactions between particular taxonomic and functional groups, while others recognize that these changes can affect the emergent properties of the soil food web as a whole. I intend this chapter for readers contemplating the use of soil organisms for monitoring ecosystem responses to, and recovery from, environmental perturbations. This chapter (1) provides a descriptive overview of trophic interactions in soil, while pointing out some gaps in our current understanding of soil food webs; (2) highlights selected examples of current research estimating effects of some human activities on soil–trophic interactions; and (3) suggests alternative methods for estimating and predicting such effects. Several recent publications provide general and in-depth discussions on the roles that trophic interactions in soil, and soil biota in general, play in ecosystem functions (Adl, 2003; Bardgett, 2005a,b; Coleman et al., 2004; Paul, 2007; Wardle, 2002). A number of publications describe methodology for sampling, extraction, and enumeration of soil organisms (Burlage et al., 1998; Carter, 1993).

2. Overview of the Soil Food Web Descriptions of soil food webs are resolved at a functional level, with taxa aggregated into trophic groups (Fig. 1). This is by necessity due to the high taxonomic richness associated with most soil food webs and lack of knowledge regarding the specific feeding behavior of many of these taxa (Hunt et al., 1987). Here, I provide a general description of the current model of soil food web organization, adapted from Coleman et al. (2004), Wardle (2002), and various other sources.

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Shoots

Rootsfeeding nematodes

Collem bolans

Predaceous mites

Mites I Roots

Nematodefeeding mites

Mycorrhizae

Mites II Inorganic N

Labile substrates

Saprophytic fungi

Predaceous nematodes Fungusfeeding nematodes

Bacteria

Omni vorous nematodes

Flagellates Resistant substrates

Amebae Bacteriafeeding nematodes

Figure 1 Connectivity web indicating trophic relationships among various functional groups of soil biota and their substrates. Reprinted from Hunt and Wall (2002), with permission from Blackwell Publishing.

As in terrestrial aboveground food webs, plants are the dominant primary producers in soil. Resources enter the soil food web either via living plant material (roots and other underground structures) or via detritus (litter, dead roots, sloughed root cells, root exudates, and organic matter originally derived from flora and fauna). The distinction between living plant material and detritus is significant; abundance of each of these resources differs both spatially and temporally, which goes on to influence the abundance and activities of the organisms utilizing these resources (Bardgett et al., 2005a; De Deyn and Van der Putten, 2005). Thus, trophic interactions and energy flow in the soil food web tend to cluster into a ‘‘herbivore food web’’ and a ‘‘detritivore food web’’ (Wardle, 2002). Algae and other photosynthetic protists are additional producers occurring in soil, but these represent significant sources of productivity only where plants are absent or sparse (e.g., in the dry valleys of Antarctica; Adams et al., 2006). Symbiotic microorganisms and root-feeding invertebrates represent firstorder consumers of living plant material. Some symbionts engage in mutualistic interactions with the host plant, providing access to some limiting resource or protection from antagonists in exchange for photosynthate. For example,

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mycorrhizal fungi can increase nutrient uptake for most plant species, and rhizobial bacteria fix atmospheric nitrogen for leguminous plant species. Other symbionts extract photosynthate to the detriment of the plant host. These parasitic symbionts include a diverse assemblage of endophytic bacterial, fungal, and nematode species. Several invertebrate species graze on plant roots, including a variety of nematodes and arthropods. Nematodes, as a group, exhibit highly variable feeding strategies, ranging from sedentary endoparasitism to migratory endoparasitism to ectoparasites (Yeates et al., 1993). Second-order consumers in the herbivore food web are spatially and temporally distributed based on their feeding behaviors. Predators are active in the rhizosphere and bulk soil, where they encounter herbivores in search of food (consumed by, e.g., nematode-trapping fungi, predatory nematodes, collembolans, and mites) and the external hyphae of symbiotic fungi (consumed by, e.g., fungal-feeding nematodes and collembolans). A variety of parasites and pathogens are not only active in the rhizosphere and bulk soil (e.g., Bacillus spp., Pasteuria spp.) but also encounter herbivores at the feeding site (e.g., various fungal parasites of nematode eggs). The detritivore food web is active in the rhizosphere and extends into the soil where litter and organic matter are present. Saprotrophic bacteria and fungi represent first-order consumers of detritus. Some invertebrates (e.g., collembolans, enchytraeids) also feed directly on detritus and make resources available to other saprotrophs. For instance, the size of litter and structural barriers within it may prevent bacteria and fungi from accessing the nutrients contained within; these barriers are removed following comminution and digestion of the litter. Invertebrates that engage in this activity are called ‘‘litter transformers.’’ A variety of bacterial predators, including some nematodes and protists, and fungal grazers, including some nematodes and microarthropods, represent second-order consumers in the detritivore food web. Among second-order consumers in both the herbivore and detritivore food webs, morphological characteristics of consumers and their resources indicate general patterns of consumption. Protozoan predators and bacterial-feeding nematodes consume their prey whole, while fungal-feeding mites, collembolans, and nematodes have mouthparts that are specialized for chewing or piercing. The distinction between consumers of bacteria and fungi also turns out to be important as bacterial and fungal feeders are spatially and temporally separated in terms of their activities in the soil: bacterial predators forage primarily in water-filled soil pores and water films adhering to the surfaces of soil particles where bacteria occur, while fungal grazers can occur in water films (nematodes) and in the humid, air-filled soil pores (various microarthropods) through which fungal hyphae pass (Coleman et al., 1983). Thus, energy flow in the detritivore food web is compartmented further into a ‘‘bacterial pathway’’ and a ‘‘fungal pathway.’’ Rates of production and turnover also differ between

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these two pathways (Coleman et al., 1983). Production in the ‘‘fast’’ bacterial pathway rapidly increases in response to labile resource inputs and then falls off as resources are depleted. The ‘‘slow’’ fungal pathway is active over longer timescales, breaking down more recalcitrant substrates that are less variable through time. The fungal pathway is also less constrained by water availability than the bacterial pathway. Such generalizations are useful in practice, even though variation in resource consumption and environmental constraints exist within these broad taxonomic categories. For example, zygomycete ‘‘sugar fungi’’ are early colonizers of plant litter, disappearing early during fungal succession (Garrett, 1981). Predatory nematodes, collembolans, mites, and larger arthropods represent higher-order consumers. These consumers tend to prey on consumers from both the herbivore and detritivore food webs and from the bacterial and fungal pathways, linking these energy flows. Earthworms greatly influence soil structure and trophic interactions via their feeding and migratory activities. However, in general, earthworms are not included as a component of the soil food web even though they feed on most trophic groups within the web, albeit indirectly while digesting litter and soil organic matter. Small soil-dwelling mammals, such as moles and ground squirrels, also feed on larger soil invertebrates but are usually not included in soil food web models. These deletions illustrate that further descriptive research on soil food webs is necessary. The environment in which these interactions occur represents an additional player in the soil food web. Soil is a complex, three-dimensional matrix with hierarchical levels of structure at particulate, micro-, and macroaggregate levels (Rillig and Mummey, 2006). Soil texture modifies bacterial population dynamics at fine spatial scales by mediating interactions with predators (Elliott et al., 1980). Bacteria gain access to particulate organic matter sequestered within microaggregates via narrow-necked pores; bacterial feeders require pores with neck size greater than 3, 20, and 30 mm for flagellates, nematodes, and ciliates, respectively (Brussaard, 1998). In addition, soil texture and structure influence trophic interactions indirectly by affecting water potential (Brady and Weil, 2002). Thus, spatial patterns of soil food web dynamics depend, to a certain extent, on fine-scale patterns of soil structure. Soil biota are important drivers of soil structure. Earthworms and plant root systems have strong effects on soil structure and texture (Brady and Weil, 2002). Direct effects of microorganisms on aggregate formation are believed to be active at different scales: fungal activity influences the formation of macroaggregates while bacteria and archaea are thought to be more important at the microaggregate level (Rillig and Mummey, 2006). Indirect effects may arise due to interactions among microorganisms and other soil biota; for example, microbiota associated with arbuscular mycorrhizal (AM) fungi had differential effects on soil aggregate stability depending on the

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identity of the fungal isolate they were associated with (Rillig et al., 2005). Trophic interactions in soil have received little study with regard to their effects on soil structure. One hypothesis is that alterations in grazing intensity on fungi might influence soil aggregation via physical (effects on mycelial structure) and chemical (altered exudation patterns from grazed hyphae) mechanisms (Rillig and Mummey, 2006).

3. Impacts on Soil Food Web Dynamics Associated with Human Activities In recent years, the monitoring of groups of soil biota occupying different trophic levels has grown as a method of evaluating trophic interactions in soil following environmental impacts and remediation programs (Sochova et al., 2006). In fact, the study of how human activities and environmental change influence soil organisms and their functions drove, to a large extent, the development and evolution of soil ecology (Wall et al., 2005). In one example, Wardle (1995) provided an extensive review and synthesis of the literature pertaining to the effects of tillage and other weed management practices on detritivore food webs in agro-ecosystems; this synthesis is broad in that, in addition to demonstrating the differential sensitivities of soil biota to weed management, it contextualizes soil food web dynamics within the testing of ecological theories. A single soil sample can contain multiple trophic groups, which is appealing given recent suggestions that evaluating restoration projects by monitoring solely the plant community inadequately estimates ecosystem recovery (Gratton and Denno, 2006; Levin et al., 2006). In this section, I briefly summarize four topics of recent, general interest in which soil biota represents major response variables: biodiversity loss, invasive species, climate change, and genetically modified (GM) crops. Most of the studies mentioned in this section quantify effects at more than one trophic level, although the distinction is not always made between direct effects at multiple trophic levels and indirect effects that cascade through trophic interactions. These topics could be subjected to extensive literature reviews if expanded to studies where only a single trophic level is considered, and have been in some cases (Dunfield and Germida, 2004; Wardle, 2002; Wolfe and Klironomos, 2005).

3.1. Biodiversity loss Ecosystem responses to the loss of biodiversity may be due to some intrinsic property of biodiversity (e.g., niche complementarity) or the loss of functionally important species (sampling effect) (Hooper et al., 2005). Researchers have attempted to determine the potential effects of biodiversity loss on soil food

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web dynamics by estimating the responses of soil organisms to different numbers of species in microcosms or field plots, then statistically evaluating the importance of plant species diversity, per se, relative to other factors, such as the traits of the plant species present. When Porazinska et al. (2003) observed differences in organism abundance within trophic groups associated primarily with the identity of grass species rather than number of species present in monoculture, plant species richness had few effects on abundance within trophic groups. In another study, plant species identity, but not plant species richness, affected the abundance of bacterial-feeding and plant-parasitic nematodes, but not fungal-feeding nematodes (De Deyn et al., 2004). Furthermore, plant-parasitic nematodes were generally greater in the presence of Holcus lanatus, Leucanthemum vulgare, and Centaurea jacea and reduced in the presence of Plantago lanceolata, regardless if they were measured in monoculture or in the presence of other plant species, further suggesting the importance of plant species identity in relationships between plant and soil biodiversity (De Deyn et al., 2004). Synthesizing these results, species identity effects were stronger than diversity effects per se. The particular traits that resulted in species identity effects are not clear. Plant development time may have been important since it represented a significant source of variation for all trophic groups except fungal feeders in the study by De Deyn et al. (2004). Resource quality homogeneity may be another important factor. Resource quality (C3 vs C4 photosynthetic pathway) and species origin (native vs exotic) did not represent significant sources of variation in the study by Porazinska et al. (2003). Gastine et al. (2003) observed no effect of plant functional group (grasses, legumes, forbs) diversity on microbial activity, microbial-feeding nematodes, or predatory nematodes. However, Wardle et al. (1999) observed complex responses of various groups of soil biota to removal of plant functional groups (C4 grasses, C3 annual and perennial grasses, legumes, forbs) from field plots, linking these responses to shifts in resource quality. Caution is necessary when interpreting these results since the effects of plant biodiversity on soil food web dynamics are not clearly understood. In one case, increased plant species diversity often negatively affected abundance within soil functional groups relative to their abundance in monoculture. Wardle et al. (2003) observed that plant species identity in monoculture had significant effects on abundance of enchytraeids and plant-parasitic, microbial-feeding, and predatory nematodes; however, when plant species and functional group diversity were manipulated, these trophic groups often did not achieve their abundance in the monocultures. In addition, focusing on abundance within functional groups may underestimate responses when compared with responses within taxonomic groups. Korthals et al. (2001) studied the effect of low diversity (initially four plant species) versus high diversity (initially 15 plant species) on nematode

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communities of abandoned agricultural land and observed positive and negative effects of diversity on several plant-, bacterial-, and fungal-feeding nematode genera responding to the treatment; however, the only trophic group showing an overall response was that of bacterial feeders, the abundance of which was reduced in the high diversity treatment. In the study by De Deyn et al. (2004), plant species identity influenced taxonomic diversity within functional groups but had little effect on overall functional diversity, as indicated by various indices of trophic structure. Currently, biodiversity researchers are using increasingly complex experimental designs in an attempt to approximate the complexity of interactions occurring in reality. Recent studies attempted to identify the linkages, direct and indirect, between aboveground and belowground communities, and to determine the consequences of these linkages for the structure of plant communities and higher trophic levels (De Deyn and Van der Putten, 2005; Hooper et al., 2000; Wardle, 2002; Wardle et al., 2004). These linkages are manifested via general mechanisms, such as detrital inputs and effects on primary productivity, as well as specific mechanisms, such as the role of plant species identity on herbivory and decomposition. For example, aboveground influences on plant growth, such as herbivory, can influence the movement of energy through soil food webs; in an assembled grassland community, increasing defoliation intensity progressively increased shootto-root ratios, and reduced root mass, resulting in increased abundance of bacterial consumers and fungal consumers and reduced herbivore abundance in soil (Mikola et al., 2001). Linkages between aboveground and belowground communities increase the potential for effects in one community as a result of biodiversity loss in the other community, and greater understanding of the strengths of these linkages may allow for more accurate predictions as to how ecosystems will respond to further biodiversity loss.

3.2. Invasive species Increased human migration and economic trade has resulted in accelerated transcontinental and intercontinental movement of biota. Species introductions into exotic environments can impact native species and ecosystems via a number of direct and indirect ecological mechanisms, including competition, facilitation, and trophic cascades (White et al., 2006). Species invasions in aquatic systems can impact food web structure resulting in diet shifts and trophic cascades (Townsend, 1996; Vander Zanden et al., 1999); however, effects on trophic cascades in terrestrial systems are poorly understood (White et al., 2006). Several studies have looked at the impacts of exotic plant invasions on soil biota and the mechanisms by which soil biota may mediate exotic plant invasions (Belnap and Phillips, 2001; Belnap et al., 2005;

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Callaway et al., 2004a,b; Kourtev et al., 2002; Stinson et al., 2006). Few of these studies, however, have measured responses in soil biota at more than one trophic level and effects are often plant and/or environment specific. Belnap and Phillips (2001) observed several variable and inconsistent effects of cheatgrass (Bromus tectorum) invasion on various groups of soil biota; they compared invaded and uninvaded plant communities in Utah and observed inconsistent responses among the two native grassland types. Similarly, Yeates and Williams (2001) detected effects of wandering jew (Tradescantia fluminensis) and gorse (Ulex europaeus), but not wild ginger (Hedychium gardnerianum), on fungal-feeding, plant-feeding, and omnivorous nematodes at various sites in New Zealand; however, the direction of the effect often differed among sites. In one Colorado field experiment, phospholipids associated with Gram-negative bacteria were less abundant in the presence of an exotic grass (Caucasian bluestem, Andropogon bladhii) than native grasses, but nematode trophic structure or mite assemblages were not affected (Porazinska et al., 2003; St. John et al., 2006). Pritekel et al. (2006) observed effects of invasive leafy spurge (Euphorbia esula) on mite assemblages in Colorado grasslands, with prostigmatid (in 1 of 2 years) and cryptostigmatid (in both years) mites being less abundant in leafy spurge-invaded field plots, but not on collembolan abundance; various herbicides had been applied in prior years to invaded plots, but not uninvaded plots, in an effort to control leafy spurge, so effects on mites may not have been entirely or in part due to the invasive plants themselves. Recent research on the role of phytochemistry in plant invasion suggests that many exotic plants exude bioactive compounds into the rhizosphere, including compounds with antiherbivore, antimicrobial, and antifungal activities (Cappuccino and Arnason, 2006). For instance, glucosinolates exuded from the roots of garlic mustard release isothiocyanates that have negative effects on AM fungi (Roberts and Anderson, 2001; Stinson et al., 2006) and possibly other fungi (Smolinska et al., 2003). Negative effects on fungal dynamics might result in cascading effects for trophic interactions involving fungal feeders and the partitioning of energy through the bacterial trophic pathway in stands of garlic mustard; however, more research is required to determine if phytochemicals associated with plant invasions can have such cascading effects on soil food webs. There are several examples of humans introducing exotic soil organisms into new environments, with consequences for ecosystem functioning. For example, exotic earthworms alter nutrient cycling and plant community dynamics (Bohlen et al., 2004), nonnative ectomycorrhizal fungi facilitated the colonization of South Africa by exotic Pinus spp. (Richardson et al., 2000), and agronomists are concerned about the movement of plantparasitic nematodes and other plant pathogens. Whether introductions of exotic soil organisms can affect trophic interactions in the invaded range is an open question. Soil food webs are considered to contain high levels of

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functional redundancy, with many similar consumers feeding on many similar prey (Seta¨la¨ et al., 2005). Such a generalist view of soil trophic interactions suggests that exotic organisms are likely to encounter predators in the invaded range similar to those in their native ranges, buffering the influence of the invader on the rate and direction of energy flowing through a soil food web. However, if specialist relationships with parasites and pathogens dominate population regulation in the native environment, the invader may exert a significant influence on trophic structure and function in the invaded range. For example, mole crickets (Scapteriscus spp., Gryllotalpidae) are particularly damaging pests of pasture and turf in the southeastern United States, inadvertently introduced from South America (Walker and Nickle, 1981). Released from natural enemies in their native range, including an entomopathogenic nematode (Parkman et al., 1993) and a carabid beetle (Weed and Frank, 2005), mole crickets attain high population densities in the absence of control measures (Adjei et al., 2003). Populations follow an annual cycle, with adults emerging, laying eggs, and dying in the spring; synchronized mortality likely results in resource pulses, similar to pulses following periodic emergence and mortality of cicadas stimulating bacterial and fungal biomass and altering abundance of various detritivorous macroarthropods (Yang, 2004, 2006).

3.3. Climate change Climate change is occurring in many forms, including changing temperature and precipitation regimes, prolonged exposure to UV-B radiation, and exposure to increasing concentrations of CO2. Soil biota may be affected by climate change as a direct result of these factors or, indirectly, due to effects on litter quality and quantity, evapotranspiration rates, and nutrient availability (Norby and Luo, 2004). One approach to studying the effects of climate change on soil biota under field conditions is to artificially increase temperature. Ruess et al. (1999) simulated climate change by manipulating temperature and nutrient availability at two sites in northern Sweden. After 6 years of manipulation, fertilization stimulated microbial biomass, and active fungal biomass at one of the sites; bacterial- and fungal-feeding nematodes appeared to increase in abundance under the elevated temperature treatment, although differences were not statistically significant. Sohlenius and Bostrom (1999) increased temperature by transplanting soil cores from northern Sweden to various warmer locations throughout Sweden, and then monitored changes in the nematode communities over the course of 1 year. This approach also takes into account that plant community responses to climate change may indirectly influence soil biota. Total nematode abundance increased in soils transplanted to warmer sites, and various effects on plant-, bacterial-, and fungal-feeding taxa and predatory taxa were observed. Effects were more

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pronounced at sites with less plant cover, suggesting that plant and soil variables may be more important drivers of climate change induced shifts than increased temperature (Sohlenius and Bostrom, 1999). The most common approach to studying the effects of climate change on soil biota is to measure their responses to elevated concentrations of CO2. Several field studies, at a number of locations worldwide, have attempted this. Sonnemann and Wolters (2005) exposed a German grassland to a 20% increase in [CO2] for 3 years. Bacterial biomass, but not fungal biomass, increased in the elevated CO2 treatment relative to the ambient CO2 treatment over the course of the experiment; trophic cascades were not observed, however, since the abundance of bacterial-feeding nematodes was not affected by the CO2 treatment. Root hair-feeding nematodes were stimulated and predaceous nematodes were reduced in the first year of the CO2 treatment, but no treatment effects were observed in subsequent years. In a Michigan forest, Hoeksema et al. (2000) observed shifts in nematode community composition following exposure of young aspen (Populus tremuloides) to twice-ambient [CO2]; however, responses were dependent on soil origin (low N and soil organic matter vs high N and soil organic matter). As a group, plant-feeding nematodes were more abundant under elevated CO2 in the high N, but not the low N soil. Predaceous nematodes, on the other hand, were more abundant under elevated CO2 in only the low N soil. At a Swiss calcareous grassland, Niklaus et al. (2003) observed responses in various components of the soil food web exposed to elevated CO2 for 6 years. They observed no significant effects of elevated CO2 on protozoans, collembolans, microbial-feeding nematodes, plant-feeding nematodes, or mites. Predaceous and omnivorous nematodes were less abundant in the elevated CO2 treatment. Hungate et al. (2000) observed that responses to 4 years of elevated CO2 at sandstone and calcareous grasslands in California were sensitive to seasonal fluctuations, with stimulatory effects on fungi, flagellate protozoans, and plant-feeding nematodes (sandstone only) detected early in the growing season. Other groups, including bacteria, other bacterial-feeding protozoans, and microbial-feeding nematodes were not responsive to the CO2 treatment. In the same experiment, after 6 years of elevated CO2, Rillig et al. (1999a) observed that fungal biomass was greater in the elevated CO2 treatment (sandstone only), as were fungal-feeding microarthropods. No effects on bacterial biomass or the biomass of bacterial-feeding protozoans were detected. Allen et al. (2005) estimated responses of bacteria, fungi, and their consumers to elevated CO2 in a Californian chaparral over a 3-year period. Biomass of bacteria and their consumers did not respond to elevated CO2. Biomass of fungi and their consumers also did not respond to elevated CO2, except for one

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growing season in which mite biomass increased with increasing [CO2]. Fungal biomass was not affected by elevated CO2 over this same sampling period; however, when the authors estimated fungal biomass consumed by mites and added this estimate to the standing fungal biomass estimates, it revealed a positive relationship between fungal biomass and [CO2] up to 550 ppm. Neher et al. (2004) evaluated the abundance and energetics of nematode communities at two locations in the eastern United States. Biomass and respiration of fungal and bacterial feeders decreased in response to elevated CO2. Bacterial feeders decreased in abundance, in contrast to fungal feeders, which increased in abundance, in response to elevated CO2. Responses of predators, omnivores, and root feeders were significant but inconsistent at the two locations. These results suggest that elevated CO2 stimulates various functional groups in soil, although effects were often inconsistent among studies. Effects on soil biota are usually attributed to changes in the abundance and quality of resources. Elevated CO2 can increase net primary productivity, resulting in increased root growth and litter fall (Norby and Luo, 2004). Cotrufo et al. (1998) reviewed the elevated CO2 literature and estimated a 14% reduction of nitrogen concentration of plant tissues associated with elevated CO2; differences varied among plant types with C3 plants demonstrating greater reductions than C4 and nitrogen-fixing plants. As a result, responses to elevated CO2 are linked to the availability of other nutrients that limit productivity and influence resource quality; for example, Klironomos et al. (1996) demonstrated the dependence of elevated CO2 effects on soil fertility. Sagebrush (Artemisia tridentata) plants were grown in a low fertility soil either supplemented with nutrients or unfertilized. Soil food web responses to elevated CO2 were muted in the unfertilized soil and exaggerated in the fertilized soil. CO2 stimulated fungal and bacterial biomass and microbefeeding microarthropods, but only in the fertilized treatment. Only nematode abundance was stimulated by elevated CO2 in the absence of fertilization, and further stimulation was observed following nutrient addition. Further research is necessary to determine the identity and relative importance of the mediating factors resulting in inconsistencies among studies. Ecosystem models that estimate soil food web dynamics and nutrient cycling in response to various components of climate change, such as the approach used by Kuijper et al. (2005), will likely be required to reconcile inconsistencies among studies in the observed effects. The model by Kuijper et al. (2005) predicts that fungal-feeding taxa will be more sensitive to climate change than bacterial-feeding taxa, a trend that is supported by many of the previously mentioned studies, and that omnivory and weak trophic links will limit effects of trophic cascades on higher trophic levels. Further experimental research is necessary to test these and other predictions.

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When discussing functional group responses to elevated CO2, researchers less frequently ascribe these responses to interactions with abiotic factors than to trophic cascades. In one example, elevated CO2 lead to reduced evapotranspiration rates in the study by Niklaus et al. (2003), resulting in increased soil moisture and reduced soil aggregate sizes; reductions in predatory and omnivorous nematodes were speculatively attributed to reduced mobility under the modified soil structure. Rillig et al. (1999b), however, observed the opposite effect of elevated CO2 on soil structure in California calcareous and sandstone grasslands. Larger soil aggregates (1–2 mm) increased in abundance, as did the stability of aggregates down to 0.25 mm in diameter, in the elevated CO2 treatment; abundances of omnivorous and predatory nematodes were not reported (Hungate et al., 2000; Rillig et al., 1999a). Extrapolating published results of experiments applying abrupt changes in [CO2] is problematic, however, as responses may be quite different from those under gradual increases in [CO2]. Klironomos et al. (2005) observed effects of elevated CO2 on structural and functional properties of AM fungal communities; these effects were only observed following an abrupt increase in [CO2] and not when [CO2] was increased gradually, over a period of 6 years. More research is required to determine if responses in soil food web dynamics to artificial climate change represent adequate estimates of responses to actual rates of climate change over the coming decades.

3.4. GM crops GM cropping systems have been the focus of recent attention, largely due to public concern about their safety. There are two general mechanisms in which GM cropping systems can affect organisms in and around fields: (1) effects associated with the modification itself and (2) effects associated with the management of transgenic varieties. Initially, attention focused on the modified traits themselves. Several studies document shifts in endophytic and rhizosphere microbial communities associated with GM crops (pleiotropic effects or other varietal changes), but few look at effects at higher trophic levels. Donegan et al. (1997) observed increased nematode abundance but reduced collembolan abundance associated with litter from transgenic proteinase inhibitor I producing tobacco in field soil. In another field experiment, Donegan et al. (1999) observed shifts in soil microbial communities and enzymatic activities associated with a recombinant nitrogen-fixing bacterium (Sinorhizobium meliloti) and transgenic lignin peroxidase- (but not amylase-)producing alfalfa, but observed no effects on protozoa, nematodes, and microarthropods. Saxena and Stotzky (2001) observed no effect of CryIAb protein, either in corn root exudates or in litter added to field soil, on microbial, protozoan, or nematode abundance. Griffiths et al. (2006) observed that omnivorous nematodes and protists were more

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abundant in the presence of a Bt-corn variety, but other nematode trophic groups, microarthropods, and cabbage root fly were not affected; soil type and insecticide treatment modified the responses and had greater overall effects than did the Bt trait in this greenhouse experiment. Not only do environmental factors and the type of modification affect functional group responses to GM crops, but variation among crop species also exists that could modify these responses. Saxena et al. (2004) observed exudation of insecticidal Cry protein from roots of Bt-corn, rice, and potato but not tobacco, canola, and cotton. There also appears to be a temporal component to when effects are more likely to occur. For example, Griffiths et al. (2006), in a greenhouse study conducted in two soil types, observed that Cry protein concentration increased in soil with corn growth stage. In addition, in the presence of living plants, protein concentration eventually became much more abundant in the soil (10.11–42.86 mg per kilogram soil) than in the roots (0.74–6.85 mg per kilogram tissue) or leaves (9.08–13.53 mg per kilogram tissue) at corn maturity, suggesting that responses of soil biota to litter addition may underestimate responses occurring in the presence of mature plants (Griffiths et al., 2006). An additional fear is that transgenes in GM crops may be incorporated into the genomes of weedy relatives, resulting in a fitness benefit to the recipients of the transgene and the evolution of new and/or stronger agricultural pests (Snow et al., 2003). Given the species-specific effects of plants on soil food webs (see discussion in Section 3.1 and 2), the potential impacts of gene transfer, if they occur, on trophic interactions in soil are likely dependent on the identity of the recipient species. More recently, impacts of GM crops are viewed in the context of the whole cropping system, as opposed to just the modified plant traits, as effects on nontarget organisms may be manifested via management approaches. Arguably, changes in the types and ways that pesticides are used and reduced reliance on tillage for effective weed control are more likely to have stronger effects on soil biota as these practices, directly and indirectly influence their abundances (Roper and Gupta, 1995; Wardle, 1995). As the adoption by growers of GM crops has increased, so has the adoption of the management practices associated with these crops. This is especially true for varieties modified to tolerate sprays of broad-spectrum herbicides. Glyphosate (RoundupÒ ) has quickly replaced the use of other herbicides in glyphosatetolerant cropping systems (Baucom and Mauricio, 2004; Carpenter et al., 2002); for instance, glyphosate is applied to >85% of soybean land area in the United States, the same percentage of land that is sown to glyphosatetolerant soybeans (NASS, 2006a, 2006b). Liphadzi et al. (2005) observed transient increases in soil microbial biomass associated with glyphosatetolerant corn–soy rotations relative to conventional systems, but no effects on nematode communities. In the UK farm scale evaluations (Bohan et al., 2005; Brooks et al., 2003), the authors compared nontarget population

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responses in fields containing GM, herbicide-tolerant varieties managed with their corresponding herbicides (glufosinate-ammonium or glyphosate) to those containing conventional varieties managed using conventional herbicides. Abundance of detritivores and seed-feeding carabid beetles varied among crop species but responded to the GM cropping systems in a similar way as did weed abundance, suggesting that responses were due to management effects on resource availability. However, it is difficult to determine the direct/indirect nature of responses in soil biota without manipulating additional factors that are known to respond to management or simulating responses using ecosystem models.

4. Alternative Approaches: Seeing the Forest for the Trees Ecosystems are inherently complex and contain a mind-boggling array of biotic and abiotic interactions. The studies mentioned in the previous section estimated effects of perturbations on functional groups within a soil food web. Many authors then attempted to scale the results up to gain information about the response of the soil food web as a whole; several interpret effects on consumer abundance as an indirect response to effects on resource abundance and, sometimes, lack of an effect on resource abundance as an indirect response to stimulatory effects on consumer abundance. However, interpretation of functional group abundances becomes difficult when time lags mask the manifestation of consumer responses to increased resource availability (Ettema et al., 1999; Wardle et al., 1999), especially when the sampling design does not take temporal variation into account. Alternatively, responses in any one functional group may be independent of the trophic interactions involving that functional group. Instead, functional groups may respond to the direct effects of the perturbation or indirect effects on abiotic factors. Therefore, it is not always valid to interpret results in the context of food web interactions, or to extrapolate changes in population estimates to ecosystem-level responses. Fortunately, soil ecologists have developed two approaches to collapse large datasets on organism abundance and trophic status into interpretable estimates of the structure and function of the food web itself. The first, nematode faunal analysis, is an empirical approach that incorporates information regarding life history characteristics (e.g., rate of population growth) and trophic status of a subset of soil organisms to estimate emergent properties of the existing soil food web, such as stability and productivity. The second is a modeling approach that attempts to (1) predict how localized changes within a food web (i.e., within a functional group) will influence

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the overall stability and productivity of the food web and (2) determine what properties of food webs make them resistant or resilient to perturbations.

4.1. Nematode faunal analysis 4.1.1. Theory It is typically difficult to quantify the condition of an ecosystem, which is dependent on many factors (e.g., nutrient status, disturbance history). The nematode faunal analysis concept attempts to gain information that surrogates for ecosystem-level factors by estimating components of food web structure from nematode communities. Nematodes are particularly suited as environmental indicators since they contain more trophic complexity than other taxonomic groups of soil organisms (Fig. 1); nematodes represent multiple trophic levels and occupy energy pathways based on all three resource-types (roots, bacteria, fungi). Nematodes are also important as their trophic activities influence nutrient cycling in natural and managed systems (Anderson et al., 1983; Ingham et al., 1985). An analogous system for estimating food web structure does not exist for any other group of soil organisms. Various indices are used to interpret nematode community shifts at a relatively high level of taxonomic resolution (family/genus); the most frequently used are the maturity index (MI), channel index (CI), enrichment index (EI), and structure index (SI). The indices combine information regarding the trophic guild (bacterivore, fungivore, herbivore, carnivore, or omnivore) and life history of the sampled nematodes. Life history is scored along a colonizer-persister scale; colonizer taxa have high population growth rates and are typical of nematode communities following a recent disturbance. Persister taxa are slower growing and typical of nematode communities in environments with low frequency of disturbance. The maturity index (MI; Bongers, 1990)

MI ¼

n X i¼1


n  c
p kc
p x n

ð1Þ

accounts for the relative proportion (nc–p/n) of nematodes in a sample (excluding plant feeders) that fit into categories (c–p) along the colonizer-persister scale, with k representing the weighting for any particular c–p category. A sample with a low MI indicates that the sample is dominated by opportunist taxa; as the MI approaches the maximum (5), the sample becomes increasingly dominated by slower growing, disturbance-sensitive taxa. An analogous index exists for plant-feeding nematodes, the plant-parasite index (Bongers, 1990), and the weighted MI (Yeates, 1994) includes plant-feeding and free-living taxa.

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Nematologists proposed additional indices that incorporate life history characteristics and trophic behavior of nematodes to a greater extent. The channel index (CI; Ferris et al., 2001)



0:8Fu2 CI ¼ 100 3:2Ba1 þ 0:8Fu2

 ð2Þ

estimates the relative weighting of the bacterial and fungal pathways of the soil food web by measuring the relative abundances of opportunitistic, freeliving nematodes in these guilds. A CI that approaches 0 indicates dominance by the bacterial energy pathway, while an index approaching 100 indicates dominance by the fungal pathway. The perceived benefit of employing the CI, as opposed to estimating the ratio of bacterial- or fungal-feeding nematodes to all microbivorous nematodes (the nematode channel ratio), is that the CI focuses on the faster-growing, opportunistic bacterial- and fungal-feeding species that respond rapidly to enrichment, while attempting to correcting for differences in the rate at which energy flows through the two pathways. The EI (Ferris et al., 2001), which estimates responses associated with the nutrient status of a system, is calculated

 EI ¼ 100

Pn

e ne i¼1 kP Pn n i¼1 ke ne þ i¼1 kb nb

 ð3Þ

and the SI (Ferris et al., 2001), which estimates the degree to which trophic interactions within food webs have developed, is calculated

 SI ¼ 100

Pn

s ns i¼1 kP Pn n i¼1 ks ns þ i¼1 kb nb

 ð4Þ

where n represents abundance and k represents the weightings for feeding guilds associated with enrichment (e), structure (s), and basal (b) components of the food web. Both indices scale on a range from 0 to 100. A high EI indicates greater availability of labile nutrients in the system, which stimulates the more rapidly cycling bacterial pathway. A high SI indicates the greater abundance of carnivorous and omnivorous nematodes, presumably due to a lack of disturbance in the system or greater resilience/resistance of the food web as structured. Estimates from the enrichment and structure indices can be calculated from the same sample and graphed together (Fig. 2); the placement of data points in one of the four quadrats in the bivariate plot space suggests certain functional properties of the ecosystem within which the food web resides (Table 1).

325

Linking Soil Food Webs to Ecosystem Functioning and Environmental Change

cto ry

Enriched

Quadrat B

t in

de

x

Quadrat A

Structured

en ric hm

Fu2 (0.8)

Quadrat D

Quadrat C

En

En

ric hm

en t tr aje

Ba1 (3.2)

Fu2 (0.8) Basal condition

Ba2 (0.8)

Basal

Structure index Ca2 (0.8) Om4 (3.2) Om5 (5.0) Ca4 (3.2) Ca3 (1.8) Ca5 (5.0) Fu3 (1.8) Fu5 (5.0) Fu4 (3.2) Ba3 (1.8) Ba5 (5.0) Ba4 (3.2) Structure trajectory

Figure 2 Functional groups of soil nematodes characterized by trophic group and life history characteristics. Groups belonging to basal, enriched, or structured food webs are included and their weightings for calculation of structure and enrichment indices indicated. Reprinted from Ferris et al. (2001), with permission from Elsevier.

4.1.2. Application Several recent studies have employed this version of the nematode faunal analysis concept. Most of these studies were conducted in agricultural systems, estimating soil food web responses to soil and crop management practices. In a series of papers, Wang et al. (2003, 2004, 2006b) evaluated the main effects of amendments on nematode trophic structure and their interactive effects with other management practices. Compost amendment (269 Mg ha
1 year
1, derived from sticks, lawn clippings, and wood fragments) for 5 years increased nutrient availability (higher EI: 31.8 vs 23.9 in the absence of compost) and the relative contribution of the bacterial energy pathway (low CI: 18.5 vs 59.4); the SI (38.4–52.2) indicated an intermediate level of trophic organization but was not significantly affected by compost amendment (Wang et al., 2004). Amending soil from compost-incorporated and control plots with sunn hemp (Crotalaria juncea) hay (1 g per 100 g soil) resulted in a greater MI in one of two greenhouse experiments (2.02–2.12 vs 1.97–2.00 in the C. juncea unamended soil) but no effects on the structure, enrichment, or channel indices (Wang et al., 2003). In a field experiment, amendment with C. juncea hay resulted in a greater reduction in the maturity and channel indices, suggesting increased abundance of opportunitistic, bacterial-feeding nematodes, and a greater increase in the EI, indicating more rapid nutrient cycling, than ammonium nitrate application (Wang et al., 2006b).

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Jeff R. Powell

Table 1 Soil nutrient status and food web condition inferred from combined calculation of nematode community structure and enrichment Indicesa

General diagnosis

Quadrat A

Quadrat B

Quadrat C

Quadrat D

Disturbance

High

Low to moderate N-enriched Balanced

Undisturbed

Stressed

Moderate Fungal

Depleted Fungal

Moderate to high Structured

High

Enrichment N-enriched Decomposition Bacterial channels C:N ratio Low Food web condition a

Disturbed

Low Maturing

Degraded

Quadrats refer to those presented in Fig. 2. Reprinted from Ferris et al. (2001), with permission from Elsevier.

In another study, Liang et al. (2005) observed reduction in the CI following fertilization with urea, associated with increased NO3 and NH4 levels; however, the slow-release urea formulation resulted in a higher value for the SI, indicating greater trophic diversity. In a comparison of long-term organic, low-input, and conventional management systems, Berkelmans et al. (2003) observed that the organic and low-input systems, relative to the conventional system, were frequently associated with higher enrichment and SI, indicating higher fertility and greater trophic structure, and lower basal and channel indices, reflecting reduced abundance of opportunistic nematodes and rapid nutrient cycling through the bacterial pathway of the soil food web. Ferris et al. (2004) manipulated the trophic structure of nematode communities (and presumably, other microbial feeders) through a combination of fall irrigation and carbon input, following which they observed greater nitrogen mineralization in the subsequent cropping season. The type of amendment used will play a role in determining the overall effect on nutrient availability. Ferris and Matute (2003) observed structural and functional succession of the nematode community in response to substrates of differing C/N ratios. The EI declined over time at a rate regardless of the substrate added. Progression toward fungal domination of energy flow was faster for wheat straw (C/N ¼ 75.9) than for alfalfa (C/N ¼ 10.6), but not faster than for compost (C/N ¼ 10.6), indicating that factors in addition to C/N are also important. There was also a succession from enrichment opportunist bacteriovores to general opportunist bacteriovores, but the rate of succession did not differ among the types of amendments (Ferris and Matute, 2003). Other studies have incorporated the nematode faunal analysis concept into estimates of soil biodiversity in grasslands and pastures, the advantage

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327

being that functional components of the ecosystem are also measured with potential implications for nutrient cycling and grassland productivity. For example, Zolda (2006) studied the nematode fauna of grazed and ungrazed grasslands in Austria, Stirling and Lodge (2005) estimated the relationships among climatic and plant species factors and nematode communities in Australian pastures, Bell et al. (2005) studied the nematode fauna of New Zealand tussocks, and De Deyn et al. (2004) employed the nematode faunal analysis concept to address the effects of plant diversity on nematode taxonomic and functional diversity. Hoeksema et al. (2000) and Sonnemann and Wolters (2005) used the MI in their evaluations of the effects of elevated CO2 on nematode community structure. Hoeksema observed an increase in the MI associated with elevated CO2 in a low-N soil, indicating greater abundance of slower-growing nematode taxa; however, this result was not observed in the high-N soil, nor in the study by Sonnemann and Wolters (2005). Nematode faunal analyses suggest that nematode communities are quite susceptible to disturbance. For example, Berkelmans et al. (2003) observed that 1 year of a common crop and tillage undid the effects of several years of divergent management practices (organic/low input/conventional). However, some analyses suggest that nematode communities are also resilient to some disturbances. Wang et al. (2006a) observed only short-term effects of solarization or cowpea cover cropping on the SI, disappearing by the end of the experiment (5–6 months); methyl bromide fumigation, however, had persistent effects. Wang et al. (2004) observed little difference in the trophic structure of nematode fauna when comparing untilled plots versus plots undergoing multiple roto-tilling events for 25 years; the tilled plots had been left fallow for 1.5 years prior to sampling, leaving the possibility open that the nematode community recovered quickly once frequent manual disturbance was removed from the system. The time required to recover from disturbance provides additional information regarding ecosystem recovery and should be a focus of future research. Further research should improve the utility and sensitivity of nematode faunal analysis. Debate continues regarding the placement of taxa into c–p groups (Bongers, 1990) and the generalities of genera and family-level resolution of trophic groups (Yeates et al., 1993). Both are based largely on observations of nematode behavior on agar media, which may not be representative of behavior in nature. Tylenchid nematodes, classified as plant-, algal-, and lichen feeders but possibly also fungal feeders (Yeates et al., 1993), can constitute 30% or more of a sample (Ferris and Bongers, 2006). Furthermore, an evaluation of nematode community indices in three different ecosystem types (wetland, forest, and agricultural) indicated that the indices were differentially sensitive to disturbance in the different ecosystems and that variance within community composition at the genus level within families was more sensitive than the community indices to ecosystem type and disturbance (Neher et al., 2005). Fiscus and Neher

328

Jeff R. Powell

(2002) used multivariate statistical techniques to evaluate the sensitivity of nematode taxa to particular agricultural disturbances, suggesting that individual analyses could be tailored to have greater sensitivity by selecting particular taxa relevant to the disturbance(s) under study.

4.2. Modeling food web dynamics 4.2.1. Theory The modeling approach to studying food webs highlights properties of the system emerging from the individual interactions occurring within. Early models focused on connectivity food webs, in which linkages between two interacting groups indicate where trophic interactions occur but all linkages are assigned equal weight. Models by May (1972, 1973) arrived at the conclusion that complex food webs (i.e., those containing many interacting species) are less likely to be stable than simple webs; increases in species richness (S) must be accompanied by a decrease in either connectance,

  L C¼ S2

ð5Þ

where L is the proportion of all possible linkages that are realized, or the average strength of the interactions (per capita effect of one species on another) occurring in the system. May observed, however, that the presence of compartments in food webs, within which species interact readily with each other but very little with species in other compartments, increased the feasibility of constructing large food webs (May, 1972, 1973). Lower richness within individual compartments allowed for more and stronger interactions among species without risking instability. In the 1980s and early 1990s, soil ecologists conducted surveys of soil food webs whereby they represented interactions as quantifiable flows of material cascading through the web. These surveys, and subsequent modeling exercises, are built upon available descriptions of connectivity webs (Fig. 1) by assigning weights to these linkages. Weights represented either the amount of energy present within and moving between pools (energy webs), or the per capita effects of one functional group on another (functional or interaction strength webs). From these models it became clear that, in determining the stability of food webs, the number of interactions within a food web is less important than how those interactions are structured. As a result, these researchers were capable of addressing questions related to the emergent properties of the food web, emphasizing properties associated with trophic diversity and structure (how many trophic levels/linkages are supported at any particular level of productivity?) and ecosystem stability (how resistant/resilient is food web structure to environmental perturbation?).

Linking Soil Food Webs to Ecosystem Functioning and Environmental Change

329

Hunt et al. (1987) derived equations for modeling the flux of energy, as carbon and nitrogen, through food webs. For the consumption rate, F, of a consumer, j

 Fj ¼

 ðdj Bj þ Pj Þ aj pj

ð6Þ

where P and d represent the predatory and nonpredatory death rates, respectively, B represents biomass, and a and p represent the assimilation (ingested and not lost in feces) and production (retained as biomass) efficiencies, respectively, of the consumer. For consumers that feed on more than one prey, the consumption rate of prey, i, is a function of the preference, w, and biomass of i relative to that of all prey, k, so that

 Fij ¼

 wij Bi Pn  Fj k¼1 wkj Bk

ð7Þ

Energy webs are particularly useful for estimating how sensitive the length and reticulation of the food web is to the amount of energy entering and moving within the web. Moore and Hunt (1988) demonstrated that energy channeled through a soil food web largely via compartments (roots, bacteria, and fungi as basal resources in each pathway) with little movement of energy between pathways at intermediate trophic levels. The authors’ analysis of published connectivity webs of trophic relationships showed that the number of energy pathways (resource richness) in a food web correlated positively with the richness of consumers and negatively with connectance. This result supports resource compartmentation, reducing the proportion of species that directly interact, as a mechanism allowing stable species rich food webs to persist (May, 1972, 1973; Moore and Hunt, 1988). Functional webs represent the dynamic effects of trophic interactions, with a change in abundance at one trophic level eliciting a quantifiable change at another. DeAngelis (1992) and Moore et al. (1993) derived the dynamics of producer, consumer, and detritus density. Biomass density, X, of producer i changes over time in relation to growth (at both the individual and population levels combined) and consumption, such that



dXi dt

 ¼ ri X i


n X

cij Xi Xj

ð8Þ

j¼1

where r represents the specific growth rate of the producer and c represents the consumption coefficient for consumer j. Biomass density of detritus, d,

330

Jeff R. Powell

changes over time in relation to the amount of detritus entering the system from allochthonous inputs, autochthonous inputs due to unassimilated and unconsumed prey, and autochthonous inputs due to nonpredatory death of consumers, and the consumption of detritus, such that



dXd dt

 ¼ Rd þ

n X n n n X X X ðð1
ai Þcji Xj Xi Þ þ d i Xi
cdj Xd Xj i¼1 j¼1

i¼1

j¼1

ð9Þ where Rd represents the rate of allochthonous input. Biomass density of consumer, j, changes over time in relation to decline due to nonpredatory death, decline due to being consumed by n consumers, l, and growth associated with consumption, such that n n X X dXj cjl Xi Xl þ aj pj cij Xi Xj ¼
dj Xj
dt i¼1 l¼1

ð10Þ

functional webs are particularly useful for estimating how perturbations of the web, such as the removal of one or more trophic groups, will affect the abundance of other trophic groups. de Ruiter et al. (1995) linked the functional and energy web models by assuming that feeding rates (Fij) and biomass (Bi,Bj) in the energy model equal consumption rates (cijXiXj) and biomass density (Xi,Xj) in the functional model, respectively, in order to estimate the consumption coefficient

 cij ¼

Fij Bi Bj

 ð11Þ

from nutrient flux data and estimate interaction strengths, a, as the per capita effects of consumer j on prey i,

  Fij aij ¼
Bj

ð12Þ

and vice versa,



aj pj Fij aji ¼
Bi

 ð13Þ

Linking Soil Food Webs to Ecosystem Functioning and Environmental Change

331

in soil food webs. Strong interactions occur when per capita effects of consumers on prey or vice versa are large. In an analysis of several soil food webs by de Ruiter et al. (1995), complex interactions, both strong and weak, had strong effects on stability. Varying the interaction strengths of most pathways in the root-pathway and at intermediate and higher trophic levels (secondary consumer and up) had strong impacts on food web stability, while varying the strengths of interactions among fungi or bacteria and their consumers had very little impact on stability. Rooney et al. (2006) further linked the models by relating interaction strength to the speed of energy flow, v, represented by the rate that consumer biomass is turned over, such that

 Pn vj ¼

i¼1 aij



Bj

ð14Þ

for energy flux into consumer j and

 Pn 
l¼1 alj vj ¼ þ dj Bj

ð15Þ

for energy flux out of consumer j, suggesting that fast energy flux webs are composed of strong interactions and slow energy flux webs contain weak interactions. Rooney et al. (2006) observed similar asymmetrical partitioning of energy to pathways in six marine (pelagic vs benthic) and terrestrial (bacterial vs fungal) food webs, with higher-order consumers deriving energy from both pathways and coupling the pathways. By varying the energy flowing through one pathway relative to a second constant pathway, they observed that stability (associated with both resilience and resistance) was lowest when the two were equal and increased with increasing difference between the variable and constant pathways. Temporal asynchrony in the flux of energy through different pathways means that consumers at higher trophic levels, where the soil food web is much more reticulate, may be less likely to encounter highly variable resource availability (McCann et al., 2005). Moore et al. (2005) modeled the stability of a two-channel food web, containing a single resource base, two primary consumers, two secondary consumers, and a single top predator and using parameters from the Colorado shortgrass steppe food web (Hunt et al., 1987), and varied the proportion of energy partitioned to each pathway; they found that the system demonstrated stability when 20–60% of energy was partitioned to the fast (bacterial) pathway, the optimum being 40%. Simulated patterns of allocation outside of this range result in unstable dynamics in food web structure. Stability is

332

Jeff R. Powell

thought to correspond to the nature of resource inputs into the system. Roots respond dynamically to herbivory, so availability is subject to negative feedback dynamics between resource inputs and consumer activity; detritus, however, is donor controlled, so consumer activity has no direct effect on future resource inputs (Moore et al., 1993). In addition, the greater resistance and/or resilience of the bacterial energy pathway also facilitates compartmentalization and overall system stability (Moore and de Ruiter, 1997; Whitford, 1989).

4.2.2. Application An environmental stressor may have an effect on one functional group or individual species within a number of functional groups. However, if the strengths of interactions with that functional group or those species, or if energy flow through the food web is sufficiently structured that the web is stable in the face of environmental stressors, these impacts may be less ecologically significant. For example, a simulated disturbance to an empirically based, two-compartment food web suggested that compartments improve total food web stability by retaining the effects of disturbance to the affected compartment, thus protecting other compartments (Krause et al., 2003). On the other hand, environmental perturbations that alter abundance within one or more components of the food web may affect overall food web structure over a timescale greater than that of the experiment. Thus, modeling responses in soil food webs might be useful to (1) predict how such perturbations may affect ecosystem function or (2) estimate the degree to which one or more functional groups must be affected to show a reduction in ecosystem stability. To utilize this modeling approach, parameter estimates should be appropriate for the system under study. Moore et al. (1996) described the roles of laboratory and microcosm experimentation required to parameterize these models. Researchers estimated predation and death rates, consumption coefficients, and assimilation and production rates of the organisms involved in the food web (Table 2). They based estimates on laboratory experiments (for lifespan and feeding behavior) and field measurements (for tissue digestibility, C:N ratios, and biomass C or N present within each of the trophic groups). It is feasible to use many of these parameter estimates for studies conducted in similar ecosystem types. However, the distribution of biomass and energy flow in soil food webs varies in a number of ecosystem types and assembled communities and, therefore, caution is necessary when employing parameter estimates derived from other studies. For example, meadows typically have higher levels of available nitrogen, higher denitrification rates, contain litter with lower C/N ratios, and retain less mineralized nitrogen than do forests (Griffiths et al., 2005; Ingham et al., 1989).

Table 2

Estimates of parameter values used in food web models Consumption coefficient cij [(g m^2)^1 year^1]

Functional group Herbivores Phytophagous nematodes Microbes Bacteria Fungi Microbivores Mycophagous collembola Mycophagous oribatida Mycophagous prostigmata Mycophagous nematodes Protozoa Bacterivorous nematodes Omnivorous nematodes Predators Predatory nematodes Nematophagous mites Predatory mites a

Horseshoe Bend

Lovinkhoeve

Kjettslinge

ai

pi

di (year )

CPER native

0.25

0.37

1.08

0.010

0.013

0.018

0.166

0.133

0.026

0.026

1.00 1.00

0.4
0.5 0.4
0.5

0.50
1.20 0.50
1.20

<0.001 <0.001

<0.001 <0.001

<0.001 <0.001

<0.001 <0.001

<0.001 <0.001

<0.001 <0.001

<0.001 <0.001

0.50

0.35

1.84

0.016

0.008

0.009

0.026

0.045

0.002a

0.002a

0.50 0.50

0.40 0.40

1.20 1.84

0.011 0.016

0.005 0.008

0.006 0.009

0.018 0.026

0.033 0.045

0.38

0.37

1.92

0.032

0.010

0.011

0.596

0.733

0.004

0.002

0.95 0.60

0.40 0.37

1.00
6.00 2.68

0.005 0.006

0.001 0.002

0.001 0.003

0.002 0.022

0.003 0.023

<0.001 0.004

<0.001 0.004

0.60

0.37

4.36

0.008

NA

NA

NA

NA

NA

NA

0.50 0.90 0.30

0.37 0.35 0.35

1.69 1.84 1.84

0.003 0.058 0.060

NA NA 0.327

NA NA 0.294

0.013 0.554 0.485

0.017 0.865 0.545

1.081 0.155b

1.016 0.178b

^1

ct

nt

if

cf

B0

B120

Mycophagous arthropods were treated as a single group. Predatory arthropods were treated as a single group. Data were obtained from a native shortgrass prairie at the Central Plain Experimental Range (CPER) in Colorado, Horseshoe Bend in Georgia (ct, conventional tillage; nt, no tillage), Lovinkhoeve in the Netherlands (if, integrated farming; cf, conventional farming), and Kjettslinge in Sweden (B0: barley low nitrogen; B120: barley high nitrogen). ai, assimilation efficiency; pi, production efficiency; di, nonpredatory death rate; cij, consumption coefficient; NA, group was not present at the site or was included with another functional group in the description. Reprinted from Moore et al. (1993), with permission from AAAS. b

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Stoichiometric differences among ecosystems are often used to explain shifts in the relative contributions of bacterial and fungal energy pathways. In a comparison of soil food webs from a prairie, a meadow, and a pine forest (Ingham et al., 1989), fungal feeders were more dominant in the forest than the meadow, with the opposite being observed for bacterial feeders, suggesting that the relative strengths of each energy pathway changed as the ratio of bacterial-to-fungal biomass changed (10:1 in the meadow, 1:8 in the forest). In a global literature survey representing 65 different sites, Ruess (2003) used the CI derived from nematode communities to test the hypothesis that the relative contribution of the fungal energy pathway increases as the ecosystem type moves from grassland through various stages of forest. Coniferous forest sites had the highest mean CI (see previous section; CI ¼ 50) relative to deciduous forest (CI ¼ 18), grassland (CI ¼ 24), and cropland (CI ¼ 18). However, all ecosystem types displayed a wide range of CI estimates (3–99 for coniferous forest, 12–31 for deciduous forest, 8–66 for grassland, 3–67 for cropland), suggesting that climatic, edaphic, and/or other factors exerted greater control. Management practices also affect energy allocation to fungal versus bacterial energy pathways. Moore and de Ruiter (1991) compared the dynamics of the soil food web from the native shortgrass prairie (Hunt et al., 1987) to those of the Lovinkhoeve winter wheat cropping systems food webs (Andre´n et al., 1990). The authors observed that conventional management practices resulted in the disappearance of much of the temporal separation in activities of the energy pathways, but that the proportion of energy derived from the different energy pathways by polyphagous predators was similar among the native prairie and the winter wheat fields, even though the ratio of bacterial-to-fungal biomass differed to a certain extent (10:1 and 50:1 at each site, respectively). In another example, Bardgett et al. (2001) sampled submontane ecosystems in the United Kingdom that varied in either grazing history (short-term and long-term ungrazed vs grazed) and in grazing intensity, associated with changes in the structure of plant communities. Moderate and intense grazing intensities were associated with relatively low and high ratios of bacterial-to-fungal biomass, respectively. Distribution of biomass within consumer trophic groups was not measured, but grazing history and intensity were associated with changes in nematode abundance, suggesting that trophic interactions may have been affected. Ettema et al. (1999) monitored the belowground impacts of fertilizing a riparian forest and observed that bacterial-, but not fungal-feeding taxa, increased in abundance following fertilization. Fertilization also resulted in stronger correlations between measurements of microbial biomass/activity and predator abundance for both bacterial- and fungal-feeding nematodes, indicating a synchronization of predator–prey dynamics (Ettema et al., 1999); responses of fast growing, opportunistic taxa to enrichment may overwhelm the time lag associated with slower-growing nematode taxa.

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Mulder et al. (2006) analyzed 99 Dutch soil food webs, derived from estimates of bacterial, nematode, microarthropod, earthworm, and enchytraeid abundances, differing in the degree to which humans impacted them. Food web connectance was lowest for the unmanaged ecosystems (dry heathlands and mature grasslands), indicating greater structuring of trophic interactions, even though these were not necessarily the most diverse or complex ecosystem types. Presence of macroherbivores was associated with greater eukaryotic biomass but also reduced soil biodiversity, trophic diversity, and food web complexity. The models presented earlier may also be used to enhance functional group abundance estimates that may be masked by trophic interactions. Allen et al. (2005) used consumption coefficients [cij; Eq. (11)] to estimate bacterial and fungal biomass consumed by nematodes and microarthropods. Total biomass (bacterial or fungal biomass in soil plus bacterial or fungal biomass consumed) allowed the authors to test for effects of elevated CO2 on these functional groups independent of top–down interactions that may mask the effects. In one case, elevated CO2 was associated with greater total fungal biomass but this effect was not detected when the estimate of only the standing crop of fungi was used.

5. Missing and Ambiguous Components of Current Soil Food Web Knowledge A number of factors may affect the robustness of using this modelbased approach to soil food web dynamics for evaluating ecosystem-level effects. For example, food web connectance is dependent on the species richness of the food web. Amalgamation of soil food webs at the level of functional groups underestimates food web richness and, probably, biases connectance estimates (Wardle, 1995). Studies by Martinez and coworkers (Martinez, 1993; Martinez et al., 1999) indicate that food web structure predicted by theory is highly dependent on the resolution at which the interactions within the web are resolved. We also lack a complete understanding of the roles that many soil organisms play in the food web. Here, I discuss some shortcomings of the current soil food web model and draw attention to techniques that should help to address some of these shortcomings.

5.1. Resolution Functional groupings underestimate the diversity of organisms taking part in soil food webs. For example, carnivorous nematodes are represented in one or two trophic groups, as predatory or omnivorous, in most food web models.

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However, researchers observe differences in feeding behavior of predatory nematodes, generally, depending on taxonomic affiliation, that may affect the prey items that they feed on (Khan and Kim, 2007; Yeates et al., 1993). Predators in the order Mononchida eat nematode prey whole or cut nematodes into smaller pieces before ingesting them. Those in the Diplogasterida can be omnivorous, feeding on microbes and microbivores, and possess a smaller buccal cavity than mononchs, limiting their ability to feed on large prey. Predators in the order Dorylaimida are also omnivorous but ingest prey contents after either piercing the prey with an odontostyle or slicing it with a mural tooth. Predators in the Aphelenchida feed in a fashion similar to dorylaims, piercing prey with a stylet and paralyzing it, followed by ingestion of body contents; aphelenchs are generally smaller than dorylaims but are able to enzymatically digest and consume large prey items. Khan and Kim (2007) summarize the results of feeding experiments and measurements of field populations from studies addressing the biological control potential of various predatory nematode species, revealing particular effects at finer levels of taxonomic resolution. Some predatory species (e.g., Mononchus aquaticus) feed on a wide range of plant-feeding nematodes, while others (e.g., Discolaimus arenicolus) have a narrow observed prey preference. Nematode species also differ in terms of the degree with which they suppress prey populations, ranging from no effect to complete elimination. The data summarized by Khan and Kim (2007) are limited to observations where prey items were plantfeeding nematodes, but these observations suggest that finer resolution will reveal greater trophic structure in other parts of the soil food web, as well. Another simplification is that food web diagrams often depict unidirectional flows of energy through consumers. Real webs, however, contain omnivory (feeding at more than one trophic level) and cannibalism (feeding within one’s own functional group), which are difficult to detect unless stable isotope abundance within the different biomass pools is also estimated (Section 5.2). As a result, the extent of consumption in food web models is generally underrepresented. In addition, some organisms are grouped within lower trophic levels but actually consume organisms at higher trophic levels. For example, nematophagous fungi feed on a variety of nematode species but, when quantifying soil food web dynamics, the abundance of nematophagous fungi is represented as fungal biomass, thus overestimating resource abundance and underestimating consumer abundance.

5.2. Integration of the detritivore and herbivore food webs A great deal of effort has gone into describing trophic interactions involving detritivores and root herbivores, mainly nematodes, to determine their roles in nutrient cycling and plant health, respectively. However, interactions involving consumers of root herbivores and symbiotic microorganisms are

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often poorly integrated into food web models. Aboveground, pathogenic fungal biomass was similar to herbivore biomass in a grassland experiment (Mitchell, 2003), suggesting that pathogenic microorganisms, in theory, could form the base of a food web energy pathway through which a considerable proportion of energy flows. Pathogenic bacteria and fungi are likely similarly abundant belowground; however, the extent to which these pathogenic organisms are consumed directly, and thus their direct involvement in soil food webs, is unclear. Many symbiotic organisms are susceptible to predation at some point in their life cycles. Some microbial antagonists (e.g., myxobacteria) kill bacterial and fungal pathogens and assimilate the contents of lysed cells (Dawid, 2000); further predation on these antagonists would constitute a food chain. Protozoan predation regulates population density of nitrogen-fixing rhizobia (Danso and Alexander, 1975). Mycorrhizal fungi have extensive hyphal networks, extending into the soil from plant roots, that may be subject to grazing (Smith and Read, 1997). Ectomycorrhizal fungi are able to access carbon through their association with ectomycorrhizal plant hosts or via decomposition of recalcitrant carbon sources, suggesting that their consumers access carbon derived from both the detritus and living plants. AM fungi, on the other hand, are unable to access carbon other than that derived from the mycorrhizal host and, thus, the path of energy flow is less ambiguous. However, there is currently some debate as to how AM fungi fit into soil food webs. Laboratory experiments (Moore et al., 1985) and studies with field soil using hyphal in-growth cores (Johnson et al., 2005) suggest that mites and collembola represent significant sources of biomass loss for AM fungi, yet choice experiments and vertically structured microcosm experiments (Klironomos and Kendrick, 1996) suggest that AM fungi are less palatable to microarthropods and that the vertical distribution of fungi in litter and soil plays a significant role in determining whether trophic interactions occur among fungi and their consumers. Root-feeding arthropods are attacked by a variety of parasites and predators. Entomopathogenic nematodes of the families Steinernematidae and Heterorhabditidae, as a group, can infect and kill a range of soil insects, herbivorous and otherwise (Poinar, 1979). The nematodes are essentially bacterivores, feeding on bacteria that they carry around with them and inoculate into the host hemocoel, and only occur outside of the host as an infective juvenile stage. As these infective juveniles have patchy distributions (Stuart and Gaugler, 1994), they represent an ephemerally abundant food source containing energy derived largely, but not entirely, from living plants. Tracking the source of that energy, however, is complicated since taxonomic identification of infective juveniles is difficult, abundance is generally determined through indirect and imprecise measures, and, even in cases where relationships involving specific herbivores and nematodes in

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the field are described (Parkman et al., 1993; Strong et al., 1996), unknown alternative hosts may contribute significantly to energy flows. In addition to their involvement within the herbivore food web, root herbivores and symbionts may indirectly influence the detritivore food web via their effects on the productivity of individual plant species (De Deyn et al., 2004; Klironomos, 2002, 2003) and entire plant communities (Burdon, 1987; De Deyn et al., 2003; van der Heijden et al., 1998), thus controlling the amount of detritus entering the soil food web. However, other factors complicate the relationship between plant productivity and activity in the detritivore food web. In a 3-year field experiment, Wardle et al. (1999) did not observe consistent associations between plant biomass and abundance within various functional groups of soil biota; the authors suggested that long-term litter and soil organic matter dynamics, resource quality, and regulation of consumer populations by predators structured soil communities to a greater extent than short-term changes in plant biomass. More detailed descriptions of soil food web dynamics may help to address uncertainties regarding the linkages between the herbivore and decomposer food webs, and the indirect versus direct effects of herbivore activity on consumer activity in the decomposer food web. Some invertebrate herbivores spend their entire life cycle belowground and actively disperse over relatively short distances (e.g., various plantfeeding nematodes), while others have both aboveground and belowground components of their life cycles and can actively disperse over long distances (e.g., various dipterans have larval stages described as ‘‘root maggots’’). This distinction may be of functional consequence since the consumption of invertebrates with aboveground dispersal stages prevents their emergence and dispersal and, thus, retains nutrients within the system. This process is analogous to that recently suggested for aquatic food webs contained within bromeliads (Ngai and Srivastava, 2006). Therefore, consumption of/by invertebrates with aboveground dispersal stages should have a greater per capita effect on local nutrient dynamics than consumption on/by those without aboveground dispersal stages.

5.3. Role of technology in resolving soil food webs Initially, when describing trophic interactions, soil ecologists were limited to conducting feeding trials under artificial, laboratory conditions and examining gut contents of field-collected specimens. The adoption of stable isotopes was a significant technological advance that allowed soil ecologists to describe feeding behavior and energy flow through soil food webs in the field (Hunt et al., 1987). Isotopic signatures (13C, 15N) in consumer biomass vary predictably in response to signatures in resource biomass. The isotopic signature of a material is depleted each time that material passes through a consumer; therefore, an organism’s isotopic signature can be use to infer its

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trophic level and whether it has engaged in omnivory (McNabb et al., 2001). Soil ecologists were thus able to validate the placement of functional groups within trophic levels and estimate the number of trophic levels present within the web, but were not able to detect specific consumer– resource interactions. However, a number of recently developed techniques should facilitate the mapping of these interactions in much greater detail. Analysis of dietary fatty acids may provide further resolution of trophic interactions to a level where the investigator can identify, broadly, the taxonomic group that the sampled organisms fed upon. Fatty acids present in cellular membranes of bacteria and fungi are assimilated into neutral (storage) lipids of their consumers and can be detected across at least three trophic levels (Ruess et al., 2005). Groups of bacteria (e.g., aerobic bacteria, anaerobic bacteria, cyanobacteria) and fungi (AM fungi, other fungi) can be resolved by the relative abundance of phospholipid fatty acids (PLFAs) that make up cellular membranes, and certain fatty acids are used as biomarkers to determine the presence and relative abundance of some groups in soil (Frostega˚rd et al., 1993; Olsson, 1999) or the diets of consumers (Ruess et al., 2005). Ruess et al. (2005) found the technique powerful enough to discriminate the regions from which collembolans were sampled; some species (e.g., Folsomia quadrioculata) had similar fatty acid compositions in the different regions, suggesting similar diets, while others (e.g., Neanurum muscorum) differed in fatty acid composition at the different regions, suggesting a geographic pattern in diet. This technique is limited to detecting trophic interactions in which fatty acids are assimilated into consumer biomass; organisms that are consumed but whose fatty acids are not assimilated are not detected. Recently developed approaches combine the analyses of stable isotopes and dietary fatty acids to gain simultaneous estimates of dietary preferences and food quality. Haubert et al. (2006) provided a variety of bacterial isolates to each of three different collembolan species, observing shifts in the neutral lipid fatty acid (NLFA; i.e., storage lipids) profiles of collembolans depending on the bacteria on which they fed. Three different surrogate variables, in addition to body mass and C/N ratio, were used to infer that one of the bacterial species represented poor food quality for the collembolans; collembolan NLFA:PLFA ratios were reduced and both 13C and 15N were enriched, suggesting metabolic mobilization of lipid reserves. Another approach for studying trophic interactions, stable isotope probing, involves the pulse-labeling of a resource and attempting to detect its presence in potential consumers; by looking for the presence of the isotopic signature within biomarker PLFAs, the consumer of the resource can be identified (Dumont and Murrell, 2005). Johnson et al. (2005) used stable isotope probing to estimate the extent to which grazing by collembola reduced AM fungal growth, indicated by the PLFA 16:1o5. Another novel approach to resolving trophic interactions in soil is the analysis of DNA in the gut contents of predators. Soil contains a number of

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materials (e.g., humic acids) that inhibit the polymerase chain reaction and can, therefore, lead to false negatives in detection of target DNA. Two recent studies describe protocols that allow for detection of prey DNA in the gut contents ( Juen and Traugott, 2006) and whole specimens (Pons, 2006) of predatory soil invertebrates. Juen and Traugott observed DNA degradation over two days in their experiment, suggesting that this method would be useful for determining the identity of prey that had been recently consumed. Clearly, the use of this method would be constrained to consumers that ingest their prey prior to digestion, as do many bacterial- and fungal feeders and organisms at higher trophic levels. Many consumers occupying low levels in the soil food web, including bacteria and fungi, obtain nutrients following the secretion of extracellular enzymes. Advances in stable isotope probing of DNA sequences may allow for high resolution of trophic interactions at the base of the soil food web. Dumont and Murrell (2005) review the use of stable isotope probing in environmental microbiology. Here, microorganisms in environmental samples are exposed to a stable isotope-labeled substrate (e.g., 13C-labeled glucose). RNA is then extracted from the sample, labeled with a fluorescent probe, and hybridized to an oligonucleotide array to identify the RNA sequences extracted from the sample. The array is then viewed using autoradiography to determine which of the extracted RNA sequences were derived from organisms utilizing the labeled substrate (i.e., contain radioactive elements). A recent study adapted the technique to characterize microbial trophic interactions. Lueders et al. (2006) amended field soil with 13C-labeled Escherichia coli, separated labeled RNA from unlabeled RNA using equilibrium density gradient centrifugation, and then characterized the RNA sequence heterogeneity of the two fractions. Sequences belonging to fungi in the Microascaceae and bacteria in the Xanthomonadaceae, Myxococcales, and Bacteroidetes were associated specifically with the 13C-labeled RNA fraction, suggesting that some organisms in these groups assimilated nutrients derived from the amended E. coli.

6. Summary and Conclusions Soil communities are sensitive indicators of environmental disturbance and recovery. Monitoring soil food web dynamics provides information regarding not just organism abundance but also energy flow, nutrient dynamics, and ecosystem stability. Many current studies do not consider these latter, emergent properties of soil food webs; those that do are advanced in that they attempt to estimate the functional consequences of environmental perturbations, and it is these consequences that many stakeholders are interested in. Evaluating these latter properties is difficult since

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they may not be observed at the spatial and temporal scales used in the experiment. Bacteria, fungi, and their consumers, particularly nematodes, are frequently used for these purposes. Advances in our understanding of food web structure and function should help improve the sensitivity and utility of soil communities by further indicating functionally important components of the soil food web and provide greater predictive power as to how environmental disturbances will influence soil food webs and ecosystem functioning.

ACKNOWLEDGMENTS I thank John Klironomos for reviewing this chapter and the Natural Sciences and Engineering Research Council of Canada for providing a postgraduate scholarship.

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