Microbial Ecology

, Volume 52, Issue 1, pp 1–9 | Cite as

Assessing Primary and Bacterial Production Rates in Biofilms on Pebbles in Ishite Stream, Japan

  • Miwa Fukuda
  • Junya Matsuyama
  • Toshiya Katano
  • Shin-ichi NakanoEmail author
  • Frank Dazzo


Various measurements of microbial productivity in streambed pebble biofilms were analyzed almost monthly for 1 year to quantify the importance of primary production as an autochthonous source of organic matter utilized to support heterotrophic bacterial production in the dynamic food web within this natural microbial habitat. Bacterial density varied from 0.3 × 108 to 1.4 × 108 cells cm−2, and chlorophyll a concentration ranged from 0.7 to 25.9 μg cm−2, with no coupled oscillation between seasonal changes in these two parameters. In bottle incubation experiments, the instantaneous bacterial growth rate of bacteria was significantly correlated with their production rate [measured by frequency of dividing cells (FDC)] as follows: ln μ = 0.138FDC − 3.003 (n = 15, r 2 = 0.445, p < 0.001). FDC values in the pebble biofilms increased with fluctuations during the study period, ranging from 3.6% to 9.2%. Bacterial production rates largely fluctuated between 0.15 to 0.92 μg C cm−2 h−1, and its seasonal pattern was similar to that of bacterial density. Net primary production measured between May 2002 to November 2002 attained minimum level (0.5 μg C cm−2 h−1) in June and maximum level (1.9 μg C cm−2 h−1) in August. Percentages of bacterial production to net primary production ranged between 21% and 120%. Because this ratio extends both below and above 100% for these parameters, it is likely that both autochthonous and allochthonous supplies of organic matter are important for production of bacteria in the pebble biofilms that develop in rapidly flowing fresh water streams.


Pebble Bacterial Production Dissolve Organic Matter Bacterial Abundance Bacterial Density 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



We are grateful to Prof. Suzuki and other members of the Marine Molecular Ecology Laboratory and Laboratory of Aquatic Food Web Dynamics, Ehime University, for advice, discussions, and encouragement throughout the study. We also thank the two anonymous reviewers for their critical but constructive comments on the manuscript. The present study was partly supported by the Grant-in-Aid for Scientific Research No. 14340245, 16370012 and 14208063, JSPS, and RR2002 at the Ehime University, and the Center for Microbial Ecology at Michigan State University.


  1. 1.
    Aizaki, M (1980) Changes in standing crop and photosynthetic rate attendant on the film development of periphyton in a shallow eutrophic river. Jpn J Limnol 41: 225–234 (in Japanese)Google Scholar
  2. 2.
    Allan, JD (1995) Physical factors of importance to the biota. In: Allan, JD (Ed.) Stream Ecology. Kluwer Academic Publishers, Dordrecht, pp 45–82Google Scholar
  3. 3.
    Austin, HK, Findlay, EG (1989) Benthic bacterial biomass and production in the Hudson River Estuary. Microb Ecol 18: 105–116CrossRefGoogle Scholar
  4. 4.
    Benner, R, Lay, J, K'nees, E, Hodson, RE (1988) Carbon conversion efficiency for bacterial growth on lignocellulose: implications for detritus-based food webs. Limnol Oceanogr 33: 1514–1526Google Scholar
  5. 5.
    Bott, TL (1996) Primary productivity and community respiration. In: Hauer, FR, Lamberti, GA (Eds.) Methods in Stream Ecology. Academic Press, San Diego, pp 533–556Google Scholar
  6. 6.
    Bott, TL, Brock, JT, Cushing, CE, Gregory, SV, King, D, Petersen, RC (1978) A comparison of methods for measuring primary productivity and community respiration in streams. Hydrobiologia 60: 3–12CrossRefGoogle Scholar
  7. 7.
    Cole, JJ, Findlay, S, Pace, ML (1988) Bacterial production in fresh and saltwater ecosystems: a cross-system overview. Mar Ecol Prog Ser 43: 1–10CrossRefGoogle Scholar
  8. 8.
    Coveney, MF, Cronberg, G, Enell, M, Larsson, K, Olofsson, L (1977) Phytoplankton, zooplankton and bacteria standing crop and relationships in a eutrophic lake. Oikos 29: 5–21CrossRefGoogle Scholar
  9. 9.
    Dazzo, FB, Liu, J, Jain, A, Prabhu, A, Reddy, C, Wadekar, M, Peretz, R, Bollempalli, R, Trione, D, Marshall, E, Zurdo, J, Hammoud, H, Wang, J, Li, M, McGarrell, D, Maya-Flores, J, Gantner, S, Dowling, C, Gomaa, AB, Yanni, Y (2004) CMEIAS v3.0 upgrade: Advanced image analysis software to strengthen microscopy-based approaches for understanding microbial ecology. The KBS LTER Site, Long-Term Ecological Research in Row-Crop Agriculture,
  10. 10.
    Eguchi, M, Nishikawa, T, MacDonald, K, Cavicchioli, R, Gottschal, JC, Kjelleberg, S (1996) Responses to stress and nutrient availability by the marine ultramicrobacterium Sphingomonas sp. strain RB2256. Appl Environ Microbiol 62: 1287–1294PubMedGoogle Scholar
  11. 11.
    Findlay, S, Meyer, JL, Risley, R (1986) Benthic bacterial biomass and production in two blackwater rivers. Can J Fish Aquat Sci 43: 1271–1276Google Scholar
  12. 12.
    Fischer, H, Pusch, M (2001) Comparison of bacterial production in sediments, epiphyton and the pelagic zone of a lowland river. Freshw Biol 46: 1335–1348CrossRefGoogle Scholar
  13. 13.
    Fukuda, M, Ashida, A, Tomaru, Y, Nakano, S (2004) An improved method for collecting heterotrophic microorganisms inhabiting on pebbles in streams. Limnology 5: 41–46CrossRefGoogle Scholar
  14. 14.
    Hagström, A, Larsson, U, Horstedt, P, Normark, S (1979) Frequency of dividing cells, a new approach to the determination of bacterial growth rates in aquatic environments. Appl Environ Microbiol 37: 805–812PubMedGoogle Scholar
  15. 15.
    Hanson, RB, Shafer, D, Ryan, T, Pope, DH, Lowery, HK (1983) Bacterioplankton in Antarctic ocean waters during late Austral winter: abundance, frequency of dividing cells, and estimates of production. Appl Environ Microbiol 45: 1622–1632PubMedGoogle Scholar
  16. 16.
    Hirotani, H, Matsui, Y, Sese, C, Kagawa, H (1992) Positive correlations between catchment areas and densities of bacteria in the upper reaches of a river. Water Sci Technol 26: 1965–1972Google Scholar
  17. 17.
    Hirotani, H, Sese, C, Kagawa, H (1999) Correlations of Aeromonas hydrophila with indicator bacteria of water quality and environmental factors in a mountain stream. Water Environ Res 71: 132–138CrossRefGoogle Scholar
  18. 18.
    Hori, M, Morikawa, K (2000) Studies on the dynamics of the protozoa in epilithon at Nishiaokidaira in the Akigawa River. Jpn J Limnol 61: 223–231 (in Japanese)Google Scholar
  19. 19.
    Hudson, JJ, Roff, JC, Burnison, BK (1992) Bacterial productivity in forested and open streams in Southern Ontario. Can J Fish Aquat Sci 49: 2412–2422CrossRefGoogle Scholar
  20. 20.
    Kaplan, LA, Bott, TL (1989) Diurnal fluctuations in bacterial activity on streambed substrata during vernal algal blooms: effects of temperature, water chemistry, and habitat. Limnol Oceanogr 34: 718–733Google Scholar
  21. 21.
    Kirchman, D (1983) The production of bacteria attached to particles suspended in a freshwater pond. Limnol Oceanogr 28: 858–872Google Scholar
  22. 22.
    Kjelleberg, S, Albertson, N, Flardh, K, Holmquist, L, Jouper-Jaan, A, Marouga, R, Ostling, J, Svenblad, B, Weichart, D (1993) How do non-differentiating bacteria adapt to starvation? Antonie van Leeuwenhoek 63: 333–341PubMedCrossRefGoogle Scholar
  23. 23.
    Kobayashi, T (1950) Japan local geological journal. Shikoku, Asakura Publications, Japan, pp 96–98 (in Japanese)Google Scholar
  24. 24.
    Lee, S, Fuhrman, JA (1987) Relationships between biovolume and biomass of naturally derived marine bacterioplankton. Appl Environ Microbiol 53: 1298–1303PubMedGoogle Scholar
  25. 25.
    Liu, J, Dazzo, FB, Glagoleva, O, Yu, B, Jain, AK (2001) CMEIAS: A computer-aided system for the image analysis of bacterial morphotypes in microbial communities. Microb Ecol 41: 173–194.> Google Scholar
  26. 26.
    Lock, MA, Wallace, RR, Costerton, JW, Ventullo, RM, Charlton, SE (1984) River epilithon: toward a structural–functional model. Oikos 42: 10–22CrossRefGoogle Scholar
  27. 27.
    Marxsen, J (1999) Importance of bacterial production in the carbon flow of an upland stream, the Breitenbach. Arch Hydrobiol Spec Issues Adv Limnol 54: 135–145Google Scholar
  28. 28.
    Matsuyama local weather station (2004) Weather data in Ehime Prefecture.
  29. 29.
    Meyer, JL (1988) Benthic bacterial biomass and production in a blackwater river. Verh Int Verein Limnol 23: 1832–1838Google Scholar
  30. 30.
    Moran, R, Porath, D (1980) Chlorophyll determination in intact tissues using N,N-dimethylformamide. Plant Physiol 65: 478–479PubMedCrossRefGoogle Scholar
  31. 31.
    Nagata, T (1987) Production rate of planktonic bacteria in the North Basin of Lake Biwa, Japan. Appl Environ Microbiol 53: 2872–2882PubMedGoogle Scholar
  32. 32.
    Nagata, T, Watanabe, Y (1990) Carbon- and nitrogen-to-volume ratios of bacterioplankton grown under different nutritional conditions. Appl Environ Microbiol 56: 1303–1309PubMedGoogle Scholar
  33. 33.
    Nakano, S (1992) Changes in bacterioplankton production and dominant algal species in the North Basin of Lake Biwa. Jpn J Limnol 53: 145–149Google Scholar
  34. 34.
    Nakano, A, Ban, S (2003) Microbial communities in oligotrophic Lake Toya, Japan. Limnology 4: 19–24CrossRefGoogle Scholar
  35. 35.
    Newell, SY, Christian, RR (1981) Frequency of dividing cells as an estimator of bacterial productivity. Appl Environ Microbiol 42: 23–31PubMedGoogle Scholar
  36. 36.
    Paul, EA, Harris, D, Klug, M, Ruess, R (1999) The determination of microbial biomass. In: Robertson, GP, Bledsoe, CS, Coleman, DC, Sollins, P (Eds.) Standard Soil Methods for Long-Term Ecological Research. Oxford University Press, New York, pp 291–317Google Scholar
  37. 37.
    Riemann, B, Sondergaard, M, Schierup, HH, Bosselmann, S, Christensen, G, Hansen, J, Nielsen, B (1982) Carbon metabolism during a spring diatom bloom in the eutrophic Lake Mosso. Int Rev Ges Hydrobiol 67: 145–185Google Scholar
  38. 38.
    Rier, ST, Stevenson, RJ (2002) Effects of light, dissolved organic carbon, and inorganic nutrients on the relationship between algae and heterotrophic bacteria in stream periphyton. Hydrobiologia 489: 179–184CrossRefGoogle Scholar
  39. 39.
    Robarts, RD, Zohary, T (1993) Fact or fiction—Bacterial growth rates and production as determined by [methyl-3H]-thymidine? In: Jones, JG (Ed.) Advances in Microbial Ecology. Plenum Press, New York, pp 371–425Google Scholar
  40. 40.
    Romani, AM, Sabater, S (2001) Structure and activity of rock and sand biofilms in a Mediterranean stream. Ecology 82: 3232–3245Google Scholar
  41. 41.
    Rosenfeld, JS, Hudson, JJ (1997) Primary production, bacterial production, and invertebrate biomass in pools and riffles in southern Ontario streams. Arch Hydrobiol 139: 301–316Google Scholar
  42. 42.
    Seitzinger, SP, Hartnett, H, Lauck, R, Mazurek, M, Minegishi, T, Spyres, G, Styles, R (2005) Molecular-level chemical characterization and bioavailability of dissolved organic matter in stream water using electrospray-ionization mass spectrometry. Limnol Oceanogr 50: 1–12CrossRefGoogle Scholar
  43. 43.
    Silvester, NR, Sleigh, MA (1985) The forces on microorganisms at surfaces in flowing water. Freshw Biol 15: 433–448CrossRefGoogle Scholar
  44. 44.
    Someya, T (1995) Three-dimensional observation of soil bacteria in organic debris with a confocal laser scanning microscope. Soil Microorganisms 46: 61–69Google Scholar
  45. 45.
    Steinman, AD, Lamberti, GA (1996) Biomass and pigments of benthic algae. In: Hauer FR, Lamberti, GA (Eds.) Methods in Stream Ecology. Academic Press, San Diego, pp 295–313Google Scholar
  46. 46.
    Strickland, JD, Parsons TR (1972) A Practical Handbook of Seawater Analysis, 2nd ed. Fisheries Research Board of Canada Ottawa, CanadaGoogle Scholar
  47. 47.
    Suehiro, S, Tezuka, Y (1981) Seasonal change in ciliate populations in the bottom sediment of a polluted river. Jpn J Limnol 42: 1–7Google Scholar
  48. 48.
    Tanaka, N, Nakanishi, M, Kadota, H (1974) The excretion of photosynthetic product by natural phytoplankton population in Lake Biwa. Jpn J Limnol 35: 91–98Google Scholar
  49. 49.
    Tanaka, N, Nakanishi, M, Kadota, H (1975) Seasonal variation of glycollate-utilizing bacteria in the water column of Lake Biwa. Bull Jpn Soc Sci Fish 41: 1129–1134Google Scholar
  50. 50.
    Torella, F, Morita, RY (1986) Microcultural study of bacterial size changes and microcolony and ultramicrocolony formation by heterotrophic bacteria in seawater. Appl Environ Microbiol 41: 518–527Google Scholar
  51. 51.
    Vadstein, O, Harkjerr, BO, Jensen, A, Olsen, Y, Reinertsen, H (1989) Cycling of organic carbon in the photic zone of a eutrophic lake with special reference to the heterotrophic bacteria. Limnol Oceanogr 34: 840–855CrossRefGoogle Scholar
  52. 52.
    Vogel, S (1994) Life in Moving Fluids. Princeton University Press, Princeton, NJGoogle Scholar
  53. 53.
    Watanabe, Y (2000) Determination of photosynthetic productivity in riverine environments. In: The Tama River Ecological Research Group (Ed.) Comprehensive Study of The Tama River, pp 33–36Google Scholar
  54. 54.
    Wetzel, RG, Likens, GE (1990) Primary productivity of phytoplankton In: Wetzel, RG, Likens, GE (Eds.) Limnological Analysis. Springer-Verlag, New York, pp 207–226Google Scholar
  55. 55.
    White, PA, Kalff, J, Rasmussen, JB, Gasol, JM (1991) The effect of temperature and algal biomass on bacterial production and specific growth rate in freshwater and marine habitats. Microb Ecol 21: 99–118CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, Inc. 2006

Authors and Affiliations

  • Miwa Fukuda
    • 1
  • Junya Matsuyama
    • 1
  • Toshiya Katano
    • 2
    • 3
  • Shin-ichi Nakano
    • 1
    Email author
  • Frank Dazzo
    • 4
  1. 1.Laboratory of Aquatic Food Web DynamicsEhime UniversityMatsuyamaJapan
  2. 2.Center of Marine Environmental StudiesEhime UniversityMatsuyamaJapan
  3. 3.Department of Life Science/Environmental ScienceHanyang UniversitySeoulSouth Korea
  4. 4.Department of Microbiology and Molecular GeneticsMichigan State UniversityEast LansingUSA

Personalised recommendations