Register      Login
Marine and Freshwater Research Marine and Freshwater Research Society
Advances in the aquatic sciences
RESEARCH ARTICLE

A phytoplankton community in a temperate reservoir in New South Wales, Australia: relationships between similarity and diversity indices and measures of hydrological disturbance

Tsuyoshi Kobayashi A B , Brian G. Sanderson A and Geoff N. G. Gordon A
+ Author Affiliations
- Author Affiliations

A Department of Environment and Conservation (NSW), PO Box A290, Sydney South, NSW 1232, Australia.

B Corresponding author. Email: yoshi.kobayashi@environment.nsw.gov.au

Marine and Freshwater Research 56(2) 203-214 https://doi.org/10.1071/MF04249
Submitted: 24 September 2004  Accepted: 31 January 2005   Published: 12 April 2005

Abstract

Temporal changes in diversity and similarity of a phytoplankton community were investigated in relation to external hydrological disturbance in the Ben Chifley reservoir from September 1998 to January 2002. Species richness varied by a factor of 4–5 at each of three sites studied during the period (n = 53 at each site). Species diversity (measured using Simpson’s D and Shannon–Wiener’s H, based on primarily genus or species number and cell densities) varied by a factor of 8–10, whereas similarity between two consecutive sampling dates (measured using Hurlbert’s index and Pinkham and Pearson’s B) varied by a factor of 10–46. When diversity was measured with H, it had an approximate quadratic (convex) relationship with similarity, as measured with Hurlbert’s index. However, diversity was seldom related to external hydrological disturbance (measured as intensity and variability of daily inflow rates between two consecutive sampling dates). Similarity was significantly and negatively related to disturbance variability. These results suggest that the mechanisms that regulate diversity and similarity may differ from each other, and question the usefulness of observed approximate quadratic relationships between similarity and diversity indices when assessing the effect of disturbance on diversity. Such relationships may therefore not provide support for Connell’s (1978) intermediate disturbance hypothesis.


Acknowledgments

We thank Peter Scanes, John Chapman, and Klaus Koop, DEC (NSW), and three anonymous reviewers for comments. Identification and cell counts of phytoplankton were conducted by Derek Cannon. The view and conclusions of the paper are those of the authors and do not necessarily represent the official policies, either expressed or implied, of the DEC (NSW).


References

Anonymous  (1997). An Environmental Impact Assessment for the Proposed Upgrading and Augmentation of Ben Chifley Dam, Bathurst City Council, July 1997. CMPS & F Environmental, Bathurst.

Connell, J. H. (1978). Diversity of tropical rainforests and coral reefs. Science 199, 1304–1310.
Ford D. E. (1990). Reservoir transport processes. In ‘Reservoir Limnology: Ecological Perspectives’. (Eds K. W. Thornton, B. L. Kimmel and F. E. Payne.) pp. 15–41. (John Wiley & Sons: New York.)

Goodman, D. (1975). The theory of diversity-stability relationships in ecology. The Quarterly Review of Biology 50, 237–266.
Crossref | GoogleScholarGoogle Scholar | Huston M. A. (1994). ‘Biological Diversity: The Coexistence of Species on Changing Landscapes.’ (Cambridge University Pres: New York.)

Kendall M., and Ord J. K. (1990). ‘Time Series.’ 3rd edn. (Edward Arnold: London.)

Kobayashi, T. , and Church, A. G. (2003). Role of nutrients and zooplankton grazing on phytoplankton growth in a temperate reservoir in New South Wales, Australia. Marine and Freshwater Research 54, 609–618.
Crossref | GoogleScholarGoogle Scholar | Krebs C. J. (1985). ‘Ecology: the Experimental Analysis of Distribution and Abundance.’ 3rd edn. (Harper & Row Publishers: New York.)

Lindenschmidt, K. E. , and Chorus, I. (1998). The effect of water column mixing on phytoplankton succession, diversity and similarity. Journal of Plankton Research 20, 1927–1951.
Magurran A. E. (1988). ‘Ecological Diversity and Its Measurement.’ (Croom Helm Limited: London.)

Padisák, J. (1994). Identification of relevant time-scales in non-equilibrium community dynamics: conclusions from phytoplankton surveys. New Zealand Journal of Ecology 18, 169–176.
Padisák J., Reynolds C. S., and Sommer U. (Eds) (1993). ‘Intermediate Disturbance Hypothesis in Phytoplankton Ecology.’ Developments in Hydrobiology 81. (Kluwer Academic Publishers: Dordrecht.)

Pickett, S. T. A. , Kolasa, J. , Armesto, J. J. , and Collins, S. L. (1989). The ecological concept of disturbance and its expression at various hierarchical levels. Oikos 54, 129–136.
Pickett S. T. A., Kolasa J., and Jones C. G. (1994). ‘Ecological Understanding.’ (Academic Press: San Diego, CA.)

Pinkham, C. F. A. , and Pearson, J. G. (1976). Applications of a new coefficient of similarity to pollution surveys. Journal – Water Pollution Control Federation 48, 717–723.
R Development Core Team (2004). R: A language and environment for statistical computing. (R Foundation for Statistical Computing: Vienna.) Available at http://www.R-project.org (verified February 2005)

Reynolds, C. S. (1993). Scales of disturbance and their role in plankton ecology. Hydrobiologia 249, 157–171.
Reynolds C. S. (1997). ‘Vegetation Processes in the Pelagic: A Model for Ecosystem Theory.’ (Ecology Institute: Oldendorf/Luhe.)

SAS Institute Inc. (1999). ‘The SAS System for Windows. Version 8.02.’ (SAS Institute Inc.: Cary, NC.)

Shannon, C. E. (1948). A mathematical theory of communications. Bell System Technical Journal 27, 379–423.
Sokal R. R., and Rohlf F. J. (1995). ‘Biometry. The Principles and Practice of Statistics in Biological Research.’ 3rd edn. (W.H. Freeman and Company: New York.)

Sommer, U. (1995). An experimental test of the intermediate disturbance hypothesis using cultures of marine phytoplankton. Limnology and Oceanography 40, 1271–1277.
Spellerberg I. F. (1991). ‘Monitoring Ecological Change.’ (Cambridge University Press: Cambridge.)

Townsend, S. A. (2001). Perennial domination of phytoplankton by Botryococcus and Peridinium in a discontinuously polymictic reservoir (tropical Australia). Archiv für Hydrobiologie 151, 529–548.
Wetzel R. G. (2001). ‘Limnology: Lake and River Ecosystems.’ 3rd edn. (Academic Press: San Diego, CA.)




Appendix 1. Phytoplankton species in Ben Chifley reservoir between September 1998 and January 2002

  • Cyanophyta

  • Anabaena spp.

  • Aphanothece clathrata

  • Aphanizomenon issatschenkoi

  • Aphanocapsa incerta

  • Dactylococcopsis spp.

  • Lyngbya sp.

  • Merismopedia sp.

  • Microcystis spp.

  • Oscillatoria sp.

  • Planktothrix cf. perornata

  • Pseudanabaena limnetica

  • Snowella litoralis

  • Synechococcus sp.

  • Unidentified coccoid cells

  • Unidentified filamentous cells

  • Chlorophyta

  • Actinastrum aciculare

  • Ankistrodesmus spp.

  • Ankyra cf. judayi

  • Botryococcus braunii

  • Carteria sp.

  • Chlamydomonas sp.

  • Closterium sp.

  • Closteriopsis sp.

  • Coelastrum sp.

  • Cosmarium sp.

  • Crucigenia sp.

  • Dictyosphaerum cf. pulchellum

  • Elakatothrix lacustris

  • Eudorina elegans

  • Golenkinopsis sp.

  • Lagerheimia cf. genevensis

  • Kirchneriella cf. obesa

  • Micractinium sp.

  • Monoraphidium spp.

  • Mougeotia sp.

  • Nephrocytium sp.

  • Oocystis sp.

  • Pediastrum spp.

  • Planctonema cf. aenigmaticum

  • Pseudcoccomyxa sp.

  • Pteromonas sp.

  • Scenedesmus spp.

  • Schroederia sp.

  • Selenastrum sp.

  • Sphaerocystis schroeteri

  • Rhizoclonium sp.

  • Spirogyra sp.

  • Staurastrum spp.

  • Staurodesmus sp.

  • Tetraedron sp.

  • Tetrastrum sp.

  • Treubaria sp.

  • Volvox spp.

  • Unidentified mono- and bi-flagellate cells

  • Unidentified filamentous cells

  • Chloromonadophyta

  • Merotrichia sp.

  • Euglenophyta

  • Euglena sp.

  • Phacus sp.

  • Strombomonas sp.

  • Trachelomonas volvocina

  • Cryptophyta

  • Chroomonas cf. acuta

  • Cryptomonas spp.

  • Chrysophyta

  • Dinobryon spp.

  • Mallomonas spp.

  • Synura uvella

  • Bacillariophyta

  • Acanthoceras zachariasi

  • Achnanthidium sp.

  • Amphora sp.

  • Asterionella formosa

  • Aulacoseira spp.

  • Bacillaria sp.

  • Cocconeis sp.

  • Cyclotella spp.

  • Cymbella sp.

  • Encyonema sp.

  • Fragilaria capucina

  • Gomphonema cf. constrictum

  • Gyrosigma sp.

  • Melosira varians

  • Navicula sp.

  • Nitzschia spp.

  • Rhoicosphenia curvata

  • Rhopalodia sp.

  • Skeletonema potamos

  • Surirella sp.

  • Synedra spp.

  • Tabellaria flocculosa

  • Urosolenia eriensis

  • Pyrrhophyta

  • Ceratium hirundinella

  • Peridinium sp.


Appendix 2. Simpson’s D and Hurlbert’s similarity index, SH

Here we demonstrate that diversity (as quantified by Simpson’s D) is correlated with the square of similarity, as quantified by Hurlbert’s index, SH. Hurlbert’s index can be written

E6

where

E7

is the Bray–Curtis dissimilarity index. It follows that the square of the Bray–Curtis dissimilarity index can be written

E8

The first term on the right hand side of this last equation involves correlations between population changes of different organisms and can only be related to D if fluctuations in the populations of one species are correlated with those of another species.

Assuming statistical stationarity, the second term on the right hand side of the equation can be written

E9

where

E10

is Simpson’s D measure of species diversity and

E11

is the autocorrelation function for species fluctuations, where τ is the actual time lag between sampling occasions indexed by t − 1 and t. The autocorrelation function will tend to 1 when the temporal lag τ between sampling occasions becomes very small. In general, one expects R(τ) < 1 for realistic time lags, as between sampling occasions at times t − 1 and t, owing to ‘random’ fluctuations in the community structure. Thus, providing dissimilarity is non-zero, we expect that the square of the Bray–Curtis dissimilarity index and therefore Hurlbert’s similarity index SH will be functionally related to Simpson’s D diversity index.