, Volume 18, Issue 4, pp 686–706 | Cite as

Are Large Herbivores Vectors of Terrestrial Subsidies for Riverine Food Webs?

  • Frank O. MaseseEmail author
  • Kátya G. Abrantes
  • Gretchen M. Gettel
  • Steven Bouillon
  • Kenneth Irvine
  • Michael E. McClain


The tropical savannas of Africa have witnessed a dramatic reduction in native large mammalian herbivore populations. The consequences of these changes for terrestrial-aquatic food-web linkages are poorly documented. We used natural abundances of stable carbon and nitrogen isotopes (δ13C, δ15N) to determine spatial and temporal patterns in the importance of herbivore-mediated subsidies for consumers in the Mara River, Kenya. Potential primary producers (terrestrial C3 and C4 producers and periphyton) and consumers (invertebrates and fish) were collected during dry and wet seasons from different sites along the river, representing a gradient from forested highlands to natural savanna grasslands with high herbivore densities across mixed agricultural and livestock-dominated zones. Bayesian mixing models were used to estimate the relative contributions of terrestrial and algal sources of organic carbon supporting consumer trophic groups. Organic carbon sources differed for consumer groups and sites and with season. Overall, periphyton was the major energy source for most consumer groups during the dry season, but with wide 95% confidence intervals. During the wet season, the importance of terrestrial-derived carbon for consumers increased. The importance of C3 producers declined from 40 and 41% at the forested upper reaches to 20 and 8% at river reaches receiving hippo inputs during the dry and wet seasons, respectively. The reciprocal increase in the importance of C4 producers was higher than expected based on areal cover of riparian vegetation that was mainly C3. The importance of C4 producers notably increased from 18 and 10% at the forested upper reaches to 33 and 58% at river reaches receiving hippo inputs during the dry and wet seasons, respectively. This study highlights the importance of large herbivores to the functioning of riverine ecosystems and the potential implications of their loss from savanna landscapes that currently harbor remnant populations. Although the importance of C4 terrestrial carbon in most river systems has been reported to be negligible, this study shows that its importance can be mediated by large herbivores as vectors, which enhance energetic terrestrial-aquatic linkages in rivers in savanna landscapes.


trophic subsidies allochthony food webs hippopotamus C4 carbon sources stable isotopes SIAR models tropical rivers 



We are grateful to Lubanga Lunaligo and David Namwaya (University of Eldoret) for assistance during lab work, William O. Ojwang and Chrisphine Nyamweya (KMFRI, Kisumu) and their team who assisted during fieldwork. We thank Zita Kelemen (KU Leuven), Amanda Subalusky, and Glendon Hunsinger (Yale University) for SIA analyses. We thank the TransMara Conservancy and the Narok County Council (Narok County) for granting us access into the Mara Triangle and MMNR, respectively. Insightful comments and suggestions by the subject editor Dr. S. Bunn and two anonymous reviewers significantly improved this manuscript. This is a publication of the MaraFlows Project and was funded by the Dutch Ministry of Foreign Affairs through UNESCO-IHE Partnership Research Fund (UPaRF). Partial support was provided by ERC-StG 240002 (AFRIVAL).

Supplementary material

10021_2015_9859_MOESM1_ESM.doc (422 kb)
Supplementary material 1 (DOC 421 kb)


  1. Abrantes KG, Barnett A, Marwick TR, Bouillon S. 2013. Importance of terrestrial subsidies for estuarine food webs in contrasting East African catchments. Ecosphere 4: Article 14.Google Scholar
  2. Abrantes KG, Sheaves M. 2010. Importance of freshwater flow in terrestrial–aquatic energetic connectivity in intermittently connected estuaries of tropical Australia. Mar Biol 157(2071):2086.Google Scholar
  3. Anderson C, Cabana G. 2005. δ15N in riverine food webs: effects of N inputs from agricultural watersheds. Can J Fish Aquat Sci 62:333–40.CrossRefGoogle Scholar
  4. APHA (American Public Health Association), 1998. Standard Methods for the Examination of Water and Wastewater, 20th ed. American Public Health Association, American Water Works Association, Water Environment Federation, Washington, DC.Google Scholar
  5. Balcombe SR, Bunn SE, McKenzie-Smith FJ, Davies PM. 2005. Variability of fish diets between dry and flood periods in an arid zone floodplain river. J Fish Biol 67:1552–67.CrossRefGoogle Scholar
  6. Bond TA, Sear DA, Edwards ME. 2012. Temperature-driven river utilisation and preferential defecation by cattle in an English chalk stream. Livestock Sci 146:59–66.CrossRefGoogle Scholar
  7. Bouillon S, Abril G, Borges AV, Dehairs F, Govers G, Hughes HJ, Merckx R, Meysman FJR, Nyunja J, Osburn C, Middelburg JJ. 2009. Distribution, origin and cycling of carbon in the Tana River (Kenya): a dry season basin-scale survey from headwaters to the delta. Biogeosciences 6:2475–93.CrossRefGoogle Scholar
  8. Brett MT. 2014. Resource polygon geometry predicts Bayesian stable isotope mixing model bias. Mar Ecol Prog Ser 514:1–12.CrossRefGoogle Scholar
  9. Buchheister A, Latour RJ. 2010. Turnover and fractionation of carbon and nitrogen stable isotopes in tissues of a migratory coastal predator, summer flounder (Paralichthys dentatus). Can J Fish Aquat Sci 67:445–61.CrossRefGoogle Scholar
  10. Bunn SE, Davies PM, Kellaway DM. 1997. Contributions of sugarcane and invasive pasture grass to the aquatic food web of a tropical lowland stream. Mar Freshw Res 48:173–9.CrossRefGoogle Scholar
  11. Bunn SE, Leigh C, Jardine TD. 2013. Diet–tissue fractionation of δ15N by consumers from streams and rivers. Limnol Oceanogr 58:765–73.CrossRefGoogle Scholar
  12. Clapcott JE, Bunn SE. 2003. Can C-4 plants contribute to aquatic food webs of subtropical streams? Freshw Biol 48:1105–16.CrossRefGoogle Scholar
  13. Corbet PS. 1961. The food of non-cichlid fishes in the Lake Victoria basin, with remarks on their evolution and adaptation to lacustrine conditions. Proc Zool Soc Lond 136:1–101.CrossRefGoogle Scholar
  14. DDP (District Development Plan). 2008a. Effective management for sustainable economic growth and poverty reduction, Bomet District 2002-2008. Nairobi: Government Printer.Google Scholar
  15. DDP (District Development Plan). 2008b. Effective management for sustainable economic growth and poverty reduction, Narok District 2002-2008. Nairobi: Government Printer.Google Scholar
  16. Defersha M, Melesse AM. 2012. Field-scale investigation of the effect of land use on sediment yield and surface runoff using runoff plot data and models in the Mara River basin, Kenya. Catena 89:54–64.CrossRefGoogle Scholar
  17. de Ruiter PC, Wolters V, Moore JC, Winemiller KO. 2005. Food web ecology: playing Jenga and beyond. Science 309:68–71.CrossRefPubMedGoogle Scholar
  18. Doucett RR, Marks JC, Blinn DW, Caron M, Hungate BA. 2007. Measuring terrestrial subsidies to aquatic food webs using stable isotopes of hydrogen. Ecology 88:1587–92.CrossRefPubMedGoogle Scholar
  19. Douglas MM, Bunn SE, Davies PM. 2005. River and wetland food webs in Australia’s wet-dry tropics: general principles and implications for management. Mar Freshw Res 56:329–42.CrossRefGoogle Scholar
  20. du Toit JT, Cumming DHM. 1999. Functional significance of ungulate diversity in African savannas and the ecological implications of the spread of pastoralism. Biodivers Conserv 8:1643–61.CrossRefGoogle Scholar
  21. Dubois S, Jean-Louis B, Bertrand B, Lefebvre S. 2007. Isotope trophic-step fractionation of suspension-feeding species: implications for food partitioning in coastal ecosystems. J Exp Mar Biol Ecol 351:121–8.CrossRefGoogle Scholar
  22. Dutton CL. 2012. Sediment fingerprinting in the Mara River: uncovering relationships between wildlife, tourism, and non-point source pollution. MSc. thesis, Yale University, USA.Google Scholar
  23. Finlay JC. 2001. Stable-carbon-isotope ratios of river biota: implications for energy flow in lotic food webs. Ecology 82:1052–64.Google Scholar
  24. Finlay JC. 2004. Patterns and controls of lotic algal stable carbon isotope ratios. Limnol Oceanogr 49:850–61.CrossRefGoogle Scholar
  25. Finlay JC, Doucett RR, McNeely C. 2010. Tracing energy flow in stream food webs using stable isotopes of hydrogen. Freshw Biol 55:941–51.CrossRefGoogle Scholar
  26. Forsberg BR, Arujo-Lima CARM, Martinelli LA, Victoria RL, Bonassi JA. 1993. Autotrophic carbon sources for fish of central Amazon. Ecology 74:643–51.CrossRefGoogle Scholar
  27. Fry B, Sherr EB. 1989. δ13C Measurements as indicators of carbon flow in marine and freshwater ecosystems. In: Rundel PW, Ehleringer JR, Nagy KA, Eds. Stable isotopes in ecological research. Ecological studies. New York: Springer. p 196–229.CrossRefGoogle Scholar
  28. Fry B. 2013. Alternative approaches for solving underdetermined isotope mixing problems. Mar Ecol Prog Series 472:1–13.CrossRefGoogle Scholar
  29. Gereta E, Wolanski E. 1998. Wildlife-water quality interactions in the Serengeti National Park, Tanzania. Afr J Ecol 36:1–14.CrossRefGoogle Scholar
  30. Grey J, Harper DM. 2002. Using stable isotope analyses to identify allochthonous inputs to Lake Naivasha mediated via the hippopotamus gut. Isot Environ Health Stud 38:245–50.CrossRefGoogle Scholar
  31. Jackson AJH, McCarter PS. 1994. A profile of the Mau complex. Nairobi: KIFCON.Google Scholar
  32. Jacobs SM, Bechtold JS, Biggs HC, Grimm NB, Lorentz S, McClain ME, Naiman RJ, Perakis SS, Pinay G, Scholes MC. 2007. Nutrient vectors and riparian processing: a review with special reference to African semiarid Savanna ecosystems. Ecosystems 10:1231–49.CrossRefGoogle Scholar
  33. Jardine TD, Pettit NE, Warfe DM, Pusey BJ, Ward DP, Douglas MM, Davies PM, Bunn SE. 2012. Consumer–resource coupling in wet–dry tropical rivers. J Anim Ecol 81:310–22.CrossRefPubMedGoogle Scholar
  34. Jepsen DB, Winemiller KO. 2007. Basin geochemistry and isotopic ratios of fishes and basal production sources in four neotropical rivers. Ecol Freshw Fish 16:267–81.CrossRefGoogle Scholar
  35. Junk WJ, Bayley PB, Sparks RE. 1989. The flood pulse concept in river floodplain systems. In: Dodge DP, Ed. Proceedings of the international large river symposium, Canadian Special Publication of Fisheries and Aquatic Sciences 106:110–127.Google Scholar
  36. Kanga EM, Ogutu JO, Olff H, Santema P. 2011. Population trend and distribution of the vulnerable common hippopotamus Hippopotamus amphibius in the Mara Region of Kenya. Oryx 45:20–7.CrossRefGoogle Scholar
  37. Kiambi S, Kuloba B, Kenana L, Muteti D, Mwenda E. 2012. Wet season aerial count of large herbivores in masai mara national reserve and the adjacent community areas (June 2010). Narok: Mara Research Station, Kenya Wildlife Service.Google Scholar
  38. KNBS-IHBS. 2007. Kenya National Bureau of Statistics (KNBS)-Kenya Integrated Household Budget Survey (KIHBS)—2005/06. Nairobi: Ministry of Planning and National Development.Google Scholar
  39. KNBS-LS. 2009. Livestock population by type and district. Nariobi: Census KNBS.Google Scholar
  40. Lamprey RH, Reid RS. 2004. Expansion of human settlement in Kenya’s Maasai Mara: what future for pastoralism and wildlife? J Biogeogr 31:997–1032.CrossRefGoogle Scholar
  41. Lewis WMJ, Hamilton SK, Rodriguez MA, Saunders JFI, Lasi MA. 2001. Foodweb analysis of the Orinoco floodplain based on production estimates and stable isotope data. J N Am Benthol Soc 20:241–54.CrossRefGoogle Scholar
  42. Logan JM, Jardine TD, Miller TJ, Bunn SE, Cunjak RA, Lutcavage ME. 2008. Lipid corrections in carbon and nitrogen stable isotope analyses: comparison of chemical extraction and modelling methods. J Anim Ecol 77:838–46.CrossRefPubMedGoogle Scholar
  43. MALP (2009a). Ministry of Agriculture and Livestock Production, Narok South District, Kenya.Google Scholar
  44. MALP (2009b). Ministry of Agriculture and Livestock Production, Bomet District, Kenya.Google Scholar
  45. Marwick TR, Tamooh F, Ogwoka B, Teodoru C, Borges AV, Darchambeau F, Bouillon S. 2014a. Dynamic seasonal nitrogen cycling in response to anthropogenic N-loading in a tropical catchment, Athi–Galana–Sabaki River, Kenya. Biogeosciences 11:443–460.CrossRefGoogle Scholar
  46. Marwick TR, Borges AV, Acker KV, Darchambeau F, Bouillon S. 2014b. Disproportionate contribution of riparian inputs to organic carbon pools in freshwater systems. Ecosystems 17:974–89. doi: 10.1007/s10021-014-9772-6.CrossRefPubMedCentralPubMedGoogle Scholar
  47. Masese FO, Gettel GM, Kitaka N, Kipkemboi J, Irvine K, McClain ME. 2014. Macroinvertebrate functional feeding groups in Kenyan highland streams: more evidence for a diverse shredder assemblage. Freshw Sci 33:435–50.CrossRefGoogle Scholar
  48. Masese FO, McClain ME. 2012. Trophic resources and emergent food web attributes in rivers of the Lake Victoria Basin: a review with reference to anthropogenic influences. Ecohydrology 5:685–707.CrossRefGoogle Scholar
  49. Mati BM, Mutie S, Gadain H, Home P, Mtalo F. 2008. Impacts of landuse/ cover changes on the hydrology of the transboundary Mara River, Kenya/Tanzania. Lakes Reserv Res Manage 13:169–77.CrossRefGoogle Scholar
  50. McClain ME, Subalusky AL, Anderson EP, Dessu SB, Melesse AM, Ndomba PM, Mtamba JOD, Tamatamah RA, Mligo C. 2014. Comparing flow regime, channel hydraulics and biological communities to infer flow–ecology relationships in the Mara River of Kenya and Tanzania. Hydrol Sci J 59(4):1–19.Google Scholar
  51. McCutchan JH, Lewis WM Jr, Kendall C, McGrath CC. 2003. Variation in trophic shift for stable isotope ratios of carbon, nitrogen, and sulfur. Oikos 102:378–90.CrossRefGoogle Scholar
  52. McIntyre PB, Flecker AS. 2006. Rapid turnover of tissue nitrogen of primary consumers in tropical freshwaters. Oecologia 148:12–21.CrossRefPubMedGoogle Scholar
  53. Mead LH, Wiegner TN. 2010. Surface water metabolism in a tropical estuary, Hilo Bay, Hawaii, USA, during storm and non-storm conditions. Estuaries Coasts 33:1099–112.CrossRefGoogle Scholar
  54. Mosepele K, Moyle PB, Merron GS, Purkey DR, Mosepele B. 2009. Fish, floods, and ecosystem engineers: aquatic conservation in the Okavango Delta, Botswana. BioScience 59:53–64.CrossRefGoogle Scholar
  55. Naiman RJ, Alldredge JR, Beauchamp DA, Bisson PA, Congleton J, Henny CJ, Huntly N, Lamberson R, Levings R, Merrill EN, Pearcy WG, Rieman BE, Ruggerone GT, Scarnecchia D, Smouse PE, Wood CC. 2012. Developing a broader scientific foundation for river restoration: Columbia River food webs. Proc Nat Acad Sci USA 109(52):21201–7.CrossRefPubMedCentralPubMedGoogle Scholar
  56. Naiman RJ, Rogers KH. 1997. Large animals and system level characteristics in river corridors. BioScience 47:521–9.CrossRefGoogle Scholar
  57. Nakano S, Miyasaka H, Kuhara N. 1999. Terrestrial-aquatic linkages: riparian arthropod inputs alter trophic cascades in a stream food web. Ecology 80:2435–41.Google Scholar
  58. Ogutu JO, Piepho H-P, Reid RS, Rainy ME, Kruska RL, Worden JS, Nyabenge M, Hobbs NT. 2010. Large herbivore responses to water and settlements in savannas. Ecol Monogr 80:241–66.CrossRefGoogle Scholar
  59. Ogutu JO, Owen-Smith N, Piepho HP, Said MY. 2011. Continuing wildlife population declines and range contraction in the Mara region of Kenya during 1977–2009. J Zool 285:99–109.CrossRefGoogle Scholar
  60. Ojwang WO, Kaufman L, Soule E, Asila AA. 2007. Evidence of stenotopy and anthropogenic influence on carbon source for two major riverine fishes of the Lake Victoria watershed. J Fish Biol 70:1430–46.CrossRefGoogle Scholar
  61. O’Reilly CM, Hecky RE, Cohen AS, Plisnier PD. 2002. Interpreting stable isotopes in food webs: recognizing the role of time averaging at different trophic levels. Limnol Oceanogr 47:306–9.CrossRefGoogle Scholar
  62. Paetzold A, Sabo JL, Sadler JP, Findlay SEG, Tockner K. 2007. Aquatic–terrestrial subsidies along river corridors. In: Wood PJ, Hannah DM, Sadler JP, Eds. Hydroecology and ecohydrology: past, present and future. Chichester: Wiley. p 57–92.Google Scholar
  63. Parnell AC, Inger R, Bearhop S, Jackson AL. 2010. Source partitioning using stable isotopes: coping with too much variation. PLoS One 5:e9672.CrossRefPubMedCentralPubMedGoogle Scholar
  64. Pennisi E. 2014. The river masters: hippos are the nutrient kingpins of Africa’s waterways. Science 346(6211):785.Google Scholar
  65. Peterson BJ, Howarth RW, Garritt RH. 1985. Multiple stable isotopes used to trace the flow of organic matter in estuarine food webs. Science 227:1361–3.CrossRefPubMedGoogle Scholar
  66. Phillips DL, Gregg JW. 2003. Source partitioning using stable isotopes: coping with too many sources. Oecologia 136:261–9.CrossRefPubMedGoogle Scholar
  67. Pingram MA, Collier KJ, Hamilton DP, Hicks BJ, David BO. 2014. Spatial and temporal patterns of carbon flow in a temperate, large river food web. Hydrobiologia 729:107–31.CrossRefGoogle Scholar
  68. Pinnegar JK, Polunin NVC. 1999. Differential fractionation of δ13C and δ15N among fish tissue: implication for the study of trophic interactions. Funct Ecol 13:225–31.CrossRefGoogle Scholar
  69. 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 28:289–316.CrossRefGoogle Scholar
  70. Post DM, Layman CA, Arrington DA, Takimoto G, Quattrochi J, Montana CG. 2007. Getting to the fat of the matter: models, methods and assumptions for dealing with lipids in stable isotope analyses. Oecologia 152:179–89.CrossRefPubMedGoogle Scholar
  71. Post DM. 2002. Using stable isotopes to estimate trophic position: models, methods, and assumptions. Ecology 83:703–18.CrossRefGoogle Scholar
  72. Prins HHT. 2000. Competition between wildlife and livestock in Africa. In: Prins HHT, Grootenhuis JG, Dolan TT, Eds. Wildlife conservation by sustainable use. Boston: Kluwer Academic Press. p 51–80.CrossRefGoogle Scholar
  73. Raburu PO, Masese FO. 2012. A fish-based index for assessing ecological integrity of riverine ecosystems in Lake Victoria Basin. River Res Appl 28:23–38.CrossRefGoogle Scholar
  74. Rasmussen JB, Trudeau V, Morinville GR. 2009. Estimating the scale of fish feeding movements in rivers using δ13C signature gradients. J Anim Ecol 78:674–85.CrossRefPubMedGoogle Scholar
  75. Rasmussen JB. 2010. Estimating terrestrial contribution to stream invertebrates and periphyton using a gradient-based mixing model for δ13C. J Anim Ecol 79:393–402.CrossRefPubMedGoogle Scholar
  76. Rau G. 1978. Carbon-13 depletion in a subalpine lake: carbon flow implications. Science 201:901–2.CrossRefPubMedGoogle Scholar
  77. Roach KA. 2013. Environmental factors affecting incorporation of terrestrial material into large river food webs. Freshw Sci 32:283–98.CrossRefGoogle Scholar
  78. Smart JS. 1972. Quantitative characterization of channel network structure. Water Resour Res 8:1487–96.CrossRefGoogle Scholar
  79. Subalusky AL, Dutton CL, Rosi-Marshall EJ, Post DM. 2014. The hippopotamus conveyor belt: vectors of carbon and nutrients from terrestrial grasslands to aquatic systems in sub-Saharan Africa. Freshw Biol. doi: 10.1111/fwb.12474.Google Scholar
  80. Tamooh F, Borges AV, Meysman FJR, Van Den Meersche K, Dehairs F, Merckx R, Bouillon S. 2013. Dynamics of dissolved inorganic carbon and aquatic metabolism in the Tana River Basin, Kenya. Biogeosciences 10:6911–28.CrossRefGoogle Scholar
  81. Tank JL, Rosi-Marshall EJ, Griffiths NA, Entrekin SA, Stephen ML. 2010. A review of allochthonous organic matter dynamics and metabolism in streams. J N Am Benthol Soc 29:118–46.CrossRefGoogle Scholar
  82. Thorp JH, Delong MD. 1994. The riverine productivity model: an heuristic view of carbon sources and organic processing in large river ecosystems. Oikos 70:305–8.CrossRefGoogle Scholar
  83. Vannote RL, Minshall GW, Cummins KW, Sedell JR, Cushing CE. 1980. The river continuum concept. Can J Fish Aquat Sci 37:130–7.CrossRefGoogle Scholar
  84. Wardle DA, Bardgett RD, Callaway RM, Van der Putten WH. 2011. Terrestrial ecosystem responses to species gains and losses. Science 332:1273–7.CrossRefPubMedGoogle Scholar
  85. Weidel BC, Carpenter SR, Kitchell JF, Vander Zanden MJ. 2011. Rates and components of carbon turnover in fish muscle: insights from bioenergetics models and a whole-lake 13C addition. Can J Fish Aquat Sci 68:387–99.CrossRefGoogle Scholar
  86. Zeug SC, Winemiller KO. 2008. Evidence supporting the importance of terrestrial carbon in a large-river food web. Ecology 89:1733–43.CrossRefPubMedGoogle Scholar
  87. Zimov SA. 2005. Pleistocene park: return of the mammoth’s ecosystem. Science 308:796–8.CrossRefPubMedGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  • Frank O. Masese
    • 1
    Email author
  • Kátya G. Abrantes
    • 2
  • Gretchen M. Gettel
    • 1
  • Steven Bouillon
    • 3
  • Kenneth Irvine
    • 1
  • Michael E. McClain
    • 1
  1. 1.Department of Water Science and EngineeringUNESCO-IHE Institute for Water EducationDelftThe Netherlands
  2. 2.Estuary and Tidal Wetland Ecosystems Research Group, School of Marine and Tropical Biology, Centre for Tropical Water and Aquatic Ecosystem Research (TropWater)James Cook UniversityTownsvilleAustralia
  3. 3.Department of Earth and Environmental SciencesKatholieke Universiteit Leuven (KU Leuven)LeuvenBelgium

Personalised recommendations