, Volume 21, Issue 6, pp 1101–1117 | Cite as

Low Levels of Allochthony in Consumers Across Three High-Elevation Lake Types

  • Michael J. VlahEmail author
  • Gordon W. Holtgrieve
  • Steven Sadro


The integration of lakes into watershed-scale energy budgets remains a major goal of aquatic ecosystem ecology. However, this enterprise has focused almost exclusively on temperate and boreal systems and on zooplankton as representatives of system-wide energy flow. We investigated the proportion of consumer biomass derived from terrestrial sources, allochthony, in three classes of high-elevation lakes—alpine, large and small montane—of varying geometry and watershed ecosystem development, and across five taxa, including macrobenthic invertebrates and fish. We used stable isotopes of carbon (13C:12C), nitrogen (15N:14N), and hydrogen (2H:1H) to fit a modular Bayesian mixing model, which estimated proportional assimilation of phytoplankton, algal periphyton, and terrestrial organic matter by each consumer. The stable isotope analysis was supplemented with a comparison of fatty acid profiles between consumers and producers, and with a Daphnia magna rearing study involving aquatic and terrestrial nutrient sources. The most probable estimate of allochthony across consumer taxa was 41% in small montane lakes (< 0.1 ha) with high terrestrial C loading. For large montane (3–11 ha) and alpine lakes (0.8–3 ha), with substantially less terrestrial influence, allochthony was just 4 and 3%, respectively. Allochthony was also lower on average for benthic grazers than for pelagic consumers. Our results corroborate previous findings that lake size, depth, and light penetration are dominant physical controls on allochthony, but add that it sharply declines at high elevation due to changes in terrestrial primary production near or above tree line.


allochthony alpine lakes stable isotope Bayesian mixing model fatty acid 



We thank Laura Twardochleb and Rachel Steinmetz for helping with sample collection and processing in the field. Daniel Schindler and Michael Brett provided tremendous logistical, conceptual, and technical advice, as well as laboratory space. Additional contributors of valuable time and expertise include Eric Ward, Andrew Schauer, Arni Litt, Joshua Gregersen, Ashley Maloney, Sydney Clark, Jon Wittouck, Arielle Ellis, and Frieda Taub.

Supplementary material

10021_2017_206_MOESM1_ESM.docx (286 kb)
Supplementary material 1 (DOCX 285 kb)


  1. Berggren M, Bergström A-K, Karlsson J. 2015. Intraspecific autochthonous and allochthonous resource use by zooplankton in a humic lake during the transitions between winter, summer and fall. PLoS ONE 10(3):1–14.CrossRefGoogle Scholar
  2. Berggren M, Ziegler SE, St-Gelais NF, Beisner BE, Del Giorgio PA. 2014. Contrasting patterns of allochthony among three major groups of crustacean zooplankton in boreal and temperate lakes. Ecology 95(7):1947–59.CrossRefPubMedGoogle Scholar
  3. Blaney HF. 1960. Evaporation from water surfaces in mountain areas of western United States. International Association of Scientific Hydrology. Bulletin 5(1):27–37.CrossRefGoogle Scholar
  4. Brett MT, Holtgrieve GW, Schindler DE. (in review). An assessment of assumptions and uncertainty in deuterium-based estimates of trophic interactions in aquatic ecosystems.Google Scholar
  5. Brett MT, Kainz MJ, Taipale SJ, Seshan H. 2009. Phytoplankton, not allochthonous carbon, sustains herbivorous zooplankton production. Proc Natl Acad Sci U S A 106(50):21197–201.CrossRefPubMedPubMedCentralGoogle Scholar
  6. Brett MT, Müller-Navarra DC, Ballantyne AP, Ravet JL, Goldman CR. 2006. Daphnia fatty acid composition reflects that of their diet. Limnol Oceanogr 51(5):2428–37.CrossRefGoogle Scholar
  7. Carpenter SR, Kitchell JF. 1996. The trophic cascade in lakes. Cambridge: Cambridge University Press.Google Scholar
  8. Carpenter SR., Cole JJ, Pace ML, de Bogert M, Bade DL, Bastviken D, & others. 2005. Ecosystem subsidies: terrestrial support of aquatic food webs from 13C addition to contrasting lakes. Ecology 86(10): 2737–50.Google Scholar
  9. Cole JJ, Carpenter SR, Kitchell J, Pace ML, Solomon CT, Weidel B. 2011. Strong evidence for terrestrial support of zooplankton in small lakes based on stable isotopes of carbon, nitrogen, and hydrogen. Proc Natl Acad Sci 108(5):1975–80.CrossRefPubMedGoogle Scholar
  10. Craig H, Hayward T. 1987. Oxygen supersaturation in the ocean—biological versus physical contributions. Science 235(4785):199–202.CrossRefPubMedGoogle Scholar
  11. Dalsgaard J, John MS, Kattner G, Müller-Navarra D, Hagen W. 2003. Fatty acid trophic markers in the pelagic marine environment. Adv Mar Biol 46:225–340.CrossRefPubMedGoogle Scholar
  12. DeAngelis DL. 1992. Dynamics of nutrient cycling and food webs. New York, NY: Chapman and Hall.CrossRefGoogle Scholar
  13. DeMott WR. 1988. Discrimination between algae and detritus by freshwater and marine zooplankton. Bull Mar Sci 43(3):486–99.Google Scholar
  14. Doucett RR, Marks JC, Blinn DW, Caron M, Hungate BA. 2007. Measuring terrestrial subsidies to aquatic food webs using stable isotopes of hydrogen. Ecology 88(6):1587–92.CrossRefPubMedGoogle Scholar
  15. Elvert M, Boetius A, Knittel K, Jørgensen BB. 2003. Characterization of specific membrane fatty acids as chemotaxonomic markers for sulfate-reducing bacteria involved in anaerobic oxidation of methane. Geomicrobiol J 20(4):403–19.CrossRefGoogle Scholar
  16. Emery KA, Wilkinson GM, Ballard FG, Pace ML. 2015. Use of allochthonous resources by zooplankton in reservoirs. Hydrobiologia 758(1):257–69.CrossRefGoogle Scholar
  17. Francis TB, Schindler DE, Holtgrieve GW, Larson ER, Scheuerell MD, Semmens BX, Ward EJ. 2011. Habitat structure determines resource use by zooplankton in temperate lakes. Ecol Lett 14(4):364–72.CrossRefPubMedGoogle Scholar
  18. Gelman A, Rubin DB. 1992. Inference from iterative simulation using multiple sequences. Stat Sci 7:457–72.CrossRefGoogle Scholar
  19. Grey J, Jones RI, Sleep D. 2001. Seasonal changes in the importance of the source of organic matter to the diet of zooplankton in Loch Ness, as indicated by stable isotope analysis. Limnol Oceanogr 46(3):505–13.CrossRefGoogle Scholar
  20. Hadas O, Cavari BZ, Kott Y, Bachrach U. 1982. Preferential feeding behaviour of Daphnia magna. Hydrobiologia 89(1):49–52.CrossRefGoogle Scholar
  21. Holtgrieve GW, Schindler DE, Gowell CP, Ruff CP, Lisi PJ. 2010. Stream geomorphology regulates the effects on periphyton of ecosystem engineering and nutrient enrichment by Pacific salmon. Freshw Biol 55(12):2598–611.CrossRefGoogle Scholar
  22. Jackson AL, Inger R, Bearhop S, Parnell A. 2009. Erroneous behaviour of MixSIR, a recently published Bayesian isotope mixing model: a discussion of Moore & Semmens (2008). Ecol Lett 12(3):E1–5.CrossRefPubMedGoogle Scholar
  23. Junk WJ, Bayley PB, Sparks RE, & others. 1989. The flood pulse concept in river-floodplain systems. Can Spec Publ Fish Aquat Sci 106(1):110–27.Google Scholar
  24. Kankaala P, Taipale S, Li L, Jones RI. 2010. Diets of crustacean zooplankton, inferred from stable carbon and nitrogen isotope analyses, in lakes with varying allochthonous dissolved organic carbon content. Aquat Ecol 44(4):781–95.CrossRefGoogle Scholar
  25. Karlsson J, Berggren M, Ask J, Byström P, Jonsson A, Laudon H, Jansson M. 2012. Terrestrial organic matter support of lake food webs: evidence from lake metabolism and stable hydrogen isotopes of consumers. Limnol Oceanogr 57(4):1042–8.CrossRefGoogle Scholar
  26. Karlsson J, Jonsson A, Meili M, Jansson M. 2003. Control of zooplankton dependence on allochthonous organic carbon in humic and clear-water lakes in northern Sweden. Limnol Oceanogr 48(1):269–76.CrossRefGoogle Scholar
  27. Kharlamenko VI, Zhukova NV, Khotimchenko SV, Svetashev VI, Kamenev GM. 1995. Fatty acids as markers of food sources in a shallow-water hydrothermal ecosystem (Kraternaya Bight, Yankich Island, Kurile Islands). Mar Ecol Progr Ser 120:231–41.CrossRefGoogle Scholar
  28. Lindeman RL. 1942. The trophic-dynamic aspect of ecology. Ecology 23(4):399–417.CrossRefGoogle Scholar
  29. Lindström K. 1991. Nutrient requirements of the dinoflagellate Peridinium gatunense. J Phycol 27(2):207–19.CrossRefGoogle Scholar
  30. Moore J, Berlow E, Coleman D. 2004. Detritus, trophic dynamics and biodiversity. Ecology Letters. Retrieved from
  31. Nichols PD, Palmisano AC, Smith GA, White DC. 1986. Lipids of the Antarctic sea ice diatom Nitzschia cylindrus. Phytochemistry 25(7):1649–53.CrossRefGoogle Scholar
  32. Pace ML, Carpenter SR, Cole JJ, Coloso JJ, Kitchell JF, Hodgson JR, & others. 2007. Does terrestrial organic carbon subsidize the planktonic food web in a clear-water lake? Limnol Oceanogr 52(5):2177–189.Google Scholar
  33. Pace ML, Cole JJ, Carpenter SR, Kitchell JF, Hodgson JR, Van de Bogert MC, & others. 2004. Whole-lake carbon-13 additions reveal terrestrial support of aquatic food webs. Nature 427(6971):240–3.Google Scholar
  34. Piovia-Scott J, Sadro S, Knapp RA, Sickman J, Pope KL, Chandra S. 2016. Variation in reciprocal subsidies between lakes and land: perspectives from the mountains of California. Can J Fish Aquat Sci 73(11):1691–701.CrossRefGoogle Scholar
  35. Plummer M. 2016. rjags: Bayesian Graphical Models using MCMC. Retrieved from
  36. Plummer M, & others. 2003. JAGS: a program for analysis of Bayesian graphical models using Gibbs sampling. In: Proceedings of the 3rd international workshop on distributed statistical computing (Vol 124, p 125).Google Scholar
  37. Polis GA, Anderson WB, Holt RD. 1997. Toward an integration of landscape and food web ecology: the dynamics of spatially subsidized food webs. Ann Rev Ecol Syst 28(1):289–316.CrossRefGoogle Scholar
  38. Post DM. 2002. Using stable isotopes to estimate trophic position: models, methods, and assumptions. Ecology 83(3):703–18.CrossRefGoogle Scholar
  39. Pulido-Villena E, Reche I, Morales-Baquero R. 2005. Food web reliance on allochthonous carbon in two high mountain lakes with contrasting catchments: a stable isotope approach. Can J Fish Aquat Sci 62(11):2640–8.CrossRefGoogle Scholar
  40. R Core Team. 2017. R: a language and environment for statistical computing. Vienna, Austria. Retrieved from
  41. Rautio M, Mariash H, Forsström L. 2011. Seasonal shifts between autochthonous and allochthonous carbon contributions to zooplankton diets in a subarctic lake. Limnol Oceanogr. Retrieved from
  42. Rose KC, Williamson CE, Kissman CEH, Saros JE. 2015. Does allochthony in lakes change across an elevation gradient? Ecology 96(12):3281–91.CrossRefPubMedGoogle Scholar
  43. Sadro S, Melack JM, MacIntyre S. 2011. Spatial and temporal variability in the ecosystem metabolism of a high-elevation lake: integrating benthic and pelagic habitats. Ecosystems 14(7):1123–40.CrossRefGoogle Scholar
  44. Smits AP, Schindler DE, Brett MT. 2015. Geomorphology controls the trophic base of stream food webs in a boreal watershed. Ecology 96(7):1775–82.CrossRefPubMedGoogle Scholar
  45. Sobek S, Tranvik LJ, Prairie YT, Kortelainen P, Cole JJ. 2007. Patterns and regulation of dissolved organic carbon: an analysis of 7,500 widely distributed lakes. Limnol Oceanogr 52(3):1208–19.CrossRefGoogle Scholar
  46. Solomon CT, Cole JJ, Doucett RR, Pace ML, Preston ND, Smith LE, Weidel BC. 2009. The influence of environmental water on the hydrogen stable isotope ratio in aquatic consumers. Oecologia 161(2):313–24.CrossRefPubMedGoogle Scholar
  47. Sterner RW, Elser JJ, Fee EJ, Guildford SJ, Chrzanowski TH. 1997. The light: nutrient ratio in lakes: the balance of energy and materials affects ecosystem structure and process. Am Nat 150(6):663–84.CrossRefPubMedGoogle Scholar
  48. Strandberg U, Taipale SJ, Kainz MJ, Brett MT. 2014. Retroconversion of docosapentaenoic acid (n-6): an alternative pathway for biosynthesis of arachidonic acid in Daphnia magna. Lipids 49(6):591–5.CrossRefPubMedGoogle Scholar
  49. Taipale SJ, Kainz MJ, Brett MT. 2015. A low −3:−6 ratio in Daphnia indicates terrestrial resource utilization and poor nutritional condition. J Plankton Res 37:596–610.CrossRefGoogle Scholar
  50. Taipale S, Strandberg U, Peltomaa E, Galloway AWE, Ojala A, Brett MT. 2013. Fatty acid composition as biomarkers of freshwater microalgae: analysis of 37 strains of microalgae in 22 genera and in seven classes. Aquat Microb Ecol 71(2):165–78.CrossRefGoogle Scholar
  51. Tanentzap AJ, Kielstra BW, Wilkinson GM, Berggren M, Craig N, del Giorgio PA, & others. 2017. Terrestrial support of lake food webs: synthesis reveals controls over cross-ecosystem resource use. Sci Adv 3(3):e1601765.Google Scholar
  52. Tansley AG. 1935. The use and abuse of vegetational concepts and terms. Ecology 16(3):284–307.CrossRefGoogle Scholar
  53. Torres-Ruiz M, Wehr JD, Perrone AA. 2007. Trophic relations in a stream food web: importance of fatty acids for macroinvertebrate consumers. J N Am Benthol Soc 26(3):509–22.CrossRefGoogle Scholar
  54. Vadeboncoeur Y, Peterson G, Vander Zanden MJ, Kalff J. 2008. Benthic algal production across lake size gradients: interactions among morphometry, nutrients, and light. Ecology 89(9):2542–52.CrossRefPubMedGoogle Scholar
  55. Vadeboncoeur Y, Vander Zanden MJ, Lodge DM. 2002. Putting the Lake Back Together: reintegrating Benthic Pathways into Lake Food Web Models: lake ecologists tend to focus their research on pelagic energy pathways, but, from algae to fish, benthic organisms form an integral part of lake food webs. Bioscience 52(1):44–54.CrossRefGoogle Scholar
  56. Vannote RL, Minshall GW, Cummins KW, Sedell JR, Cushing CE. 1980. The river continuum concept. Can J Fish Aquat Sci 37(1):130–7.CrossRefGoogle Scholar
  57. Vuorio K, Meili M, Sarvala J. 2006. Taxon-specific variation in the stable isotopic signatures ($δ$13C and $δ$15N) of lake phytoplankton. Freshw Biol 51(5):807–22.CrossRefGoogle Scholar
  58. Weiss RF. 1970. The solubility of nitrogen, oxygen and argon in water and seawater. Deep Sea Res Oceanogr Abstr 17:721–35.CrossRefGoogle Scholar
  59. Wilkinson GM, Carpenter SR, Cole JJ, Pace ML, Yang C. 2013. Terrestrial support of pelagic consumers: patterns and variability revealed by a multilake study. Freshw Biol 58(10):2037–49.CrossRefGoogle Scholar

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© Springer Science+Business Media, LLC, part of Springer Nature 2017

Authors and Affiliations

  1. 1.School of Aquatic and Fishery SciencesUniversity of WashingtonSeattleUSA
  2. 2.Department of Environmental Science and PolicyUniversity of California, DavisDavisUSA

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