Skip to main content Accessibility help
×
Hostname: page-component-78c5997874-mlc7c Total loading time: 0 Render date: 2024-11-03T19:17:23.955Z Has data issue: false hasContentIssue false

16 - Empirical Methods of Identifying and Quantifying Trophic Interactions for Constructing Soil Food-Web Models

from Part II - Food Webs: From Traits to Ecosystem Functioning

Published online by Cambridge University Press:  05 December 2017

John C. Moore
Affiliation:
Colorado State University
Peter C. de Ruiter
Affiliation:
Wageningen Universiteit, The Netherlands
Kevin S. McCann
Affiliation:
University of Guelph, Ontario
Volkmar Wolters
Affiliation:
Justus-Liebig-Universität Giessen, Germany
Get access

Summary

Image of the first page of this content. For PDF version, please use the ‘Save PDF’ preceeding this image.'
Type
Chapter
Information
Adaptive Food Webs
Stability and Transitions of Real and Model Ecosystems
, pp. 257 - 286
Publisher: Cambridge University Press
Print publication year: 2017

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Abraham, W.-R. (2014). Applications and impacts of stable isotope probing for analysis of microbial interactions. Journal of Appled Microbiology and Biotechnology, 98, 48174828.Google Scholar
Agustí, N., Bourguet, D., Spataro, T., et al. (2005). Detection, identification and geographical distribution of European corn borer larval parasitoids using molecular markers. Molecular Ecology, 14, 32673274.Google Scholar
Alvarez, H. M. and Steinbüchel, A. (2002). Triacylglycerols in prokaryotic microorganisms. Journal of Applied Microbiology and Biotechnology, 60, 367376.Google ScholarPubMed
Andújar, C., Arribas, P., Ruzicka, F., et al. (2015). Phylogenetic community ecology of soil biodiversity using mitochondrial metagenomics. Molecular Ecology, 24(14), 36033617. doi:10.1111/mec.13195.Google Scholar
Baiser, B., Russell, G. J., and Lockwood, J. L. (2010). Connectance determines invasion success via trophic interactions in model food webs. Oikos, 119, 19701976.Google Scholar
Baker, R., Buckland, A., and Sheaves, M. (2014). Fish gut content analysis: robust measures of diet composition. Fish and Fisheries, 15, 170177.Google Scholar
Bardgett, R. D., Cook, R., Yeates, G. W., and Denton, C. S. (1999). The influence of nematodes on below-ground processes in grassland ecosystems. Plant Soil, 212, 2333.Google Scholar
Berg, M., de Ruiter, P. C., Didden, W. A. M., et al. (2001). Community food web, decomposition and nitrogen mineralisation in a stratified Scots pine forest soil. Oikos 94, 130142.Google Scholar
Berlow, E. L., Neutel, A.-M., Cohen, J. E., et al. (2004). Interaction strengths in food webs: issues and opportunities. Journal of Animal Ecology, 73, 585598.Google Scholar
Bongers, T. (1990). The maturity index: an ecological measure of environmental disturbance based on nematode species composition. Oecologica, 83, 1419.Google Scholar
Bonkowski, M. (2004). Protozoa and plant growth: the microbial loop in soil revisited. New Phytologist, 162, 617631.Google Scholar
Boschker, H. T. S., Nold, S. C., Wellsbury, P., et al. (1998). Direct linking of microbial populations to specific biogeochemical processes by 13C-labelling of biomarkers. Nature, 392, 801805.Google Scholar
Boyer, S., Yeates, G. W., Wratten, S. D., Holyoake, A., and Cruickshank, R. H. (2011). Molecular and morphological analyses of faeces to investigate the diet of earthworm predators: example of a carnivorous land snail endemic to New Zealand. Pedobiologia (Jena), 54, 153158.Google Scholar
Brose, U. (2010). Body-mass constraints on foraging behaviour determine population and food-web dynamics. Functional Ecology, 24, 2834.Google Scholar
Brose, U., Jonsson, T., Berlow, E. L., et al. (2006). Consumer-resource body-size relationships in natural food webs. Ecology, 87, 24112417.Google Scholar
Brose, U., Ehnes, R. B., Rall, B. C., et al. (2008). Foraging theory predicts predator–prey energy fluxes. Journal of Animal Ecology, 77, 10721078.Google Scholar
Buse, T., Ruess, L., and Filser, J. (2013). New trophic biomarkers for Collembola reared on algal diets. Pedobiologia (Jena), 56, 153159.CrossRefGoogle Scholar
Buse, T., Ruess, L., and Filser, J. (2014). Collembola gut passage shapes microbial communities in faecal pellets but not viability of dietary algal cells. Chemoecology, 24, 7984.Google Scholar
Chamberlain, P. M., Bull, I. D., Black, H. I. J., Ineson, P., and Evershed, R. P. (2005). Fatty acid composition and change in Collembola fed differing diets: identification of trophic biomarkers. Soil Biology and Biochemistry, 37, 16081624.Google Scholar
Chen, J., Ferris, H., Scow, K. M., and Graham, K. J. (2001). Fatty acid composition and dynamics of selected fungal-feeding nematodes and fungi. Comparative Biochemistry and Physiology Part B: Biochemistry and Molecular Biology, 130, 135144.Google Scholar
Clare, E. L. (2014). Molecular detection of trophic interactions: emerging trends, distinct advantages, significant considerations and conservation applications. Evolutionary Applications, 7(9), 11441157. doi:10.1111/eva.12225.Google Scholar
Deagle, B. E. and Tollit, D. J. (2007). Quantitative analysis of prey DNA in pinniped faeces: potential to estimate diet composition? Conservation Genetics, 8, 743747.Google Scholar
Deagle, B. E., Kirkwood, R., Jarman, S. N. (2009). Analysis of Australian fur seal diet by pyrosequencing prey DNA in faeces. Molecular Ecology, 18, 20222038.Google Scholar
Deagle, B. E., Jarman, S. N., Coissac, E., Pompanon, F., and Taberlet, P. (2014). DNA metabarcoding and the cytochrome c oxidase subunit I marker. Biology Letters, 10, dx.doi.org/10.1098/rsbl.2014.0562.Google Scholar
de Ruiter, P. C., Moore, J. C., Zwart, K. B., et al. (1993). Simulation of nitrogen mineralization in the below-ground food webs of two winter wheat fields. Journal of Applied Ecology, 30, 95106.Google Scholar
de Ruiter, P. C., Wolters, V., and Moore, J. C. (2005). Dynamics Food Webs: Multispecies Assemblages, Ecosystem Development and Environmental Change. San Diego, CA: Academic Press.CrossRefGoogle Scholar
Drigo, B., Pijl, A. S., Duyts, H., et al. (2010). Shifting carbon flow from roots into associated microbial communities in response to elevated atmospheric CO2. Proceeding of the National Academy of Sciences of the USA, 107, 1093810942.Google Scholar
Eggers, T. and Jones, T. H. (2000). You are what you eat… or are you? Trends in Ecology and Evolution, 15, 265266.Google Scholar
Ferlian, O., Scheu, S., and Pollierer, M. M. (2012). Trophic interactions in centipedes (Chilopoda, Myriapoda) as indicated by fatty acid patterns: variations with life stage, forest age and season. Soil Biology and Biochemistry, 52, 3342.Google Scholar
Ferris, H. (2010a). Contribution of nematodes to the structure and function of the soil food web. Journal of Nematology, 42, 6367.Google Scholar
Ferris, H. (2010b). Form and function: metabolic footprints of nematodes in the soil food web. European Journal of Soil Biology, 46, 97104.Google Scholar
Ferris, H., Bongers, T., and De Goede, R. G. M. (2001). A framework for soil food web diagnostics: extension of the nematode faunal analysis concept. Applied Soil Ecology, 18, 1329.Google Scholar
Freckman, D. W. (1988). Bacterivorous nematodes and organic-matter decomposition. Agriculture Ecosystems and Environment, 24, 195217.Google Scholar
Friedrich, M. W. (2011). Trophic interactions in microbial communities and food webs traced by stable isotope probing of nucleic acids. In Stable Isotope Probing and Related Technologies, ed. Murrell, J. C. and Whiteley, A. S., American Society for Microbiology Press, pp. 203232.Google Scholar
Gariepy, T., Kuhlmann, U., Gillott, C., and Erlandson, M. (2008). A large-scale comparison of conventional and molecular methods for the evaluation of host–parasitoid associations in non-target risk-assessment studies. Journal of Applied Ecology, 45, 708715.Google Scholar
Ghafouri, S. and McGhee, J. (2007). Bacterial residence time in the intestine of Caenorhabditis elegans. Nematology, 9, 8791.Google Scholar
Greenstone, M. H., Rowley, D. L., Weber, D. C., Payton, M. E., and Hawthorne, D. J. (2007). Feeding mode and prey detectability half-lives in molecular gut-content analysis: an example with two predators of the Colorado potato beetle. Bulletin of Entomological Research, 97, 201209.Google Scholar
Greenstone, M. H., Payton, M. E., Weber, D. C., and Simmons, A. M. (2014). The detectability half-life in arthropod predator–prey research: what it is, why we need it, how to measure it, and how to use it. Molecular Ecology, 23, 37993813.Google Scholar
Griffiths, B. S., Ritz, K., Ebblewhite, N., and Dobson, G. (1999). Soil microbial community structure: effects of substrate loading rates. Soil Biology and Biochemistry, 31, 145153.Google Scholar
Harper, G. L., King, R. A., Dodd, C. S., et al. (2005). Rapid screening of invertebrate predators for multiple prey DNA targets. Molecular Ecology, 14, 819827.Google Scholar
Haubert, D., Häggblom, M. M., Scheu, S., and Ruess, L. (2004). Effects of fungal food quality and starvation on the fatty acid composition of Protaphorura fimata (Collembola). Comparative Biochemistry and Physiology Part B: Biochemistry and Molecular Biology, 138, 4152.Google Scholar
Haubert, D., Häggblom, M. M., Langel, R., Scheu, S., and Ruess, L. (2006). Trophic shift of stable isotopes and fatty acids in Collembola on bacterial diets. Soil Biology and Biochemistry, 38, 20042007.CrossRefGoogle Scholar
Haubert, D., Häggblom, M. M., Scheu, S., and Ruess, L. (2008). Effects of temperature and life stage on the fatty acid composition of Collembola. European Journal of Soil Biology, 44, 213219.Google Scholar
Haubert, D., Birkhofer, K., Fließbach, A., et al. (2009). Trophic structure and major trophic links in conventional versus organic farming systems as indicated by carbon stable isotope ratios of fatty acids. Oikos, 118, 15791589.Google Scholar
Heidemann, K., Scheu, S., Ruess, L., and Maraun, M. (2011). Molecular detection of nematode predation and scavenging in oribatid mites: laboratory and field experiments. Soil Biology and Biochemistry, 43, 22292236.Google Scholar
Heidemann, K., Hennies, A., Schakowske, J., et al. (2014a). Free-living nematodes as prey for higher trophic levels of forest soil food webs. Oikos, 123, 11991211.Google Scholar
Heidemann, K., Ruess, L., Scheu, S., and Maraun, M. (2014b). Nematode consumption by mite communities varies in different forest microhabitats as indicated by molecular gut content analysis. Experimental and Applied Acarology, 64, 4960.Google Scholar
Holmstrup, M., Hedlund, K., and Boriss, H. (2002). Drought acclimation and lipid composition in Folsomia candida: implications for cold shock, heat shock and acute desiccation stress. Journal of Insect Physiology, 48, 961970.Google Scholar
Hrček, J. and Godfray, H. C. J. (2015). What do molecular methods bring to host–parasitoid food webs? Trends in Parasitology, 31, 3035.Google Scholar
Huang, W. E., Stoecker, K., Griffiths, R., et al. (2007). Raman–FISH: combining stable-isotope Raman spectroscopy and fluorescence in situ hybridization for the single cell analysis of identity and function. Environmental Microbiology, 9, 18781889.Google Scholar
Hunt, H. W., Coleman, D. C., Ingham, E. R., et al. (1987). The detrital food web in a shortgrass prairie. Biology and Fertility of Soils, 3, 5768.Google Scholar
Hyslop, E. J. (1980). Stomach contents analysis: a review of methods and their application. Journal of Fish Biology, 17, 411429.Google Scholar
Iverson, S. J., Field, C., Bowen, W. D., and Blanchard, W. (2004). Quantitative fatty acid signature analysis: a new method of estimating predator diets. Ecological Monographs, 74, 211235.Google Scholar
Jezbera, J., Hornák, K., and Simek, K. (2005). Food selection by bacterivorous protists: insight from the analysis of the food vacuole content by means of fluorescence in situ hybridization. FEMS Microbiol Ecology, 52, 351363.Google Scholar
Jonsson, T. (2014). Trophic links and the relationship between predator and prey body sizes in food webs. Community Ecology, 15, 5464.Google Scholar
Jousset, A. (2012). Ecological and evolutive implications of bacterial defences against predators. Environmental Microbiology, 14, 18301843.Google Scholar
Jousset, A., Rochat, L., Péchy-Tarr, M., et al. (2009). Predators promote defence of rhizosphere bacterial populations by selective feeding on non-toxic cheaters. ISME Journal, 3, 666674.CrossRefGoogle ScholarPubMed
Juen, A. and Traugott, M. (2005). Detecting predation and scavenging by DNA gut-content analysis: a case study using a soil insect predator–prey system. Oecologia, 142, 344352.Google Scholar
Juen, A. and Traugott, M. (2007). Revealing species-specific trophic links in soil food webs: molecular identification of scarab predators. Molecular Ecology, 16, 15451557.Google Scholar
Jürgens, K. and Simek, K. (2000). Functional response and particle size selection of Halteria cf. grandinella, a common freshwater oligotrichous ciliate. Aquatic Microbial Ecology, 22, 5768.Google Scholar
Kalinkat, G., Rall, B. C., Vucic-Pestic, O., and Brose, U. (2011). The allometry of prey preferences. PLoS One, 6, e25937.CrossRefGoogle ScholarPubMed
Kasper, M. L., Reeson, A. F., Cooper, S. J. B, Perry, K. D., and Austin, A. D. (2004). Assessment of prey overlap between a native (Polistes humilis) and an introduced (Vespula germanica) social wasp using morphology and phylogenetic analyses of 16S rDNA. Molecular Ecology, 13, 20372048.Google Scholar
King, R. A., Read, D. S., Traugott, M., and Symondson, W. O. C. (2008). Molecular analysis of predation: a review of best practice for DNA-based approaches. Molecular Ecology, 17, 947963.Google Scholar
King, R. A., Vaughan, I. P., Bell, J. R., Bohan, D. A., and Symondson, W. O. C. (2010). Prey choice by carabid beetles feeding on an earthworm community analysed using species- and lineage-specific PCR primers. Molecular Ecology, 19, 17211732.Google Scholar
Layman, C. A., Araujo, M. S., Boucek, R., et al. (2012). Applying stable isotopes to examine food-web structure: an overview of analytical tools. Biological Reviews, 87, 545562.Google Scholar
Li, M., Huang, W. E., Gibson, C. M., Fowler, P. W., and Jousset, A. (2013). Stable isotope probing and Raman spectroscopy for monitoring carbon flow in a food chain and revealing metabolic pathway. Analytical Chemistry, 85, 16421649.Google Scholar
Lundgren, J. G. and Fergen, J. K. (2014). Predator community structure and trophic linkage strength to a focal prey. Molecular Ecology, 23, 37903798.CrossRefGoogle ScholarPubMed
MacArthur, R. H. (1972). Strong, or weak, interations? Transactions of the Connecticut Academy of Arts and Sciences, 44, 177188.Google Scholar
Manefield, M., Whiteley, A. S., Griffiths, R. I., and Bailey, M. J. (2002). RNA stable isotope probing, a novel means of linking microbial community function to phylogeny. Rapid Communication in Mass Spectrometry, 16, 21792183.Google Scholar
Maxfield, P. J. and Evershed, R. P. (2011). Phospholipid fatty acid stable isotope probing techniques in microbial ecology. In Stable Isotope Probing and Related Technologies, ed. Murrell, J. C. and Whiteley, A. S., American Society of Microbiology Press, pp. 3771.Google Scholar
May, R. M. (1972). Will a large complex system be stable? Nature, 238, 413414.Google Scholar
May, R. M. (1974). Stability and Complexity in Model Ecosystems. Princeton, NJ: Princeton University Press.Google Scholar
Mayali, X., Weber, P. K., Brodie, E. L., et al. (2012). High-throughput isotopic analysis of RNA microarrays to quantify microbial resource use. ISME Journal, 6, 12101221.Google Scholar
Memmott, J. (2009). Food webs: a ladder for picking strawberries or a practical tool for practical problems? Philosophical Transactions of the Royal Society B: Biological Sciences, 364, 16931699.Google Scholar
Molkentin, J. and Giesemann, A. (2007). Differentiation of organically and conventionally produced milk by stable isotope and fatty acid analysis. Analytical Bioanalytical Chemistry, 388, 297305.Google Scholar
Moore, J. C. and de Ruiter, P. C. (2012). Energetic Food Webs. Oxford, UK: Oxford University Press.Google Scholar
Moore, J. C., de Ruiter, P. C., and Hunt, H. W. (1993). Soil invertebrate/micro-invertebrate interactions: disproportionate effects of species on food web structure and function. Veterinary Parasitology, 48, 247260.Google Scholar
Mora, C. A., Paunescu, D., Grass, R. N., and Stark, W. J. (2014). Silica particles with encapsulated DNA as trophic tracers. Molecular Ecology Resources, 15(2), 231241, doi:10.1111/1755–0998.12299.Google Scholar
Müller-Navarra, D. C., Brett, M. T., Liston, A. M., and Goldman, C. R. (2000). A highly unsaturated fatty acid predicts carbon transfer between primary producers and consumers. Nature, 403, 7477.Google Scholar
Neher, D. A. (2010). Ecology of plant and free-living nematodes in natural and agricultural soil. Annual Review of Phytopathology, 48, 371394.Google Scholar
Neidig, N., Paul, R. J., Scheu, S., and Jousset, A. (2011). Secondary metabolites of Pseudomonas fluorescens CHA0 drive complex non-trophic interactions with bacterivorous nematodes. Microbial Ecology, 61, 853859.Google Scholar
Neutel, A.-M., Heesterbeek, J. A. P., and de Ruiter, P. C. (2002). Stability in real food webs: weak links in long loops. Science, 296, 11201123.Google Scholar
Ngosong, C., Gabriel, E., and Ruess, L. (2012). Use of the signature fatty acid 16:1ω5 as a tool to determine the distribution of arbuscular mycorrhizal fungi in soil. Journal of Lipids, 2012. doi:10.1155/2012/236807.Google Scholar
Ngosong, C., Gabriel, E., and Ruess, L. (2014). Collembola grazing on arbuscular mycorrhiza fungi modulates nutrient allocation in plants. Pedobiologia (Jena), 57, 171179.Google Scholar
O’Neill, R. V. (1969). Indirect estimation of energy fluxes in animal food webs. Journal of Theoretical Biology, 22, 284290.CrossRefGoogle ScholarPubMed
Paine, R. T. (1980). Food webs: linkage, interation strength and community infrastructure. Journal of Animal Ecology, 49, 667685.CrossRefGoogle Scholar
Paine, R. T. (1992). Food-web analysis through field measurement of per capita interaction strength. Nature, 355, 7375.CrossRefGoogle Scholar
Pausch, J., Kramer, S., Scharroba, A., et al. (2015). Small but active: pool size does not matter for carbon incorporation in belowground food webs. Functional Ecology, 30(3), 479489.Google Scholar
Pimm, S. L. (1982). Food Webs. London, UK: Chapman and Hall.Google Scholar
Pollierer, M. M., Scheu, S., and Haubert, D. (2010). Taking it to the next level: trophic transfer of marker fatty acids from basal resource to predators. Soil Biology and Biochemistry, 42, 919925.Google Scholar
Pompanon, F., Deagle, B. E., Symondson, W. O. C., et al. (2012). Who is eating what: diet assessment using next generation sequencing. Molecular Ecology, 21, 19311950.Google Scholar
Pond, D. W., Leakey, R. J. G., and Fallick, A. E. (2006). Monitoring microbial predator–prey interactions: an experimental study using fatty acid biomarker and compound-specific stable isotope techniques. Journal of Plankton Research, 28, 419427.Google Scholar
Radajewski, S., Ineson, P., Parekh, N. R., and Murrell, J. C. (2000). Stable-isotope probing as a tool in microbial ecology. Nature, 403, 646649.Google Scholar
Ruess, L. (2003). Nematode soil faunal analysis of decomposition pathways in different ecosystems. Nematology, 5, 179181.Google Scholar
Ruess, L. and Chamberlain, P. M. (2010). The fat that matters: soil food web analysis using fatty acids and their carbon stable isotope signature. Soil Biology and Biochemistry, 42, 18981910.Google Scholar
Ruess, L. and Ferris, H. (2004). Decomposition pathways and successional changes. Nematology Monographs and Perspectives, 2, 547556.Google Scholar
Ruess, L., Häggblom, M. M., Garciá Zapata, E. J., and Dighton, J. (2002). Fatty acids of fungi and nematodes: possible biomarkers in the soil food chain? Soil Biology and Biochemistry, 34, 745756.Google Scholar
Ruess, L., Häggblom, M. M., Langel, R., and Scheu, S. (2004). Nitrogen isotope ratios and fatty acid composition as indicators of animal diets in belowground systems. Oecologia, 139, 336346.Google Scholar
Ruess, L., Tiunov, A., Haubert, D., et al. (2005a). Carbon stable isotope fractionation and trophic transfer of fatty acids in fungal based soil food chains. Soil Biology Biochemistry, 37, 945953.Google Scholar
Ruess, L., Schütz, K., Haubert, D., et al. (2005b). Application of lipid analysis to understand trophic interactions in soil. Ecology, 86, 20752082.Google Scholar
Ruess, L., Schütz, K., Migge-Kleian, S., et al. (2007). Lipid composition of Collembola and their food resources in deciduous forest stands: implications for feeding strategies. Soil Biology and Biochemistry, 39, 19902000.Google Scholar
Sanders, D., Jones, C. G., Thébault, E., et al. (2014). Integrating ecosystem engineering and food webs. Oikos, 123, 513524.Google Scholar
Scheu, S. (2002). The soil food web: structure and perspectives. European Journal of Soil Biology, 38, 1120.Google Scholar
Scheu, S., Ruess, L., and Bonkowski, M. (2005). Interactions between microorganisms and soil micro- and mesofauna. In Microorganisms in Soil: Roles in Genesis and Functions, ed. Buscot, F. and Varma, A., Berlin: Springer-Verlag, pp. 253277.Google Scholar
Schröter, D., Wolters, V., and de Ruiter, P. C. (2003). C and N mineralisation in the decomposer food webs of a European forest transect. Oikos, 102, 294308.Google Scholar
Seeber, J., Rief, A., Seeber, G. U. H., Meyer, E., and Traugott, M. (2010). Molecular identification of detritivorous soil invertebrates from their faecal pellets. Soil Biology Biochemistry, 42, 12631267.Google Scholar
Selakovic, S., de Ruiter, P. C., and Heesterbeek, H. (2014). Infectious disease agents mediate interaction in food webs and ecosystems. Proceedings of the Royal Society B: Biological Sciences, 281(1777), 20132709.Google Scholar
Sint, D., Raso, L., and Traugott, M. (2012). Advances in multiplex PCR: balancing primer efficiencies and improving detection success. Methods in Ecology and Evolution, 3, 898905.Google Scholar
Stübing, D., Hagen, W., and Schmidt, K. (2003). On the use of lipid biomarkers in marine food web analyses: an experimental case study on the Antarctic krill, Euphausia superba. Limnology and Oceanography, 48, 16851700.Google Scholar
Symondson, W. O. C. (2012). The molecular revolution: using polymerase chain reaction based methods to explore the role of predators in terrestrial food webs. In Biodiversity and Insect Pests: Key Issues for Sustainable Management, ed. Gurr, G. M., Wratten, S. D., Snyder, W. E., and Read, D. M. Y., New York: Wiley and Sons, pp. 166184.CrossRefGoogle Scholar
Thiemann, G. W., Iverson, S. J., and Stirling, I. (2008). Polar bear diets and arctic marine food webs: insights from fatty acid analysis. Ecological Monographs, 78, 591613.Google Scholar
Traugott, M., Kamenova, S., and Ruess, L. (2013). Empirically characterising trophic networks: what emerging DNA-based methods, stable isotope and fatty acid analyses can offer. Advances in Ecological Research, 49, 177224, doi:10.1016/B978-0–12-420002–9.00003–2.Google Scholar
van Dooremalen, C. and Ellers, J. (2010). A moderate change in temperature induces changes in fatty acid composition of storage and membrane lipids in a soil arthropod. Journal Insect Physiology, 56, 178184.Google Scholar
Vestheim, H. and Jarman, S. N. (2008). Blocking primers to enhance PCR amplification of rare sequences in mixed samples: a case study on prey DNA in Antarctic krill stomachs. Frontiers in Zoology, 5, 12, DOI: 10.1186/1742–9994-5–12.CrossRefGoogle ScholarPubMed
von Berg, K., Traugott, M., and Scheu, S. (2012). Scavenging and active predation in generalist predators: a mesocosm study employing DNA-based gut content analysis. Pedobiologia (Jena), 55, 15.Google Scholar
Vuvic-Pestic, O. K., Birkhofer, K., Rall, B. C., Scheu, S., and Brose, U. (2010). Habitat structure and prey aggregation determine the functional response in a soil predator–prey interaction. Pedobiologica, 53, 307312.Google Scholar
Waldner, T. and Traugott, M. (2012). DNA-based analysis of regurgitates: a noninvasive approach to examine the diet of invertebrate consumers. Molecular Ecology Resoures, 12, 669675.Google Scholar
Waldner, T., Sint, D., Juen, A., and Traugott, M. (2013). The effect of predator identity on post-feeding prey DNA detection success in soil-dwelling macro-invertebrates. Soil Biology Biochemistry, 63, 116123.Google Scholar
Wallinger, C., Staudacher, K., Schallhart, N., et al. (2013). The effect of plant identity and the level of plant decay on molecular gut content analysis in a herbivorous soil insect. Molecular Ecology Resoures, 13, 7583.Google Scholar
Wardle, D. A., Verhoef, H. A., and Clarholm, M. (1998). Trophic relationships in the soil microfood-web: predicting the responses to a changing global environment. Global Change Biology, 4, 713727.Google Scholar
White, D. C., Stair, J. O., and Ringelberg, D. B. (1996). Quantitative comparisons of in situ microbial biodiversity by signature biomarker analysis. Journal of Industrial Microbiology, 17, 185196.Google Scholar
Williams, C. T. and Buck, C. L. (2010). Using fatty acids as dietary tracers in seabird trophic ecology: theory, application and limitations. Journal of Ornithology, 151, 531543.Google Scholar
Winemiller, K. O. and Layman, C. A. (2005). Food web science: moving on the path from abstraction to prediction. In Dynamic Food Webs, ed. de Ruiter, P. C., Moore, J. C., and Wolters, V., San Diego: Academic Press, pp. 1023.Google Scholar
Wirta, H. K., Hebert, P. D. N., Kaartinen, R., et al. (2014). Complementary molecular information changes our perception of food web structure. Proceedings of the National Academy of Sciences of the United States of America, 111, 18851890.Google Scholar
Yeates, G. W. (2010). Nematodes in ecological webs. In Encyclopedia of Life Sciences (ELS), New York: John Wiley and Sons. doi:10.1002/9780470015902.a0021913.Google Scholar
Yeates, G. W., Bongers, T., De Goede, R. G., Freckman, D. W., and Georgieva, S. S. (1993). Feeding habits in soil nematode families and genera: an outline for soil ecologists. Journal of Nematology, 25, 315331.Google Scholar
Yeates, G. W., Ferris, H., Moens, T., and van der Putten, W. H. (2009). The role of nematodes in ecosystems. In Nematodes as Environmental Bioindicators, ed. Wilson, M. and Kakouli-Duarte, T., Wallingford, UK: CABI, pp. 144.Google Scholar
Zelles, L. (1999). Fatty acid patterns of phospholipids and lipopolysaccharides in the characterisation of microbial communities in soil: a review. Biology and Fertility of Soils, 29, 111129.Google Scholar
Zhang, G.-F., , Z.-C., Wan, F.-H., and Lövei, G. L. (2007). Real-time PCR quantification of Bemisia tabaci (Homoptera: Aleyrodidae) B-biotype remains in predator guts. Molecular Ecology Notes, 7, 947954.Google Scholar

Save book to Kindle

To save this book to your Kindle, first ensure [email protected] is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

Available formats
×