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The food web in a subterranean ecosystem is driven by intraguild predation

  • 1.

    Mulec, J. Phototrophs in caves. In Cave Ecology (eds Moldovan, O. T. et al.) 91–106 (Springer, Cham, 2018). https://doi.org/10.1007/978-3-319-98852-8_6

    Google Scholar 

  • 2.

    Culver, D. C. & Pipan, T. The Biology of Caves and Other Subterranean Habitats (Oxford University Press Inc., New York, 2009).

    Google Scholar 

  • 3.

    Engel, A. S. Chemoautotrophy. In Encyclopedia of caves 2nd edn (eds White, W. B. & Culver, D. C.) 125–134 (Elsevier, Amsterdam, 2012).

    Google Scholar 

  • 4.

    Kinkle, B. K. & Kane, T. C. Chemolithotrophic microorganisms and their potential role in subsurface environments. In Ecosystems of the World 30 Subterranean Ecosystems (eds Wilkens, H. et al.) 309–319 (Elsevier, Amsterdam, 2000).

    Google Scholar 

  • 5.

    Sarbu, S. M. Movile cave: A chemoautotrophically based groundwater ecosystem. In Ecosystems of the World 30 Subterranean Ecosystems (eds Wilkens, H. et al.) 319–343 (Elsevier, Amsterdam, 2001).

    Google Scholar 

  • 6.

    Simon, K. S., Pipan, T. & Culver, D. C. A conceptual model of the flow and distribution of organic carbon in caves. J. Cave Karst Stud. 69, 279–284 (2007).

    CAS  Google Scholar 

  • 7.

    Camassa, M. M. Food resources. In Encyclopaedia of Caves and Karst Science (ed. Gunn, J.) 755–760 (Fitzroy Dearborn, London, 2004).

    Google Scholar 

  • 8.

    Poulson, T. L. & Lavoie, K. H. (The trophic basis of subsurface ecosystems. In Ecosystems of the World 30 Subterranean Ecosystems (eds Wilkens, H. et al.) 323–334 (Elsevier, Amsterdam, 2000).

    Google Scholar 

  • 9.

    Gibert, J. & Deharveng, L. Subterranean ecosystems: A truncated functional biodiversity. Bioscience 52(6), 473–481. https://doi.org/10.1641/0006-3568(2002)052[0473:SEATFB]2.0 (2002).

    Article  Google Scholar 

  • 10.

    Chen, B. & Wise, D. H. Bottom-up limitation of predaceous arthropods in a detritus-based terrestrial food web. Ecology 80(3), 761–772. https://doi.org/10.2307/177015 (1999).

    Article  Google Scholar 

  • 11.

    Venarsky, M. P. & Huntsman, B. M. Food webs in caves. In Cave Ecology (eds Moldovan, O. T. et al.) 309–331 (Springer, Cham, 2018). https://doi.org/10.1007/978-3-319-98852-8_14

    Google Scholar 

  • 12.

    Gnaspini, P. Guano communities. In Encyclopedia of caves 2nd edn (eds White, W. B. & Culver, D. C.) 357–364 (Elsevier, Amsterdam, 2012).

    Google Scholar 

  • 13.

    Ipsen, A. The Segeberger Höhle—A phylogenetically young cave ecosystem in northern Germany. In Ecosystems of the World 30. Subterranean Ecosystems (eds Wilkens, H. et al.) 569–579 (Elsevier, Amsterdam, 2000).

    Google Scholar 

  • 14.

    Stone, F. D., Howarth, F. G., Hoch, H. & Asche, M. Root communities in lava tubes. In Encyclopedia of Caves 2nd edn (eds White, W. B. & Culver, D. C.) 658–664 (Elsevier, Amsterdam, 2012).

    Google Scholar 

  • 15.

    Mammola, S., Piano, E. & Isaia, M. Step back! Niche dynamics in cave-dwelling predators. Acta Oecol. 75, 35–42. https://doi.org/10.1016/j.actao.2016.06.011 (2016).

    ADS  Article  Google Scholar 

  • 16.

    Mammola, S. & Isaia, M. Cave communities and species interactions. In Cave Ecology (eds Moldovan, O. T. et al.) 255–269 (Springer, Cham, 2018). https://doi.org/10.1007/978-3-319-98852-8_11

    Google Scholar 

  • 17.

    Scheu, S. & Setälä, H. Multitrophic interactions in decomposer food webs. In Multitrophic Interactions in Terrestrial Systems (eds Tscharntke, T. & Hawkins, B. A.) 223–264 (Cambridge, Cambridge University Press, 2001).

    Google Scholar 

  • 18.

    Wood, P. J. Subterranean ecology. In Encyclopaedia of Caves and Karst Science (ed. Gunn, J.) 1514–1519 (Fitzroy Dearborn, London, 2004).

    Google Scholar 

  • 19.

    Pekár, S., García, L. F. & Viera, C. Trophic niche and trophic adaptations of prey specialised spiders of the Neotropics: A guide. In Behavioural Ecology of Neotropical Spiders (eds Viera, C. & Gonzaga, M. O.) 247–274 (Springer, Cham, 2017).

    Google Scholar 

  • 20.

    Pohlman, J. W., Iliffe, T. M. & Cifuentes, L. A. A stable isotope study of organic cycling and the ecology of an anchialine cave ecosystem. Mar. Ecol. Prog. Ser. 155, 17–27 (1997).

    ADS  CAS  Article  Google Scholar 

  • 21.

    Pohlman, J. W., Cifuentes, L. A. & Iliffe, T. M. Food web dynamics and biogeochemistry of anchialine caves: A stable isotope approach. In Ecosystems of the World 30 Subterranean Ecosystems (eds Wilkens, H. et al.) 345–357 (Elsevier, Amsterdam, 2000).

    Google Scholar 

  • 22.

    Sarbu, S. M., Galdenzi, S., Menichetti, M. & Gentile, G. Geology and biology of the Frasassi caves in Central Italy: An ecological multi-disciplinary study of a hypogenic underground karst system. In Ecosystems of the World 30 Subterranean Ecosystems (eds Wilkens, H. et al.) 359–378 (Elsevier, Amsterdam, 2000).

    Google Scholar 

  • 23.

    Eitzinger, B., Micic, A., Körner, M., Traugott, M. & Scheu, S. Unveiling soil food web links: New PCR assays for detection of prey DNA in the gut of soil arthropod predators. Soil Biol. Biochem. 57, 943–945. https://doi.org/10.1016/j.soilbio.2012.09.001 (2013).

    CAS  Article  Google Scholar 

  • 24.

    Juen, A. & Traugott, M. Revealing species-specific trophic links in soil food webs: Molecular identification of scarab predators. Mol. Ecol. 16, 1545–1557. https://doi.org/10.1111/j.1365-294X.2007.03238.x (2007).

    CAS  Article  PubMed  Google Scholar 

  • 25.

    King, R. A., Read, D. S., Traugott, M. & Symondson, W. O. C. Molecular analysis of predation: A review of best practice for DNA-based approaches. Mol. Ecol. 17, 947–963. https://doi.org/10.1111/j.1365-294X.2007.03613.x (2008).

    CAS  Article  PubMed  Google Scholar 

  • 26.

    Symondson, W. O. C. Molecular identification of prey in predator diets. Mol. Ecol. 11(4), 627–641. https://doi.org/10.1046/j.1365-294x.2002.01471.x (2002).

    CAS  Article  PubMed  Google Scholar 

  • 27.

    Traugott, M., Kamenova, S., Ruess, L., Seeber, J. & Plantegenest, M. Empirically characterising trophic networks: What emerging DNA-based methods, stable isotope and fatty acid analyses can offer. Adv. Ecol. Res. 49, 177–224. https://doi.org/10.1016/B978-0-12-420002-9.00003-2 (2013).

    Article  Google Scholar 

  • 28.

    Kováč, Ľ. et al. Terrestrial arthropods of the Domica Cave system and the Ardovská Cave (Slovak Karst): Principal microhabitats and diversity. In Contributions to Soil Zoology in Central Europe I (eds Tajovský, K. et al.) 61–70 (ISB AS CR, České Budějovice, 2005).

    Google Scholar 

  • 29.

    Kováč, Ľ. et al. The cave biota of Slovakia. Speleologia Slovaca 5. (Liptovský Mikuláš, State Nature Conservancy SR, Slovak Caves Administration, 2014). https://doi.org/10.13140/2.1.3473.0569

  • 30.

    Kováč, Ľ, Parimuchová, A. & Miklisová, D. Distributional patterns of cave Collembola (Hexapoda) in association with habitat conditions, geography and subterranean refugia in the Western Carpathians. Biol. J. Linn. Soc. Lond. 119(3), 571–592. https://doi.org/10.1111/bij.12555 (2016).

    Article  Google Scholar 

  • 31.

    Smrž, J., Kováč, Ľ, Mikeš, J. & Lukešová, A. Microwhip scorpions (Palpigradi) feed on heterotrophic Cyanobacteria in Slovak caves: A curiosity among Arachnida. PLoS ONE 8(10), e75989. https://doi.org/10.1371/journal.pone.0075989 (2013).

    ADS  CAS  Article  PubMed  PubMed Central  Google Scholar 

  • 32.

    Pekár, S., Coddington, J. A. & Blackledge, T. Evolution of stenophagy in spiders (Araneae): Evidence based on the comparative analysis of spider diets. Evolution 66(3), 776–806. https://doi.org/10.1111/j.1558-5646.2011.01471.x (2012).

    Article  Google Scholar 

  • 33.

    Alderweireldt, M. Prey selection and prey capture strategies of linyphiid spiders in highinput agricultural fields. Bull. Br. Arachnol. Soc. 9, 300–308 (1994).

    Google Scholar 

  • 34.

    Lukić, M., Collembola in caves. Croatian Biospeleological Society, DVD, 10.25 min (2012).

  • 35.

    Roewer, C. F. Palpigradi. In Klassen und Ordnungen des Tierreichs 5: Arthropoda IV: Arachnoidea (ed. Bronns, H. G.) 640–707 (Akademische Verlagsgesellschaft MBH, Leipzig, 1932).

    Google Scholar 

  • 36.

    van der Hammen, L. Comparative studies in Chelicerata II. Epimerata (Palpigradi and Actinotrichida). Zool. Verh. 196, 3–70 (1982).

    Google Scholar 

  • 37.

    Wheeler, W. M. A singular arachnid Koenenia mirabilis (Grassi) occurring in Texas. Am. Nat. 34, 837–850 (1900).

    Article  Google Scholar 

  • 38.

    Harwood, J. D., Phillips, S. W., Sunderland, K. D. & Symondson, W. O. C. Secondary predation: quantification of food chain errors in an aphid–spider–carabid system using monoclonal antibodies. Mol. Ecol. 10(8), 2049–2057. https://doi.org/10.1046/j.0962-1083.2001.01349.x (2001).

    CAS  Article  PubMed  Google Scholar 

  • 39.

    Szafranek, P., Lewandowski, M. & Kozak, M. Prey preference and life tables of the predatory mite Parasitus bituberosus (Acari: Parasitidae) when offered various prey combinations. Exp. Appl. Acarol. 61(1), 53–67. https://doi.org/10.1007/s10493-013-9701-y (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  • 40.

    Al-Amidi, A. H. K. & Downes, M. J. Parasitus bituberosus (Acari: Parasitidae), a possible agent for biological control of Heteropeza pygmaea (Diptera: Cecidomyiidae) in mushroom compost. Exp. Appl. Acarol. 8(1–2), 13–25 (1990).

    Article  Google Scholar 

  • 41.

    Adams, B. J. & Nguyen, K. B. Nematode parasites of insects. In Encyclopedia of Entomology (ed. Capinera, J. L.) 2577–2584 (Springer, Cham, 2008).

    Google Scholar 

  • 42.

    Cokendolpher, J. C. Pathogens and parasites of opiliones (arthropoda: arachnida). J. Arachnol. 21(2), 120–146 (1993).

    Google Scholar 

  • 43.

    Kruse, P. D., Toft, S. & Sunderland, K. D. Temperature and prey capture: Opposite relationships in two predator taxa. Ecol. Entomol. 33(2), 305–312. https://doi.org/10.1111/j.1365-2311.2007.00978.x (2008).

    Article  Google Scholar 

  • 44.

    Krooss, S. & Schaefer, M. How predacious are predators? A study on Ocypus similis, a rove beetle of cereal fields. Ann. Appl. Biol. 133(1), 1–16. https://doi.org/10.1111/j.1744-7348.1998.tb05797.x (1998).

    Article  Google Scholar 

  • 45.

    Waldbauer, G. P. & Friedman, S. Self-selection of optimal diets by insects. Annu. Rev. Entomol. 36(1), 43–63. https://doi.org/10.1146/annurev.en.36.010191.000355 (1991).

    Article  Google Scholar 

  • 46.

    Mayntz, D. & Toft, S. Nutrient composition of the prey’s diet affects growth and survivorship of a generalist predator. Oecologia 127, 207–213. https://doi.org/10.1007/s004420000591 (2001).

    ADS  Article  PubMed  Google Scholar 

  • 47.

    Finke, D. L. & Denno, R. F. Intraguild predation diminished in complex-structured vegetation: implications for prey suppression. Ecology 83, 643–652. https://doi.org/10.2307/3071870 (2002).

    Article  Google Scholar 

  • 48.

    Staudacher, K. et al. Habitat heterogeneity induces rapid changes in the feeding behaviour of generalist arthropod predators. Funct. Ecol. 32(3), 809–819. https://doi.org/10.1111/1365-2435.13028 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  • 49.

    Finke, D. L. & Denno, R. F. Predator diversity and the functioning of ecosystems: the role of intraguild predation in dampening trophic cascades. Ecol. Lett. 8, 1299–1306. https://doi.org/10.1111/j.1461-0248.2005.00832.x (2005).

    Article  Google Scholar 

  • 50.

    Schausberger, P. & Croft, B. A. Nutritional benefits of intraguild predation and cannibalism among generalist and specialist phytoseiid mites. Ecol. Entomol. 25(4), 473–480. https://doi.org/10.1046/j.1365-2311.2000.00284.x (2000).

    Article  Google Scholar 

  • 51.

    Schausberger, P. Cannibalism among phytoseiid mites: a review. Exp. Appl. Acarol. 29(3/4), 173–191. https://doi.org/10.1023/a:1025839206394 (2003).

    Article  PubMed  Google Scholar 

  • 52.

    Elgar, M. A. & Crespi, B. J. Cannibalism: Ecology and Evolution Among Diverse Taxa (Oxford University Press, Oxford, 1992).

    Google Scholar 

  • 53.

    Polis, G. A. The evolution and dynamics of intraspecific predation. Annu. Rev. Ecol. Syst. 12(1), 225–251. https://doi.org/10.1146/annurev.es.12.110181.001301 (1981).

    Article  Google Scholar 

  • 54.

    Fagan, W. F. et al. Nitrogen in insects: Implications for trophic complexity and species diversification. Am. Nat. 160(6), 784–802. https://doi.org/10.1086/343879 (2002).

    Article  Google Scholar 

  • 55.

    Fagan, W. F. & Denno, R. F. Stoichiometry of actual vs. potential predator–prey interactions: Insights into nitrogen limitation for arthropod predators. Ecol. Lett. 7(9), 876–883. https://doi.org/10.1111/j.1461-0248.2004.00641.x (2004).

    Article  Google Scholar 

  • 56.

    Denno, R. F. & Fagan, W. F. Might nitrogen limitation promote omnivory among carnivorous arthropods?. Ecology 84(10), 2522–2531. https://doi.org/10.1890/02-0370 (2003).

    Article  Google Scholar 

  • 57.

    Snyder, W. E., Joseph, S. B., Preziosi, R. F. & Moore, A. J. Nutritional benefits of cannibalism for the lady beetle Harmonia axyridis (Coleoptera: Coccinellidae) when prey quality is poor. Environ. Entomol. 29(6), 1173–1179. https://doi.org/10.1603/0046-225x-29.6.1173 (2000).

    Article  Google Scholar 

  • 58.

    Nováková, A. et al. Feeding sources of invertebrates in the Ardovská Cave and Domica Cave systems: preliminary results. In Contributions to Soil Zoology in Central Europe I (eds Tajovský, K. et al.) 107–112 (ISB AS CR, České Budějovice, 2005).

    Google Scholar 

  • 59.

    Crossley, D. & Blair, J. M. A high efficiency, “low-technology” Tullgren-type extractor for soil microarthropods. Agric. Ecosyst. Environ. 34, 187–192 (1991).

    Article  Google Scholar 

  • 60.

    Folmer, O., Black, M., Hoeh, W., Lutz, R. & Vrijenhoek, R. DNA primers for amplification of mitochondrial cytochrome c oxidase subunit I from diverse metazoan invertebrates. Mol. Mar. Biol. Biotechnol. 3(5), 294–299 (1994).

    CAS  PubMed  Google Scholar 

  • 61.

    de Groot, A. G., Laros, I. & Geisen, S. Molecular identification of soil eukaryotes and focused approaches targeting protist and faunal groups using high-throughput meta-barcoding methods in molecular biology. Methods Mol. Biol. 1399, 125–140. https://doi.org/10.1007/978-1-4939-3369-3_7 (2016).

    CAS  Article  Google Scholar 

  • 62.

    Aronesty, E. Comparison of sequencing utility programs. Open Bioinform. J. 7(1), 1–8. https://doi.org/10.2174/1875036201307010001 (2013).

    MathSciNet  Article  Google Scholar 

  • 63.

    Martin, M. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet J. 17, 10–12. https://doi.org/10.14806/ej.17.1.200 (2011).

    Article  Google Scholar 

  • 64.

    Mahé, F., Rognes, T., Quince, C., de Vargas, C. & Dunthorn, M. Swarm: robust and fast clustering method for amplicon-based studies. PeerJ. 2, e593 (2014).

    Article  Google Scholar 

  • 65.

    Belshaw, R., Lopez-Vaamonde, C., Degerli, N. & Quicke, D. L. J. Paraphyletic taxa and taxonomic chaining: Evaluation the classification of braconine wasps (Hymenoptera: Braconidae) using 28S D2–3 rDNA sequences and morphological characters. Biol. J. Linn. Soc. Lond. 73(4), 411–424. https://doi.org/10.1111/j.1095-8312.2001.tb01370.x (2001).

    Article  Google Scholar 

  • 66.

    Hurlbert, S. H. The measurement of niche overlap and some relatives. Ecology 59(1), 67–77. https://doi.org/10.2307/1936632 (1978).

    Article  Google Scholar 

  • 67.

    Novakowski, G. C., Hahn, N. S. & Fugi, R. Diet seasonality and food overlap of the fish assemblage in a pantanal pond. Neotrop. Ichthyol. 6(4), 567–576. https://doi.org/10.1590/S1679-62252008000400004 (2008).

    Article  Google Scholar 

  • 68.

    Pianka, E. R. The structure of lizard communities. Annu. Rev. Ecol. Syst. 4(1), 53–74. https://doi.org/10.1146/annurev.es.04.110173.000413 (1973).

    Article  Google Scholar 

  • 69.

    Pekár, S. & Brabec, M. Modern Analysis of Biological Data. Generalized Linear Models in R (MUNI Press, Brno, 2016).

    Google Scholar 

  • 70.

    R Core Team. R: A Language and Environment for Statistical Computing. (R Foundation for Statistical Computing, Vienna). https://www.R-project.org/ (2017).

  • 71.

    Breheny, P. & Burchett, W. Visualization of regression models using visreg. R J. 9, 56–71 (2017).

    Article  Google Scholar 

  • 72.

    Kučera, B. Krasová morfologie a vývoj Ardovské jeskyně v Jihoslovenském krasu. Československý Kras. 16, 41–56 (1964) ([in Czech]).

    Google Scholar 


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