Skip to main content
SpringerLink
Log in

Identifying cardinal dates in phytoplankton time series to enable the analysis of long-term trends

  • Global Change and Conservation Ecology
  • Published:
Oecologia Aims and scope Submit manuscript

Abstract

Phenology and seasonal succession in aquatic ecosystems are strongly dependent on physical factors. In order to promote investigations into this coupling, methods of characterising annual time series of phytoplankton were derived and applied to a 31-year data set from Saidenbach Reservoir (Saxony, Germany). Field data are often scarce and irregularly sampled, particularly in the transition period from winter to spring, so reliable methods of determining cardinal dates in the time series are necessary. The proposed methods were used to determine the beginning, maximum and end of the spring mass development of phytoplankton by estimating the inflexion points (A), fitting a Weibull-type function (B) and fitting linear segments to the logarithmic values (C). For the data set from Saidenbach Reservoir, all three methods proved to be relevant to the analysis of long-term trends. Differences between the maxima determined by the different methods seemed small, but there were deviations when the maximum was related to physical factors such as ice-out. The Weibull-type fit gave the most reliable and comprehensible results and is recommended for trend analyses. For all methods, long-term analysis of the duration of the spring mass development and the duration of the spring full circulation revealed a period of consistently low values (1975–1990) followed by a period of higher values (1990–2005). These periods were also identified for the date of ice-out, although in this case there was a period of high values followed by a period of low values. A sensitivity analysis that compared results from subsampled time series with increasing time intervals indicated that a minimum of one sample every three weeks is needed to obtain reliable results.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

Notes

  1. source: http://www.cgd.ucar.edu/cas/jhurrell/nao.stat.winter.html

References

  • Adrian R, Walz N, Hintze T, Hoeg S, Rusche R (1999) Effects of ice duration on plankton succession during spring in a shallow polymictic lake. Freshw Biol 41(3):621–634

    Article  Google Scholar 

  • Anneville O, Souissi S, Gammeter S, Straile D (2004) Seasonal and inter-annual scales of variability in phytoplankton assemblages: comparison of phytoplankton dynamics in three perialpine lakes over a period of 28 years. Freshw Biol 49:98–115

    Article  Google Scholar 

  • Backhaus JO, Hegseth EN, Wehde H, Irigoien X, Hatten K, Logemann K (2003) Convection and primary production in winter. Mar Ecol Prog Ser 251:1–14

    Google Scholar 

  • Benndorf J, Kranich J, Mehner T, Wagner A (2001) Temperature impact on the midsummer decline of Daphnia galeata: an analysis of long-term data from the biomanipulated Bautzen Reservoir (Germany). Freshw Biol 46:199–211

    Article  Google Scholar 

  • Blenckner T, Omstedt A, Rummukainen M (2002) A Swedish case study of contemporary and possible future consequences of climate change on lake function. Aquat Sci 64:171–184

    Article  Google Scholar 

  • Durant JM, Hjermann DO, Anker-Nilssen T, Beaugrand G,Mysterud A, Pettorelli N, Stenseth NC (2005) Timing and abundance as key mechanisms affecting trophic interactions in variable environments. Ecol Lett 8(9):952–958

    Article  Google Scholar 

  • Edwards M, Richardson AJ (2004) Impact of climate change on marine pelagic phenology and trophic mismatch. Nature 430:881–884

    Article  PubMed  CAS  Google Scholar 

  • Gerten D, Adrian R (2000) Climate-driven changes in spring plankton dynamics and the sensitivity of shallow polymictic lakes to the North Atlantic Oscillation. Limnol Oceanogr 45(5):1058–1066

    Article  Google Scholar 

  • Gerten D, Adrian R (2001) Differences in the persistency of the North Atlantic Oscillation signal among lakes. Limnol Oceanogr 46(2):448–455

    Article  Google Scholar 

  • Hamed KH, Rao AR (1998) A modified Mann–Kendall trend test for autocorrelated data. J Hydrol 204(1–4):182–196

    Article  Google Scholar 

  • Horn H (2003a) The relative importance of climate and nutrients in controlling phytoplankton growth in Saidenbach reservoir. Hydrobiologia 504:159–166

    Article  Google Scholar 

  • Horn W (2003b) Long-term development of the crustacean plankton in the Saidenbach reservoir (Germany)—changes, causes, consequences. Hydrobiologia 504:185–192

    Article  Google Scholar 

  • Horn H, Horn W (1993) Sedimentary losses in the reservoir Saidenbach: flux and sinking velocities of dominant phytoplankton species. Int Revue ges Hydrobiol 78(1):39–57

    Google Scholar 

  • Horn W, Horn H (1995) Interrelationships between crustacean zooplankton and phytoplankton. Hydrobiologia 307:231–238

    Article  Google Scholar 

  • Horn H, Horn W (2000) Sedimentation—the main loss factor in waters dominated by diatoms. Results of long-term investigations. Int Rev Hydrobiol 85(2–3):191–208

    Article  Google Scholar 

  • Horn H, Paul L (1984) Interactions between light situation, depth of mixing and phytoplankton growth during spring period of full circulation. Int Revue ges Hydrobiol 69(4):507–519

    Article  Google Scholar 

  • Horn H, Uhlmann D (1995) Competitive growth of blue–greens and diatoms (Fragilaria) in the Saidenbach Reservoir, Saxony. Wat Sci Tech 32(4):77–88

    Article  CAS  Google Scholar 

  • Horn W, Horn H, Paul L (1994) Long-term trends in the nutrient input and in-lake concentrations of a drinking water reservoir in a dense populated catchment area (Erzgebirge, Germany). Int Revue ges Hydrobiol 79(2):213–227

    Article  CAS  Google Scholar 

  • Huisman J, Van Oostveen P, Weissing FJ (1999) Critical depth and critical turbulence: two different mechanisms for the development of phytoplankton blooms. Limnol Oceanogr 44(7):1781–1787

    Article  Google Scholar 

  • Köhler J, Hilt S, Adrian R, Nicklisch A, Kozerski HP, Walz N (2005) Long-term response of a shallow, moderately flushed lake to reduced external phosphorus and nitrogen loading. Freshw Biol 50:1639–1650

    Article  CAS  Google Scholar 

  • Mooij WM, Hülsmann S, Domis LND, Nolet BA, Bodelier PLE, Boers PCM, Pires LMD, Gons HJ, Ibelings BW, Noordhuis R, Portielje R, Wolfstein K, Lammens EHRR (2005) The impact of climate change on lakes in The Netherlands: a review. Aquat Ecol 39(4):381–400

    Article  CAS  Google Scholar 

  • Paul L (2003) Nutrient elimination in pre-dams: results of long-term studies. Hydrobiologia 504:298–295

    Article  Google Scholar 

  • R Development Core Team (2005) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria, ISBN 3-900051-07-0, http://www.r-project.org. Cited 8th June 2007

  • Scheffer M, Straile D, van Nes EH, Hosper H (2001) Climatic warming causes regime shifts in lake foodwebs. Limnol Oceanogr 46:1780–1783

    Article  Google Scholar 

  • Sommer U, Gliwicz ZM, Lampert W, Duncan A (1986) The PEG-model of seasonal succession of planktonic events in fresh waters. Arch Hydrobiol 106(4):433–471

    Google Scholar 

  • Straile D (2000) Meteorological forcing of plankton dynamics in a large and deep continental European lake. Oecologia 122(1):44–50

    Article  Google Scholar 

  • Straile D, Adrian R (2000) The North Atlantic Oscillation and plankton dynamics in two European lakes—two variations on a general theme. Glob Change Biol 6(6):663–670

    Article  Google Scholar 

  • Straile D, Jöhnk K, Rossknecht H (2003a) Complex effects of winter warming on the physicochemical characteristics of a deep lake. Limnol Oceanogr 48(4):1432–1438

    Article  CAS  Google Scholar 

  • Straile D, Livingstone D, Weyhenmeyer GA, George DG (2003b) The response of freshwater ecosystems to climate variability associated with the North Atlantic Oscillation. In: Hurrell JW, Kushnir Y, Ottersen G, Visbeck M (eds) The North Atlantic Oscillation—climatic significance and environmental impact (AGU Geophysical Monograph Series). American Geophysical Union, Washington, DC, 134:263–279

  • Venables QN, Ripley BD (1999) Modern applied statistics with S-plus, 3rd edn. Springer, New York

    Google Scholar 

  • Vollenweider RA (1976) Advances in defining critical loading levels for phosphorus in lake eutrophication. Mem Ist Ital ldrobiol 33:53–83

    CAS  Google Scholar 

  • Walther GR, Post E, Convey P, Menzel A, Parmesank C, Beebee TJC, Fromentin JM, Hoegh-Guldberg O, Bairlein F (2002) Ecological responses to recent climate change. Nature 416:398–395

    Article  CAS  Google Scholar 

  • Weyhenmeyer GA (2001) Warmer winters: are planktonic algal populations in Sweden’s largest lakes affected? Ambio 30(8):565–571

    Article  PubMed  CAS  Google Scholar 

  • Weyhenmeyer GA, Blenckner T, Pettersson K (1999) Changes of the plankton spring outburst related to the North Atlantic Oscillation. Limnol Oceanogr 44(7):1788–1792 12

    Article  Google Scholar 

  • Wiltshire KH, Manly BFJ (2004) The warming trend at Helgoland Roads, North Sea: phytoplankton response. Helgoland Mar Res 58(4):269–273

    Article  Google Scholar 

  • Winder M, Schindler DE (2004) Climate change uncouples trophic interactions in an aquatic ecosystem. Ecology 85(8):2100–2106

    Article  Google Scholar 

  • Yue S, Wang C (2004) The Mann–Kendall test modified by effective sample size to detect trend in serially correlated hydrological series. Water Resour Manage 18(3):201–218

    Article  Google Scholar 

  • Zeileis A, Leisch F, Hornik K, Kleiber C (2002) strucchange: An R package for testing for structural change in linear regression models. J Stat Softw 7(2):1–38 13

    Google Scholar 

  • Zeileis A, Kleber C, Krämer W, Hornik K (2003) Testing and dating of structural changes in practise. Comput Stat Data Anal 44(1–2):109–123

    Article  Google Scholar 

Download references

Acknowledgments

This study is supported by the German Research Foundation (DFG) under grant (PA 1202/1) of priority programme 1162 AQUASHIFT. The authors are grateful to Karsten Rinke and Stephan Hülsmann for fruitful discussions, Otto Richter for bringing up the Weibull function, and two anonymous referees for their detailed, persevering and constructive suggestions and their encouragement of the sensitivity analysis.

Author information

Authors and Affiliations

  1. Institute of Hydrobiology, Technische Universität Dresden, 01062, Dresden, Germany

    Susanne Rolinski

  2. Limnology of Reservoirs, Neunzehnhain Ecological Station, Saxon Academy of Sciences, Neunzehnhainer Str. 14, 09514, Lengefeld, Germany

    Heidemarie Horn

  3. Institute of Hydrobiology, Technische Universität Dresden, 01062, Dresden, Germany

    Thomas Petzoldt

  4. Neunzehnhain Ecological Station, Technische Universität Dresden, Neunzehnhainer Str. 14, 09514, Lengefeld, Germany

    Lothar Paul

Authors
  1. Susanne Rolinski
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Heidemarie Horn
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Thomas Petzoldt
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Lothar Paul
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Susanne Rolinski.

Additional information

Communicated by Ulrich Sommer.

Priority program of the German Research Foundation–contribution 16.

Electronic supplementary material

Below is the link to the electronic supplementary material.

ESM (DOC 39.5 kb)

Rights and permissions

Reprints and permissions

About this article

Cite this article

Rolinski, S., Horn, H., Petzoldt, T. et al. Identifying cardinal dates in phytoplankton time series to enable the analysis of long-term trends. Oecologia 153, 997–1008 (2007). https://doi.org/10.1007/s00442-007-0783-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00442-007-0783-2

Keywords

Search

Navigation