1932

Abstract

Food webs are a major focus and organizing theme of ecology, but the data used to assemble them are deficient. Early debates over food-web data focused on taxonomic resolution and completeness, lack of which had produced spurious inferences. Recent data are widely believed to be much better and are used extensively in theoretical and meta-analytic research on network ecology. Confidence in these data rests on the assumptions () that empiricists correctly identified consumers and their foods and () that sampling methods were adequate to detect a near-comprehensive fraction of the trophic interactions between species. Abundant evidence indicates that these assumptions are often invalid, suggesting that most topological food-web data may remain unreliable for inferences about network structure and underlying ecological and evolutionary processes. Morphologically cryptic species are ubiquitous across taxa and regions, and many trophic interactions routinely evade detection by conventional methods. Molecular methods have diagnosed the severity of these problems and are a necessary part of the cure.

Loading

Article metrics loading...

/content/journals/10.1146/annurev-ecolsys-110218-024908
2020-11-02
2024-12-07
Loading full text...

Full text loading...

/deliver/fulltext/ecolsys/51/1/annurev-ecolsys-110218-024908.html?itemId=/content/journals/10.1146/annurev-ecolsys-110218-024908&mimeType=html&fmt=ahah

Literature Cited

  1. Allesina S, Tang S. 2012. Stability criteria for complex ecosystems. Nature 483:205–8
    [Google Scholar]
  2. Araujo MS, Bolnick DI, Layman CA 2011. The ecological causes of individual specialization. Ecol. Lett. 14:948–58
    [Google Scholar]
  3. Arias-Penna DC, Whitfield JB, Janzen DH, Hallwachs W, Dyer LA et al. 2019. A species-level taxonomic review and host associations of Glyptapanteles (Hymenoptera, Braconidae, Microgastrinae) with an emphasis on 136 new reared species from Costa Rica and Ecuador. ZooKeys 890:1–685
    [Google Scholar]
  4. Atkins JL, Long RA, Pansu J, Daskin JH, Potter AB et al. 2019. Cascading impacts of large-carnivore extirpation in an African ecosystem. Science 364:173–77
    [Google Scholar]
  5. Balme GA, le Roex N, Rogan MS, Hunter LTB 2019. Ecological opportunity drives individual dietary specialization in leopards. J. Anim. Ecol. 89:589–600
    [Google Scholar]
  6. Barton BT, Hill JG, Wolff CL, Newsome TM, Ripple WJ, Lashley MA 2020. Grasshopper consumption by grey wolves and implications for ecosystems. Ecology 101:e02892
    [Google Scholar]
  7. Bascompte J, Jordano P. 2014. Mutualistic Networks Princeton, NJ: Princeton Univ. Press
    [Google Scholar]
  8. Bascompte J, Jordano P, Melián CJ, Olesen JM 2003. The nested assembly of plant-animal mutualistic networks. PNAS 100:9383–87
    [Google Scholar]
  9. Baskerville EB, Dobson AP, Bedford T, Allesina S, Anderson TM, Pascual M 2011. Spatial guilds in the Serengeti food web revealed by a Bayesian group model. PLOS Comput. Biol. 7:e1002321
    [Google Scholar]
  10. Bastolla U, Fortuna MA, Pascual-García A, Ferrera A, Luque B, Bascompte J 2009. The architecture of mutualistic networks minimizes competition and increases biodiversity. Nature 458:1018–20
    [Google Scholar]
  11. Bison M, Ibanez S, Redjadj C, Boyer F, Coissac E et al. 2015. Upscaling the niche variation hypothesis from the intra- to the inter-specific level. Oecologia 179:835–42
    [Google Scholar]
  12. Blüthgen N. 2010. Why network analysis is often disconnected from community ecology: a critique and an ecologist's guide. Basic Appl. Ecol. 11:185–95
    [Google Scholar]
  13. Bohan DA, Vacher C, Tamaddoni-Nezhad A, Raybould A, Dumbrell AJ, Woodward G 2017. Next-generation global biomonitoring: large-scale, automated reconstruction of ecological networks. Trends Ecol. Evol. 32:477–87
    [Google Scholar]
  14. Bortolus A. 2008. Error cascades in the biological sciences: the unwanted consequences of using bad taxonomy in ecology. Ambio 37:114–18
    [Google Scholar]
  15. Bosch J, González AMM, Rodrigo A, Navarro D 2009. Plant-pollinator networks: adding the pollinator's perspective. Ecol. Lett. 12:409–19
    [Google Scholar]
  16. Bowser AK, Diamond AW, Addison JA 2013. From puffins to plankton: a DNA-based analysis of a seabird food chain in the northern Gulf of Maine. PLOS ONE 8:e83152
    [Google Scholar]
  17. Branco PS, Merkle JA, Pringle RM, Pansu J, Potter AB et al. 2019. Determinants of elephant foraging behaviour in a coupled human‐natural system: Is brown the new green. J. Anim. Ecol. 88:780–92
    [Google Scholar]
  18. Briand F, Cohen JE. 1984. Community food webs have scale-invariant structure. Nature 307:264–67
    [Google Scholar]
  19. Buss IO. 1961. Some observations on food habits and behavior of the African elephant. J. Wildl. Manag. 25:131–48
    [Google Scholar]
  20. Cirtwill AR, Stouffer DB, Romanuk TN 2015. Latitudinal gradients in biotic niche breadth vary across ecosystem types. Proc. R. Soc. B 282:20151589
    [Google Scholar]
  21. Clegg T, Ali M, Beckerman AP 2018. The impact of intraspecific variation on food web structure. Ecology 99:2712–20
    [Google Scholar]
  22. Cohen JE. 1978. Food Webs and Niche Space Princeton, NJ: Princeton Univ. Press
    [Google Scholar]
  23. Cohen JE. 1989. Food webs and community structure. Perspectives in Ecological Theory J Roughgarden, RM May, SA Levin 181–202 Princeton, NJ: Princeton Univ. Press
    [Google Scholar]
  24. Cohen JE, Beaver RA, Cousins SH, DeAngelis DL, Goldwasser L et al. 1993. Improving food webs. Ecology 74:252–58
    [Google Scholar]
  25. Cohen JE, Briand F. 1984. Trophic links of community food webs. PNAS 81:4105–9
    [Google Scholar]
  26. Cohen JE, Schittler DN, Raffaelli DG, Reuman DC 2009. Food webs are more than the sum of their tritrophic parts. PNAS 106:22335–40
    [Google Scholar]
  27. Coverdale TC, Kartzinel TR, Grabowski KL, Shriver RK, Hassan AA et al. 2016. Elephants in the understory: opposing direct and indirect effects of consumption and ecosystem engineering by megaherbivores. Ecology 97:3219–30
    [Google Scholar]
  28. Craine JM, Towne EG, Miller M, Fierer N 2015. Climatic warming and the future of bison as grazers. Sci. Rep. 5:16738
    [Google Scholar]
  29. Cristescu ME, Hebert PDN. 2018. Uses and misuses of environmental DNA in biodiversity science and conservation. Annu. Rev. Ecol. Evol. Syst. 49:209–30
    [Google Scholar]
  30. De Angelis DL. 1975. Stability and connectance in food web models. Ecology 56:238–43
    [Google Scholar]
  31. de Visser SN, Freymann BP, Olff H 2011. The Serengeti food web: empirical quantification and analysis of topological changes under increasing human impact. J. Anim. Ecol. 80:484–94
    [Google Scholar]
  32. Deagle BE, Chiaradia A, McInnes J, Jarman SN 2010. Pyrosequencing faecal DNA to determine diet of little penguins: Is what goes in what comes out. Conserv. Genet. 11:2039–48
    [Google Scholar]
  33. Deagle BE, Kirkwood R, Jarman SN 2009. Analysis of Australian fur seal diet by pyrosequencing prey DNA in faeces. Mol. Ecol. 18:2022–38
    [Google Scholar]
  34. Deagle BE, Thomas AC, McInnes JC, Clarke LJ, Vesterinen EJ et al. 2019. Counting with DNA in metabarcoding studies: How should we convert sequence reads to dietary data. Mol. Ecol. 28:391–406
    [Google Scholar]
  35. Deagle BE, Thomas AC, Shaffer AK, Trites AW, Jarman SN 2013. Quantifying sequence proportions in a DNA-based diet study using Ion Torrent amplicon sequencing: which counts count. Mol. Ecol. Res. 13:620–33
    [Google Scholar]
  36. Delmas E, Besson M, Brice M-H, Burkle LA, Dalla Riva GV et al. 2019. Analysing ecological networks of species interactions. Biol. Rev. 94:16–36
    [Google Scholar]
  37. Desjardins-Proulx P, Laigle I, Poisot T, Gravel D 2017. Ecological interactions and the Netflix problem. PeerJ 5:e3644
    [Google Scholar]
  38. Dobson A. 2009. Food-web structure and ecosystem services: insights from the Serengeti. Phil. Trans. R. Soc. B 364:1665–82
    [Google Scholar]
  39. Domínguez-García V, Dakos V, Kéfi S 2019. Unveiling dimensions of stability in complex ecological networks. PNAS 116:25714–20
    [Google Scholar]
  40. Dormann CF, Fründ J, Schaefer HM 2017. Identifying causes of patterns in ecological networks: opportunities and limitations. Annu. Rev. Ecol. Evol. Syst. 48:559–84
    [Google Scholar]
  41. Drymon JM, Feldheim K, Fournier AMV, Seubert EA, Jefferson AE et al. 2019. Tiger sharks eat songbirds: scavenging a windfall of nutrients from the sky. Ecology 100:e02728
    [Google Scholar]
  42. Dudley JP, Hang'Ombe BM, Leendertz FH, Dorward LJ, de Castro J et al. 2016. Carnivory in the common hippopotamus Hippopotamus amphibius: implications for the ecology and epidemiology of anthrax in African landscapes. Mammal Rev 46:191–203
    [Google Scholar]
  43. Dunne JA, Williams RJ, Martinez ND 2002. Food-web structure and network theory: the role of connectance and size. PNAS 99:12917–22
    [Google Scholar]
  44. Egli L, LeVan KE, Work TT 2020. Taxonomic error rates affect interpretations of a national-scale ground beetle monitoring program at National Ecological Observatory Network. Ecosphere 11:e03035
    [Google Scholar]
  45. Emrich MA, Clare EL, Symondson WOC, Koenig SE, Fenton MB 2014. Resource partitioning by insectivorous bats in Jamaica. Mol. Ecol. 23:3648–56
    [Google Scholar]
  46. Evans DM, Kitson JJN, Lunt DH, Straw NA, Pocock MJO 2016. Merging DNA metabarcoding and ecological network analysis to understand and build resilient terrestrial ecosystems. Funct. Ecol. 30:1904–16
    [Google Scholar]
  47. Fernandez-Triana JL, Whitfield JB, Rodriguez JJ, Smith MA, Janzen DH et al. 2014. Review of Apanteles sensu strictu (Hymenoptera, Braconidae, Microgastrinae) from Area de Conservación Guanacaste, northwestern Costa Rica, with keys to all described species from Mesoamerica. ZooKeys 383:1–565
    [Google Scholar]
  48. Fort H, Vázquez DP, Lan BL 2016. Abundance and generalisation in mutualistic networks: solving the chicken-and-egg dilemma. Ecol. Lett. 19:4–11
    [Google Scholar]
  49. Fründ J, McCann KS, Williams NM 2016. Sampling bias is a challenge for quantifying specialization and network structure: lessons from a quantitative niche model. Oikos 125:502–13
    [Google Scholar]
  50. Gaiarsa MP, Guimarães PR Jr 2019. Interaction strength promotes robustness against cascading effects in mutualistic networks. Sci. Rep. 9:676
    [Google Scholar]
  51. Gill BA, Musili PM, Kurukura S, Hassan AA, Goheen JR et al. 2019. Plant DNA‐barcode library and community phylogeny for a semi‐arid East African savanna. Mol. Ecol. Res. 19:838–46
    [Google Scholar]
  52. Gilljam D, Curtsdotter A, Ebenman B 2015. Adaptive rewiring aggravates the effects of species loss in ecosystems. Nat. Commun. 6:8412
    [Google Scholar]
  53. Goheen JR, Palmer TM, Charles GK, Helgen KM, Kinyua SN et al. 2013. Piecewise disassembly of a large-herbivore community across a rainfall gradient: the UHURU experiment. PLOS ONE 8:e55192
    [Google Scholar]
  54. Gotelli NJ. 2004. A taxonomic wish-list for community ecology. Phil. Trans. R. Soc. B 359:585–97
    [Google Scholar]
  55. Grilli J, Rogers T, Allesina S 2016. Modularity and stability in ecological communities. Nat. Commun. 7:12031
    [Google Scholar]
  56. Guyton JA, Pansu J, Hutchinson MC, Kartzinel TR, Potter AB et al. 2020. Trophic rewilding revives biotic resistance to shrub invasion. Nat. Ecol. Evol. 4:71224
    [Google Scholar]
  57. Hall SJ, Raffaelli DG. 1993. Food webs: theory and reality. Adv. Ecol. Res. 24:187–239
    [Google Scholar]
  58. Hansen RM, Mugambi MM, Bauni SM 1985. Diets and trophic ranking of ungulates of the northern Serengeti. J. Wildl. Manag. 49:823–29
    [Google Scholar]
  59. Hebert PDN, Cywinska A, Ball SL, deWaard JR 2003. Biological identifications through DNA barcodes. Proc. R. Soc. B 270:313–21
    [Google Scholar]
  60. Hebert PDN, Penton EH, Burns JM, Janzen DH, Hallwachs W 2004. Ten species in one: DNA barcoding reveals cryptic species in the neotropical skipper butterfly Astraptes fulgerator. . PNAS 101:14812–17
    [Google Scholar]
  61. Hollingsworth PM, Graham SW, Little DP 2011. Choosing and using a plant DNA barcode. PLOS ONE 6:e19254
    [Google Scholar]
  62. Hrcek J, Miller SE, Quicke DLJ, Smith MA 2011. Molecular detection of trophic links in a complex insect host-parasitoid food web. Mol. Ecol. Res. 11:786–94
    [Google Scholar]
  63. Ings TC, Montoya JM, Bascompte J, Blüthgen N, Brown L et al. 2009. Ecological networks—beyond food webs. J. Anim. Ecol. 78:253–69
    [Google Scholar]
  64. Jacquet C, Moritz C, Morissette L, Legagneux P, Massol F et al. 2016. No complexity-stability relationship in empirical ecosystems. Nat. Commun. 7:12573
    [Google Scholar]
  65. James A, Pitchford JW, Plank MJ 2012. Disentangling nestedness from models of ecological complexity. Nature 487:227–30
    [Google Scholar]
  66. James A, Pitchford JW, Plank MJ 2013. James et al. reply. Nature 500:E2–3
    [Google Scholar]
  67. Janzen DH. 1979. New horizons in the biology of plant defenses. Herbivores: Their Interaction with Secondary Plant Metabolites GA Rosenthal, DH Janzen 331–50 New York, NY: Academic, 1st ed..
    [Google Scholar]
  68. Janzen DH. 2004. Now is the time. Phil. Trans. R. Soc. B 359:731–32
    [Google Scholar]
  69. Janzen DH, Burns JM, Cong Q, Hallwachs W, Dapkey T et al. 2017. Nuclear genomes distinguish cryptic species suggested by their DNA barcodes and ecology. PNAS 114:8313–18
    [Google Scholar]
  70. Janzen DH, Hallwachs W. 2016. DNA barcoding the Lepidoptera inventory of a large complex tropical conserved wildland, Area de Conservacion Guanacaste, northwestern Costa Rica. Genome 59:641–60
    [Google Scholar]
  71. Janzen DH, Hallwachs W, Blandin P, Burns JM, Cadiou J-M et al. 2009. Integration of DNA barcoding into an ongoing inventory of complex tropical biodiversity. Mol. Ecol. Res. 9:1–26
    [Google Scholar]
  72. Jordan MJR. 2005. Dietary analysis for mammals and birds: a review of field techniques and animal-management applications. Int. Zoo Yearb. 39:108–16
    [Google Scholar]
  73. Jordano P. 2016. Sampling networks of ecological interactions. Funct. Ecol. 30:1883–93
    [Google Scholar]
  74. Kaartinen R, Stone GN, Hearn J, Lohse K, Roslin T 2010. Revealing secret liaisons: DNA barcoding changes our understanding of food webs. Ecol. Entomol. 35:623–38
    [Google Scholar]
  75. Kartzinel TR, Chen PA, Coverdale TC, Erickson DL, Kress WJ et al. 2015. DNA metabarcoding illuminates dietary niche partitioning by African large herbivores. PNAS 112:8019–24
    [Google Scholar]
  76. Kartzinel TR, Hsing JC, Musili PM, Brown BRP, Pringle RM 2019. Covariation of diet and gut microbiome in African megafauna. PNAS 116:23588–93
    [Google Scholar]
  77. Kartzinel TR, Pringle RM. 2020. Multiple dimensions of dietary diversity in large mammalian herbivores. J. Anim. Ecol. 89:148296
    [Google Scholar]
  78. Kleynhans EJ, Jolles AE, Bos MRE, Olff H 2011. Resource partitioning along multiple niche dimensions in differently sized African savanna grazers. Oikos 120:591–600
    [Google Scholar]
  79. Knowlton N. 1993. Sibling species in the sea. Annu. Rev. Ecol. Syst. 24:189–216
    [Google Scholar]
  80. Knowlton N, Jackson JBC. 1994. New taxonomy and niche partitioning on coral reefs: jack of all trades or master of some. Trends Ecol. Evol. 9:7–9
    [Google Scholar]
  81. Lau MK, Borrett SR, Baiser B, Gotelli NJ, Ellison AM 2017. Ecological network metrics: opportunities for synthesis. Ecosphere 8:e01900
    [Google Scholar]
  82. Lawton JH. 1999. Are there general laws in ecology. Oikos 84:177–92
    [Google Scholar]
  83. LeDuc RG, Robertson KM, Pitman RL 2008. Mitochondrial sequence divergence among Antarctic killer whale ecotypes is consistent with multiple species. Biol. Lett. 4:426–29
    [Google Scholar]
  84. Leray M, Knowlton N, Ho S-L, Nguyen BN, Machida RJ 2019. GenBank is a reliable resource for 21st century biodiversity research. PNAS 116:22651–56
    [Google Scholar]
  85. Lucas A, Bodger O, Brosi BJ, Ford CR, Forman DW et al. 2018. Floral resource partitioning by individuals within generalised hoverfly pollination networks revealed by DNA metabarcoding. Sci. Rep. 8:5133
    [Google Scholar]
  86. Martinez ND. 1993. Effects of resolution on food web structure. Oikos 66:403–12
    [Google Scholar]
  87. Martínez del Rio C, Wolf N, Carleton SA, Gannes LZ 2009. Isotopic ecology ten years after a call for more laboratory experiments. Biol. Rev. 84:91–111
    [Google Scholar]
  88. May RM. 1973. Complexity and Stability in Model Ecosystems Princeton, NJ: Princeton Univ. Press
    [Google Scholar]
  89. McCann K, Hastings A, Huxel GR 1998. Weak trophic interactions and the balance of nature. Nature 395:794–98
    [Google Scholar]
  90. Moore JC, de Ruiter PC, McCann KS, Wolters V 2018. Adaptive Food Webs: Stability and Transitions of Real and Model Ecosystems Cambridge, UK: Cambridge Univ. Press
    [Google Scholar]
  91. Newmaster SG, Thompson ID, Steeves RAD, Rodgers AR, Fazekas AJ et al. 2013. Examination of two new technologies to assess the diet of woodland caribou: video recorders attached to collars and DNA barcoding. Can. J. For. Res. 43:897–900
    [Google Scholar]
  92. Nielsen JM, Clare EL, Hayden B, Brett MT, Kratina P 2018. Diet tracing in ecology: method comparison and selection. Methods Ecol. Evol. 9:278–91
    [Google Scholar]
  93. Novak M, Wootton JT. 2010. Using experimental indices to quantify the strength of species interactions. Oikos 119:1057–63
    [Google Scholar]
  94. Olesen JM, Bascompte J, Dupont YL, Elberling H, Rasmussen C, Jordano P 2011. Missing and forbidden links in mutualistic networks. Proc. R. Soc. B 278:725–32
    [Google Scholar]
  95. Paine RT. 1966. Food web complexity and species diversity. Am. Nat. 100:65–75
    [Google Scholar]
  96. Paine RT. 1988. Food webs: road maps of interactions or grist for theoretical development. Ecology 69:1648–54
    [Google Scholar]
  97. Pansu J, Guyton JA, Potter AB, Atkins JL, Daskin JH et al. 2019. Trophic ecology of large herbivores in a reassembling African ecosystem. J. Ecol. 107:1355–76
    [Google Scholar]
  98. Pascual M, Dunne JA. 2006. Ecological Networks: Linking Structure to Dynamics in Food Webs New York: Oxford Univ. Press
    [Google Scholar]
  99. Pfenninger M, Schwenk K. 2007. Cryptic animal species are homogeneously distributed among taxa and biogeographical regions. BMC Evol. Biol. 7:121
    [Google Scholar]
  100. Pilcher M, Boreaux V, Klein A-M, Schleuning M, Hartig F 2020. Machine learning algorithms to infer trait matching and predict species interactions in ecological networks. Methods Ecol. Evol. 11:281–93
    [Google Scholar]
  101. Pilosof S, Porter MA, Pascual M, Kéfi S 2017. The multilayer nature of ecological networks. Nat. Ecol. Evol. 1:0101
    [Google Scholar]
  102. Pimm SL. 1980. Food web design and the effect of species deletion. Oikos 35:139–49
    [Google Scholar]
  103. Pimm SL, Lawton JH. 1977. Number of trophic levels in ecological communities. Nature 268:329–31
    [Google Scholar]
  104. Pimm SL, Lawton JH. 1980. Are food webs divided into compartments. J. Anim. Ecol. 49:879–98
    [Google Scholar]
  105. Pimm SL, Lawton JH, Cohen JE 1991. Food web patterns and their consequences. Nature 350:669–74
    [Google Scholar]
  106. Poisot T, Stouffer DB, Kéfi S 2016. Describe, understand and predict: Why do we need networks in ecology. Funct. Ecol. 30:1878–82
    [Google Scholar]
  107. Polis GA. 1991. Complex trophic interactions in deserts: an empirical critique of food-web theory. Am. Nat. 138:123–55
    [Google Scholar]
  108. Polis GA, Power ME, Huxel GR 2004. Food Webs at the Landscape Level Chicago: Univ. Chicago Press
    [Google Scholar]
  109. Polis GA, Winemiller KO. 1996. Food Webs: Integration of Patterns and Dynamics London: Chapman & Hall
    [Google Scholar]
  110. Pompanon F, Deagle BE, Symondson WOC, Brown DS, Jarman SN, Taberlet P 2012. Who is eating what: diet assessment using next generation sequencing. Mol. Ecol. 21:1931–50
    [Google Scholar]
  111. Pornon A, Andalo C, Burrus M, Escaravage N 2017. DNA metabarcoding data unveils invisible pollination networks. Sci. Rep. 7:16828
    [Google Scholar]
  112. Post DM. 2002. The long and short of food-chain length. Trends Ecol. Evol. 17:269–77
    [Google Scholar]
  113. Power ME. 1990. Effects of fish in river food webs. Science 250:811–14
    [Google Scholar]
  114. Pringle RM. 2020. Untangling food webs. Unsolved Problems in Ecology AP Dobson, RD Holt, D Tilman 225–38 Princeton, NJ: Princeton Univ. Press
    [Google Scholar]
  115. Pringle RM, Fox-Dobbs K. 2008. Coupling of canopy and understory food webs by ground-dwelling predators. Ecol. Lett. 11:1328–37
    [Google Scholar]
  116. Pringle RM, Kartzinel TR, Palmer TM, Thurman TJ, Fox-Dobbs K et al. 2019. Predator-induced collapse of niche structure and species coexistence. Nature 570:58–64
    [Google Scholar]
  117. Ratnasingham S, Hebert PDN. 2007. BOLD: The Barcode of Life Data System. http://www.barcodinglife.org Mol. Ecol. Notes 7:355–64
    [Google Scholar]
  118. Raubenheimer D. 2011. Toward a quantitative nutritional ecology: the right-angled mixture triangle. Ecol. Monogr. 81:407–27
    [Google Scholar]
  119. Roeder KA, Kaspari M. 2017. From cryptic herbivore to predator: stable isotopes reveal consistent variability in trophic levels in an ant population. Ecology 98:297–303
    [Google Scholar]
  120. Rooney N, McCann K, Gellner G, Moore JC 2006. Structural asymmetry and the stability of diverse food webs. Nature 442:265–69
    [Google Scholar]
  121. Roslin T, Majaneva S. 2016. The use of DNA barcodes in food web construction—terrestrial and aquatic ecologists unite. ! Genome 59:603–28
    [Google Scholar]
  122. Roslin T, Wirta H, Hopkins T, Hardwick B, Várkonyi G 2013. Indirect interactions in the High Arctic. PLOS ONE 8:e67367
    [Google Scholar]
  123. Schmitz OJ, Krivan V, Ovadia O 2004. Trophic cascades: the primacy of trait-mediated indirect interactions. Ecol. Lett. 7:153–63
    [Google Scholar]
  124. Schnell IB, Thomsen PF, Wilkinson N, Rasmussen M, Jensen LRD et al. 2012. Screening mammal biodiversity using DNA from leeches. Curr. Biol. 22:R262–63
    [Google Scholar]
  125. Smith MA, Eveleigh ES, McCann KS, Merilo MT, McCarthy PC, Van Rooyen KI 2011. Barcoding a quantified food web: crypsis, concepts, ecology and hypotheses. PLOS ONE 6:e14424
    [Google Scholar]
  126. Smith MA, Rodriguez JJ, Whitfield JB, Deans AR, Janzen DH et al. 2008. Extreme diversity of tropical parasitoid wasps exposed by iterative integration of natural history, DNA barcoding, morphology, and collections. PNAS 105:12359–64
    [Google Scholar]
  127. Smith MA, Wood DM, Janzen DH, Hallwachs W, Hebert PDN 2007. DNA barcodes affirm that 16 species of apparently generalist tropical parasitoid flies (Diptera, Tachinidae) are not all generalists. PNAS 104:4967–72
    [Google Scholar]
  128. Smith MA, Woodley NE, Janzen DH, Hallwachs W, Hebert PDN 2006. DNA barcodes reveal cryptic host-specificity within the presumed polyphagous members of a genus of parasitoid flies (Diptera: Tachinidae). PNAS 103:3657–62
    [Google Scholar]
  129. Soininen EM, Valentini A, Coissac E, Miquel C, Gielly L et al. 2009. Analysing diet of small herbivores: the efficiency of DNA barcoding coupled with high-throughput pyrosequencing for deciphering the composition of complex plant mixtures. Front. Zool. 6:16
    [Google Scholar]
  130. Srivathsan A, Ang A, Vogler AP, Meier R 2016. Fecal metagenomics for the simultaneous assessment of diet, parasites, and population genetics of an understudied primate. Front. Zool. 13:17
    [Google Scholar]
  131. Strogatz SH. 2001. Exploring complex networks. Nature 410:268–76
    [Google Scholar]
  132. Taberlet P, Bonin A, Zinger L, Coissac E 2018. Environmental DNA for Biodiversity Research and Monitoring Oxford, UK: Oxford Univ. Press
    [Google Scholar]
  133. Talbot LM, Talbot MH. 1962. Food preferences of some East African wild ungulates. East Afr. Agric. For. J. 27:131–38
    [Google Scholar]
  134. Terborgh J, Estes JA. 2013. Trophic Cascades: Predators, Prey, and the Changing Dynamics of Nature Washington, DC: Island Press
    [Google Scholar]
  135. Thébault E, Fontaine C. 2010. Stability of ecological communities and the architecture of mutualistic and trophic networks. Science 329:853–56
    [Google Scholar]
  136. Thomas AC, Deagle BE, Eveson JP, Harsch CH, Trites AW 2016. Quantitative DNA metabarcoding: improved estimates of species proportional biomass using correction factors derived from control material. Mol. Ecol. Res. 16:714–26
    [Google Scholar]
  137. Thompson RM, Brose U, Dunne JA, Hall RO Jr, Hladyz S et al. 2012. Food webs: reconciling the structure and function of biodiversity. Trends Ecol. Evol. 27:689–97
    [Google Scholar]
  138. Thompson RM, Townsend CR. 2000. Is resolution the solution?: the effect of taxonomic resolution on the calculated properties of three stream food webs. Freshw. Biol. 44:413–22
    [Google Scholar]
  139. Thomsen PF, Sigsgaard EE. 2019. Environmental DNA metabarcoding of wild flowers reveals diverse communities of terrestrial arthropods. Ecol. Evol. 9:1665–79
    [Google Scholar]
  140. Tinker MT, Bentall G, Estes JA 2008. Food limitation leads to behavioral diversification and dietary specialization in sea otters. PNAS 105:56065
    [Google Scholar]
  141. Tinley KL. 1977. Framework of the Gorongosa ecosystem DSc Thesis, Univ. Pretoria South Afr:.
    [Google Scholar]
  142. Traugott M, Kamenova S, Ruess L, Seeber J, Plantegenest M 2013. Empirically characterising trophic networks: what emerging DNA-based methods, stable isotope and fatty acid analyses can offer. Adv. Ecol. Res. 49:177–224
    [Google Scholar]
  143. Valdovinos FS, Ramos-Jiliberto R, Garay-Narváez L, Urbani P, Dunne JA 2010. Consequences of adaptive behaviour for the structure and dynamics of food webs. Ecol. Lett. 13:1546–59
    [Google Scholar]
  144. Vilgalys R. 2003. Taxonomic misidentification in public DNA databases. New Phytol 160:4–5
    [Google Scholar]
  145. Willerslev E, Davison J, Moora M, Zobel M, Coissac E et al. 2014. Fifty thousand years of Arctic vegetation and megafaunal diet. Nature 506:47–51
    [Google Scholar]
  146. Winemiller KO. 2007. Interplay between scale, resolution, life history and food web properties. From Energetics to Ecosystems: The Dynamics and Structure of Ecological Systems N Rooney, KS McCann, DLG Noakes 101–26 Dordrecht, Neth: Springer
    [Google Scholar]
  147. Wirta HK, Hebert PDN, Kaartinen R, Prosser SW, Várkonyi G, Roslin T 2014. Complementary molecular information changes our perception of food web structure. PNAS 111:1885–90
    [Google Scholar]
  148. Zinger L, Bonin A, Alsos IG, Bálint M, Bik H et al. 2019. DNA metabarcoding—need for robust experimental designs to draw sound ecological conclusions. Mol. Ecol. 28:1857–62
    [Google Scholar]
/content/journals/10.1146/annurev-ecolsys-110218-024908
Loading
/content/journals/10.1146/annurev-ecolsys-110218-024908
Loading

Data & Media loading...

  • Article Type: Review Article
This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error