Advertisement

Ecosystems

pp 1–18 | Cite as

Origin of Fish Biomass in a Diverse Subtropical River: An Allochthonic-Supported Biomass Increase Following Flood Pulses

  • Ivan González-BergonzoniEmail author
  • Alejandro D’Anatro
  • Nicolás Vidal
  • Samanta Stebniki
  • Giancarlo Tesitore
  • Ivana Silva
  • Franco Teixeira de Mello
Article
  • 25 Downloads

Abstract

The origin of resources supporting metazoan biomass in rivers has long been a subject of debate. The river wave concept (RWC) postulates that the energetic basis of food webs varies along its spatial–temporal location with respect to flow pulses. According to the RWC, river flow determines carbon assimilation in food webs, but this may also depend on river geomorphology. However, studies testing this theory are scarce, particularly those from large subtropical rivers. To analyse the origin of fish biomass in areas of differing geomorphology, we combined stable isotope analysis with standardised measurements of biomass of a diverse fish assemblage along the lower Uruguay River. Furthermore, using 14 years of monitoring data, we tested for relationships between the biomass of species dominantly fuelled by allochthonic resources and the river flow. Fish biomass was dominantly allochthonous-derived along most of the studied sites. At all trophic levels, autochthonous-derived fish biomass was the highest in an upstream anabranch functional process zone (FPZ) (fuelling 54% of the total biomass), while allochthonous-derived biomass prevailed downstream, in the widest sections of an unconstrained lowland FPZ (fuelling 64–72% of the total biomass). Moreover, the dominant species that derived most of its biomass from allochthonous resources (Prochilodus lineatus) increased its biomass following flood pulses. This study supports the RWC statements that, at a spatial scale, local river geomorphology affects fuelling sources for food webs (probably by determining contrasting resource availability scenarios) and, at a temporal scale, increases in the allochthonous fraction of biomass are driven by flood pulses.

Keywords

river wave concept river food webs energy subsidies fuelling resources allochthonous carbon Uruguay River Prochilodus lineatus 

Notes

Acknowledgements

We gratefully thank the many students and researchers that helped with the fish monitoring sampling campaigns, namely Jukka Tana, Diego Larrea, Roberto Ballabio, Malvina Masdeu, Daniel Garcia, Emanuel Machín, Juan Manuel Martinez, Sebastian Serra, Joaquín Pais, Anahí López and Matias Zarucki. We also thank the artisanal fisherman from Las Cañas, Elbio Russo, and the wildlife park ranger from Nuevo Berlin, Angel Rosano for their constant support and collaboration with sampling and fisheries data. This research project was partly funded by the Scientific Research Sectorial Commission (Uruguay) (Project CSIC I + D_2016_577-348) and the National Agency for Innovation and Research (ANII) (Project ANII-FCE_2_2016_1_126780). From 2005, sampling campaigns were financed by the UPM pulp mill environmental monitoring programme; we thank Gervasio Gonzalez for logistics and data accessibility. IGB, AD, NV and FTM received financial support by the ANII National System of Researchers (SNI), and IGB also received financial support from a ANII scholarship (ANII PD_NAC_2015_1_108121).

Compliance with Ethical Standards

Conflict of interest

The authors declare that they have no conflict of interest.

Supplementary material

10021_2019_370_MOESM1_ESM.docx (325 kb)
Supplementary material 1 (DOCX 324 kb)
10021_2019_370_MOESM2_ESM.docx (13 kb)
Supplementary material 2 (DOCX 12 kb)

References

  1. Anderson MJ. 2001. A new method for non-parametric multivariate analysis of variance. Aust Ecol 26:32–46.Google Scholar
  2. Araujo-Lima CARM, Forsberg BR, Victoria R, Martinelli L. 1986. Energy sources for detritivorous fishes in the Amazon. Science 4781:1256–8.CrossRefGoogle Scholar
  3. Arim M, Bozinovic F, Marquet PA. 2007. On the relationship between trophic position, body mass and temperature: reformulating the energy limitation hypothesis. Oikos 116:1524–30.CrossRefGoogle Scholar
  4. Arim M, Abades SR, Laufer G, Loureiro M, Marquet PA. 2010. Food web structure and body size: trophic position and resource acquisition. Oikos 119:147–53.CrossRefGoogle Scholar
  5. Baumgartner G, Nakatani K, Cavicchioli M, Baumgartner MdST. 1997. Some aspects of the ecology of fish larvae in the floodplain of the high Paraná river, Brazil. Rev Bras Zool 14:551–63.CrossRefGoogle Scholar
  6. Bayley PB. 1973. Studies on the migratory characin, Prochilodus platensis Holmberg 1889, (Pisces, Characoidei) in the River Pilcomayo, South America. J Fish Biol 5:25–40.CrossRefGoogle Scholar
  7. Brito EF, Moulton TP, De Souza ML, Bunn SE. 2006. Stable isotope analysis indicates microalgae as the predominant food source of fauna in a coastal forest stream, south-east Brazil. Aust Ecol 31:623–33.CrossRefGoogle Scholar
  8. Bunn SE, Davies PM, Winning M. 2003. Sources of organic carbon supporting the food web of an arid zone floodplain river. Freshw Biol 48:619–35.CrossRefGoogle Scholar
  9. 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
  10. Caraco N, Bauer JE, Cole JJ, Petsch S, Raymond P. 2010. Millennial-aged organic carbon subsidies to a modern river food web. Ecology 91:2385–93.CrossRefGoogle Scholar
  11. Cole JJ, Solomon CT. 2012. Terrestrial support of zebra mussels and the Hudson River food web: a multi-isotope, Bayesian analysis. Limnol Oceanogr 57:1802–15.CrossRefGoogle Scholar
  12. Collins SM, Kohler TJ, Thomas SA, Fetzer WW, Flecker AS. 2016. The importance of terrestrial subsidies in stream food webs varies along a stream size gradient. Oikos 125:674–85.CrossRefGoogle Scholar
  13. Delong M, Thorp J. 2006. Significance of instream autotrophs in trophic dynamics of the Upper Mississippi River. Oecologia 147:76–85.CrossRefGoogle Scholar
  14. Espinach Ros A, Sverlij S, Amestoy F, Spinetti M. 1998. Migration pattern of the sabalo Prochilodus lineatus (Pisces, Prochilodontidae) tagged in the lower Uruguay River. SIL Proc 26(5):2234–6.Google Scholar
  15. Fry B. 2013. Alternative approaches for solving underdetermined isotope mixing problems. Mar Ecol Prog Ser 472:1–13.CrossRefGoogle Scholar
  16. Fuentes CM, Espinach Ros A. 1998. Variación de la actividad reproductiva del Sábalo, Prochilodus Lineatus (Valenciennes, 1847), estimada por el flujo de larvas en el Río Paraná inferior. Nat Neotropicalis 29:25–32.Google Scholar
  17. González-Bergonzoni I, D’Anatro A, Stebniki S, Teixeira de Mello F. 2015. Estructura comunitaria y diversidad de peces en el Rio Uruguay: monitoreo en la zona receptora de efluentes de la planta de pasta de celulosa UPM S.A, Noviembre 2014. UPM S.A, Fray Bentos, Uruguay. p 29.Google Scholar
  18. González-Bergonzoni I, Kristensen PB, Baattrup-Pedersen A, Kristensen EA, Alnoee AB, Riis T. 2018. Riparian forest modifies fuelling sources for stream food webs but not food-chain length in lowland streams of Denmark. Hydrobiologia 805:291–310.CrossRefGoogle Scholar
  19. Hamilton SK, Lewis WM, Sippel SJ. 1992. Energy sources for aquatic animals in the Orinoco River floodplain: evidence from stable isotopes. Oecologia 89:324–30.CrossRefGoogle Scholar
  20. Hayden B, McWilliam-Hughes SM, Cunjak RA. 2016. Evidence for limited trophic transfer of allochthonous energy in temperate river food webs. Freshw Sci 35:544–58.CrossRefGoogle Scholar
  21. Hoeinghaus D, Winemiller K, Agostinho A. 2007. Landscape-scale hydrologic characteristics differentiate patterns of carbon flow in large-river food bebs. Ecosystems 10:1019–33.CrossRefGoogle Scholar
  22. Hoffman JC, Bronk DA, Olney JE. 2007. Contribution of allochthonous carbon to American shad production in the Mattaponi River, Virginia, using stable isotopes. Estuar Coasts 30:1034–48.CrossRefGoogle Scholar
  23. Humphries P, Keckeis H, Finlayson B. 2014. The river wave concept: integrating river ecosystem models. BioScience 64:870–82.CrossRefGoogle Scholar
  24. Jardine TD, Hunt RJ, Faggotter SJ, Valdez D, Burford MA, Bunn SE. 2013. Carbon from periphyton supports fish biomass in waterholes of a wet–dry tropical river. River Res Appl 29:560–73.CrossRefGoogle Scholar
  25. Jardine TD, Rayner TS, Petit NE, Valdez D, Ward DP, Linder G, Douglas MM, Bunn SE. 2017. Body size drives allochthony in food webs of tropical rivers. Oecologia 183:505–17.CrossRefGoogle Scholar
  26. Junk WJ, Bayley PB, Sparks RE. 1989. The flood pulse concept in river-floodplain systems. In: Dodge DP, Eds. Proceedings of the international large river symposium (LARS). Canadian Special Publication of Fisheries and Aquatic Sciences 106. pp 110–127.Google Scholar
  27. Krepper CM, García NO, Jones PD. 2003. Interannual variability in the Uruguay river basin. Int J Climatol 23:103–15.CrossRefGoogle Scholar
  28. LATU. 2015. Informe sobre caracterización biológica en el tramo inferior del Río Uruguay, febrero-noviembre 2015. Laboratorio Tecnológico del Uruguay, Montevideo, Uruguay. p 81.Google Scholar
  29. Lau DCP, Leung KMY, Dudgeon D. 2009a. Are autochthonous foods more important than allochthonous resources to benthic consumers in tropical headwater streams? J N Am Benthol Soc 28:426–39.CrossRefGoogle Scholar
  30. Lau DCP, Leung KMY, Dudgeon D. 2009b. What does stable isotope analysis reveal about trophic relationships and the relative importance of allochthonous and autochthonous resources in tropical streams? A synthetic study from Hong Kong. Freshw Biol 54:127–41.CrossRefGoogle Scholar
  31. Levin LA, Currin C. 2012. Stable isotope protocols: sampling and sample procesing Scripps Institution of Oceanography Technical Report, eScholarship, University of California.Google Scholar
  32. Lewis WM Jr, Hamilton SK, Rodriquez MA, Saunders JFIII, Lasi DH. 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
  33. Li AOY, Dudgeon D. 2008. Food resources of shredders and other benthic macroinvertebrates in relation to shading conditions in tropical Hong Kong streams. Freshw Biol 53:2011–25.CrossRefGoogle Scholar
  34. Lopes CA, Manetta GI, Figueiredo BRS, Martinelli LA, Benedito E. 2015. Carbon from littoral producers is the major source of energy for bottom-feeding fish in a tropical floodplain. Environ Biol Fishes 98:1081–8.CrossRefGoogle Scholar
  35. Marchese MR, Saigo M, Zili FL, Capello S, Devercelli M, Montalto L, Paporello G, Wantzen KM. 2014. Food webs of the Paraná River floodplain: assessing basal sources using stable carbon and nitrogen isotopes. Limnol Ecol Manag Inland Waters 46:22–30.CrossRefGoogle Scholar
  36. Mintenbeck K, Brey T, Jacob U, Knust R, Struck U. 2008. How to account for the lipid effect on carbon stable-isotope ratio (δ13C): sample treatment effects and model bias. J Fish Biol 72:815–30.CrossRefGoogle Scholar
  37. Moulton TP. 2006. Why the world is green, the waters are blue and food webs in small streams in the atlantic rainforest are predominantly driven by microalgae? Oecol Aust 10:78–89.Google Scholar
  38. Oldani NO, Iwaszkim IM, Pandini OH. 1992. Flutuaciones de la abundaneia de peces en el Alto Parana (Corrientes, Argentina). Publicaciones de la Comisión Administradora del Río Uruguay 1:43–55.Google Scholar
  39. Parnell A, Inger R, Bearhop S. 2010. Source partitioning using stable isotopes: coping with too much variation. PLoS ONE 5:e9672.CrossRefGoogle Scholar
  40. Phillips DL. 2012. Converting isotope values to diet composition: the use of mixing models. J Mammal 93:342–52.CrossRefGoogle Scholar
  41. 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
  42. Post DM. 2002. Using stable isotopes to estimate trophic position: models, methods, and assumptions. Ecology 83:703–18.CrossRefGoogle Scholar
  43. Post DM, Layman CA, Arrington DA, Takimoto G, Quattrochi J, Montaña 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.CrossRefGoogle Scholar
  44. R Development Core Team. 2018. R: a language and environment for statistical computing. Vienna: R Foundation for Statistical Computing.Google Scholar
  45. Roach KA, Winemiller KO. 2015. Hydrologic regime and turbidity influence entrance of terrestrial material into river food webs. Can Fish Aquat Sci 72:1099–112.CrossRefGoogle Scholar
  46. Stassen MJM, van de Ven MWPM, van der Heide T, Guerrero Hiza MA, van der Velde G, Smolders AJP. 2010. Population dynamics of the migratory fish Prochilodus lineatus in a neotropical river: the relationships with river discharge, flood pulse, El Niño and fluvial megafan behaviour. Neotrop Ichthyol 8:113–22.CrossRefGoogle Scholar
  47. 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
  48. Teixeira de Mello F, González-Bergonzoni I, Loureiro M. 2011. Peces de agua dulce del Uruguay. PPR-MGAP (Montevideo, Uruguay).Google Scholar
  49. Thoms MC, Delong MA, Collins SE, Flotemersch JH. 2017. Physical heterogeneity and aquatic community function in river networks: a case study from the Kanawha River Basin, USA. Geomorphology 290:277–87.CrossRefGoogle Scholar
  50. Thorp JH, Bowes RE. 2017. Carbon sources in riverine food webs: new evidence from amino acid isotope techniques. Ecosystems 20:1029–41.CrossRefGoogle Scholar
  51. Thorp JH, Delong MD. 1994. The riverine productivity model: an heuristic view of carbon sources and organic processing in large river ecosystems. Oxford: Blackwell.Google Scholar
  52. Thorp JH, Delong MD. 2002. Dominance of autochthonous autotrophic carbon in food webs of heterotrophic rivers. Oikos 96:543–50.CrossRefGoogle Scholar
  53. Thorp JH, Thoms MC, Delong MD. 2008. The riverine ecosystem synthesis: toward conceptual cohesiveness in river science. Amsterdam: Academic Press/Elsevier.CrossRefGoogle Scholar
  54. 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
  55. Wang J, Gu B, Huang J, Han X, Lin G, Zheng F, Li Y. 2014. Terrestrial contributions to the aquatic food web in the middle Yangtze River. PLOS ONE 9:e102473.CrossRefGoogle Scholar
  56. Winemiller KO, Jepsen DB. 1998. Effects of seasonality and fish movement on tropical river food webs. J Fish Biol 53:267–96.CrossRefGoogle Scholar
  57. Zeug SC, Winemiller KO. 2008. Evidence supporting the importance of terrestrial carbon in a large-river food web. Ecology 89:1733–43.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  • Ivan González-Bergonzoni
    • 1
    • 2
    • 3
    Email author
  • Alejandro D’Anatro
    • 2
  • Nicolás Vidal
    • 2
  • Samanta Stebniki
    • 2
  • Giancarlo Tesitore
    • 2
    • 4
  • Ivana Silva
    • 1
    • 2
    • 3
  • Franco Teixeira de Mello
    • 4
  1. 1.Departamento de Ecología y Biología EvolutivaInstituto de Investigaciones Biológicas Clemente EstableMontevideoUruguay
  2. 2.Departamento de Ecología y Evolución, Facultad de CienciasUniversidad de la RepúblicaMontevideoUruguay
  3. 3.Departamento del Agua, CENUR Litoral NortePaysandúUruguay
  4. 4.Departamento de Ecología y Gestión Ambiental CUREUniversidad de la RepúblicaMaldonadoUruguay

Personalised recommendations