Advertisement

Hydrobiologia

, Volume 347, Issue 1–3, pp 171–184 | Cite as

Diatoms as quantitative indicators of pH and water temperature in subarctic Fennoscandian lakes

  • Jan Weckström
  • Atte Korhola
  • Tom Blom
Article

Abstract

Weighted averaging (WA) regression and calibrationbased optima and tolerances of lakewater pH andtemperature are presented for diatoms in ecologicallysensitive, subarctic Fennoscandian lakes. The studysites are mostly small, simple, oligotrophic,low-conductivity lakes with a pH range from 5.0 to7.7 and a temperature range (after data screening)from 9.3 to 15.0 °C. Experiments with inverse andclassical deshrinking, with or without tolerancedownweighting, were used to identify the bestcalibration functions. The model estimates wereadjusted by jackknifing procedures. WA by inversedeshrinking and with tolerance downweighting performedbest for pH prediction, whereas simple WA wasmarginally superior for predicting water temperature.The established pH model is accurate to within± 0.39 H units, and the temperature model towithin ± 0.88 degrees Celcius. Fifteen diatom taxawere identified as potential indicator species for pHand three for temperature.

diatoms pH water temperature weightedaveraging inference model subarctic Fennoscandia 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Atlas of Finland, 1986. Appendix 132, water. National board of survey & Geographical society of Finland, 31 pp.Google Scholar
  2. Anderson, N. J., 1993. Natural versus anthropogenic change in lakes: the role of the sediment record. Trends Ecol. Evol. 8: 356–361.Google Scholar
  3. Battarbee, R. W., 1991. Recent palaeolimnology and diatom-based environmental reconstruction. In Shane, L. C. & E. J. Cushing (eds), Quaternary Landscapes. Belhaven Press, London: 129–174.Google Scholar
  4. Bennion, H., S. Juggins & N. J. Anderson, 1996. Predicting epilimnetic phosphorus concentrations using improved diatom-based transfer function and its application to lake eutrophication management. Envir. Sci. Technol. 30: 2004–2007.Google Scholar
  5. Birks, H. J. B., 1996. Contributions of Quaternary palaeoecology to nature conservation. J. veg. Sci. 7: 89–98.Google Scholar
  6. Birks, H. J. B., J. M. Line, S. Juggins, A. C. Stevenson, & C. F. J. ter Braak, 1990. Diatoms and pH reconstructions. Phil. Trans. r. Soc. Lond. B 327: 263–278.Google Scholar
  7. Charles, D. F., 1985. Relationship between surface sediment diatom assemblages and lakewater characteristics in Adirondack lakes. Ecology 66: 994–1011.Google Scholar
  8. Charles, D. F. & J. P. Smol, 1994. Long-term chemical changes in lakes: quantitative inferences from biotic remains in the sediment record. In Baker, L. (ed.), Environmental chemistry of lakes and reservoirs. Advances in Chemistry Series 237. Washington, DC: American Chemical Society: 3–31.Google Scholar
  9. Charles, D. F., J. P. Smol & D. R. Engstrom, 1994. Paleolimnological approaches to biological monitoring. In Loeb, S. L. & A. Spacie (eds), Biological monitoring of aquatic systems. Boca Raton, FL: CRC Press: 233–293.Google Scholar
  10. Dixit, S. S., J. P. Smol, J. C. Kingston & D. F. Charles, 1992. Diatoms: Powerful indicators of environmental change. Envir. Sci. Technol. 26: 23–33.Google Scholar
  11. Dixit, S. S., B. F. Cumming, H. J. B. Birks, J. P. Smol, J. C. Kingston, A. J. Uutala, D. F. Charles & K. E. Camburn, 1993. Diatom assemblages from Adirondack lakes (New York, USA) and the development of inference models for retrospective environmental assessment. J. Paleolimnol. 8: 27–47.Google Scholar
  12. Dixit, S. S. & J. P. Smol, 1994. Diatoms as indicators in the Environmental Monitoring and Assessment Program-Surface Waters (EMAP-SW). Envir. Monit. Assess. 31: 275–306.Google Scholar
  13. Douglas, M. S. V., J. P. Smol & W. Jr. Blake, 1994. Marked post-18th century environmental change in high arctic ecosystems. Science 266: 416–419.Google Scholar
  14. Efron, B., 1982. The jacknife, the bootstrap and other resampling plans. Monogr. 38. Philadelphia, Pennysylvania Society for industrial and applied mathematics.Google Scholar
  15. Haila, Y., 1992. Measuring nature: quantitative data in field biology. In Clarke, A. E. & J. H. Fujimura (eds), The Right Tools for the Job–At Work in Twentieth Century Life Sciences. Princeton University Press, Princeton, NJ: 233–253.Google Scholar
  16. Hall, R. I. & J. P. Smol, 1996. Paleolimnological assessment of long-term water-quality changes in south-central Ontario lakes affected by cottage development and acidification. Can. J. Fish. aquat. Sci. 53: 1–17.Google Scholar
  17. Hartley, B., 1986. Acheck-list of the freshwater, brackish andmarine diatoms of the British Isles and adjoining coastal waters. J. mar. biol. Ass. 66: 531–610.Google Scholar
  18. Hill, M. O., 1973. Diversity and evennes: a unifying notation and its consequences. Ecology 54: 427–432.Google Scholar
  19. Hustedt, F., 1957. Die Diatomeenflora des Hubsystems der Weser im Gebiet der Hansestadt Bremen. Abh. Naturw. Ver. Bremen 34: 181–440.Google Scholar
  20. Huttunen, P. & J. Turkia, 1990. Surface sediment diatom assemblages and lake acidity. In Kauppi, P., P. Anttila & K. Kenttämies (eds), Acidification in Finland. Springer-Verlag, Berlin/Heidelberg: 995–1008.Google Scholar
  21. Jones, V. J. & S. Juggins, 1995. The construction of a diatom-based chlorophyll atransfer function and its application at three lakes on Signy Island (maritime Antartic) subject to differing degrees of nutrient enrichment. Freshwat. Biol. 34: 433–445.Google Scholar
  22. Juggins, S. & C. J. F. ter Braak, 1992. CALIBRATE–a program for species-environment calibration by [weighted averaging] partial least squares regression. Environmental Change Research Centre, University of Collage London.Google Scholar
  23. Korhola, A., 1996. Northern lakes as key witnesses for climatic change. Universitas Helsingiensis 3: 16–19.Google Scholar
  24. Korhola, A. & T. Blom, 1996. Marked early 20th century pollution and the subsequent recovery of Töölö Bay, central Helsinki, as indicated by subfossil diatom assemblage changes. Hydrobiologia 341: 169–179.Google Scholar
  25. Korhola, A., J. Virkanen, M. Tikkanen & T. Blom, 1996. Fireinduced pH rise in a naturally acid hill-top lake, southern Finland: a palaeoecological survey. J. Ecol. 84: 257–265.Google Scholar
  26. Korsman, T. & H. J. B. Birks, 1996. Diatom-based water chemistry reconstructions from northern Sweden: a comparison of reconstruction techniques. J. Paleolimnol. 15: 65–77.Google Scholar
  27. Martens, H. & T. Naes. 1989. Multivariate Calibration. John Wiley, Chichester.Google Scholar
  28. Moser, K. A., G. M. MacDonald & J. P. Smol, 1996. Applications of freshwater diatoms to geographical research. Progr. Phys. Geogr. 20: 21–52.Google Scholar
  29. Mölder, K. & R. Tynni, 1973. Über Finnlands rezente und subfossile Diatomeen VII. Bull. Geol. Soc. Finland 45: 159–179.Google Scholar
  30. Oksanen, J., E. Läärä, P. Huttunen & J. Meriläinen, 1988. Estimation of pH optima and tolerances of diatoms in lake sediments by the methods of weighting averaging, least squares and maximum likelihood, and their use for predicton of lake acidity. J. Paleolimnol. 1: 39–49.Google Scholar
  31. Olander, H., A. Korhola & T. Blom, 1996. Surface sediment Chironomidae (Insecta: Diptera) distributions along an ecotonal transect in subarctic Fennoskandia: developing a tool for palaeotemperature reconstructions. J. Paleolimnol. (in press)Google Scholar
  32. Patrick, R. & C. Reimer, 1966. The Diatoms of United States. Vol 1: Fragilariaceae, Eunotiaceae, Achnanthaceae, Naviculaceae. The Academy of Natural Sciences of Philadelphia, Philadelphia, 688 pp.Google Scholar
  33. Patrick, R. & C. Reimer, 1975. The Diatoms of United States. Vol 2: Entomoneidaceae, Cymbellaceae, Gomphonemaceae, Epithemiaceae. The Academy of Natural Sciences of Philadelphia, Philadelphia, 213 pp.Google Scholar
  34. Pienitz, R. & J. P. Smol, 1993. Diatom assemblages and their relationship to environmental variables in lakes from the boreal forest-tundra ecotone near Yellowknife, Northwest Territories, Canada. Hydrobiologia 269/270: 391–404.Google Scholar
  35. Pienitz, R., J. P. Smol & H. J. B. Birks, 1995. Assessment of freshwater diatoms as quantitative indicators of past climatic change in the Yukon and Northwest Territories, Canada. J. Paleolimnol. 13: 21–49.Google Scholar
  36. Reynolds, C. S., 1990. Temporal scales of variability in pelagic environments and response of phytoplankton. Freshwat. Biol. 23: 25–53.Google Scholar
  37. Salonen, K., 1979. A versatile method for the rapid and accurate determination of carbon by high temperature combustion. Limnol. Oceanogr. 24: 177–183.Google Scholar
  38. Seppä, H., 1996. Post-glacial dynamics of vegetation and tree-lines in the far north of Fennoscandia. Fennia 174: 1–96.Google Scholar
  39. Smol, J. P., 1992. Paleolimnology: An important tool for effective ecosystem management. J. Ecosystem Health 1: 49–58.Google Scholar
  40. Smol, J. P., 1995. Paleolimnological approaches to the evaluation and monitoring of ecosystem health: providing a history for environmental damage and recovery. In Rapport, UJ. D., C. L. Gaudet & P. Calow (eds), Evaluating and Monitoring the Health of Large-ScaleEcosystems.NATO ASI Series 128. Springer-Verlag, Berlin, Heidelberg: 301–318.Google Scholar
  41. Smol, J. P., I. R. Walker & P. R. Leavitt, 1991. Paleolimnology and hindcasting climatic trends. Verh. int. Ver. Limnol. 24: 1240–1246.Google Scholar
  42. Stevenson, A. C., S. Juggins, H. J. B. Birks, D. S. Anderson, N. J. Anderson, R.W. Battarbee, F. Berge, R. B. Davis, R. J. Flower, E. Y. Haworth, V. J. Jones, J. C. Kingston, A. M. Kreiser, J. M. Line, M. A. R. Munro & I. Renberg, 1991. The surface waters acidification project palaeolimnology programme: modern diatom/lake-water chemistry data-set. ENSIS Publishing, London, 86 pp.Google Scholar
  43. ter Braak, C. J. F., 1986. Canonical correspondence analysis: a new eigenvector method for multivariate direct gradient analysis. Ecology 67: 1167–1179.Google Scholar
  44. ter Braak, C. J. F., 1988. CANOCO–FORTRAN program for canonical community ordination by [partial] [detrended] [canonical] correspondence analysis, principal components analysis and redundancy analysis (version 2.1). TNO Institute of Applied Computer Sciences, Wageningen, 95 pp.Google Scholar
  45. ter Braak, C. J. F., 1990. Update notes: CANOCO version 3.10. Wageningen: Agricultural Mathematics group, 35 pp.Google Scholar
  46. ter Braak, C. J. F., 1994. Canonical community ordination. Part I: Basic theory and linear methods. Écoscience 1: 127–140.Google Scholar
  47. ter Braak, C. J. F. & C. W. N. Looman, 1986. Weighted averaging, logistic regression and the Gaussian response model. Vegetatio 65: 3–11.Google Scholar
  48. ter Braak, C. J. F. & H. Van Dam, 1989. Inferring pH from diatoms: a comparison of old and new calibration methods. Hydrobiologia 178: 209–223.Google Scholar
  49. ter Braak, C. J. F. & S. Juggins, 1993. Weighted averaging partial least squares regression (WA-PLS): an improved method for reconstructing environmental variables from species assemblages. Hydrobiologia 269/270: 485–502.Google Scholar
  50. Tynni, R., 1975–80. Über Finnlands rezente und subfossile Diatomeen. Geol. Surv. Finland, Bulletins Vols 274: 1–55; 284: 1–37; 296: 1–55; 312: 1–93.Google Scholar
  51. Weckström, J., A. Korhola & T. Blom, 1997. The relationship between diatoms and water temperature in 30 subarctic Fennoscandian lakes. Arct. Alp. Res. 29: 75–92.Google Scholar

Copyright information

© Kluwer Academic Publishers 1997

Authors and Affiliations

  • Jan Weckström
    • 1
  • Atte Korhola
    • 1
  • Tom Blom
    • 1
  1. 1.Laboratory of Physical GeographyUniversity of HelsinkiFinland

Personalised recommendations