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

Quantifying percentage cover of subtidal organisms on rocky coasts: a comparison of the costs and benefits of standard methods

S. P. Drummond A and S. D. Connell A B
+ Author Affiliations
- Author Affiliations

A Southern Seas Ecology Laboratories, DP418, University of Adelaide, Adelaide, SA 5005, Australia.

B Corresponding author. Email: sean.connell@adelaide.edu.au

Marine and Freshwater Research 56(6) 865-876 https://doi.org/10.1071/MF04270
Submitted: 19 November 2004  Accepted: 26 April 2005   Published: 27 September 2005

Abstract

This study compares the cost (time and funds) and benefits (precision and accuracy) of methods commonly used to estimate percentage cover of sessile marine organisms. We applied nine methods to morphological groups of benthic algae and broad taxonomic groups of sessile invertebrates; including varying the intensity of sampling (25 v. 50 v. 100 point-intercepts), random v. regular arrays, in situ v. laboratory v. photographic sampling v. computer digitising. We detected little to no difference in estimates of percentage cover among methods, indicating that accuracy is unlikely to be an important issue that distinguishes methods. Precision was generally unaffected by the intensity of sampling within quadrats (25 v. 50 v. 100 point-intercepts) or between environments (in situ v. on photographs v. within the laboratory) and appeared to be of secondary concern to decisions about replication. Computer digitising (estimates of surface area of each taxon) provided the least precise estimates and did not justify the additional laboratory time required to process them. Depending on whether field expenses or laboratory expenses are of the greatest concern, the techniques that permit the greatest coverage of area (greatest replication) are likely to produce the most representative (accurate) and reliable (precise) estimates.

Extra keywords: abundance, accuracy, precision, quantification.


Acknowledgments

We are grateful for the discussions with M. J. Anderson, T. E. Minchinton, B. M. Gillanders and assistance by A. D. Irving and M. J. Fowler-Walker. We genuinely enjoyed engaging with the astute and meticulous assistance provided by all three anonymous reviewers. This work was supported by an Australian Research Council grant to SDC.


References

Anderson, M. J. , Connell, S. D. , Gillanders, B. M. , Diebel, C. E. , Blom, W. M. , Saunders, J. E. , and Landers, T. J. (2005). Relationships between taxonomic resolution and spatial scales of multivariate variation. Journal of Animal Ecology 74, 636–646.
Crossref | GoogleScholarGoogle Scholar | Cochran W. G. (1977). ‘Sampling Techniques.’ (John Wiley & Sons: New York.)

Cohen J. (1988). ‘Statistical Power Analysis for the Behavioural Sciences.’ 2nd edn. (L. Erlbaum Associates: Hillsdale, NJ.)

Connell, S. D. (2003). Negative effects overpower the positive of kelp to exclude invertebrates from the understorey community. Oecologia 137, 97–103.
Crossref | GoogleScholarGoogle Scholar | PubMed | Efron B., and Tibshirani R. J. (1993). ‘An Introduction to the Bootstrap.’ 1st edn. (Chapman & Hall: Boca Raton, FL.)

Fairweather, P. G. (1991). Statistical power and design requirements for environmental monitoring. Australian Journal of Marine and Freshwater Research 42, 555–567.
Greig-Smith P. (1983). ‘Quantitative Plant Ecology.’ (Blackwell Scientific Publications: Melbourne.)

Irving, A. D. , and Connell, S. D. (2002). Sedimentation and light penetration interact to maintain heterogeneity of subtidal habitats: algal vs invertebrate dominated assemblages. Marine Ecology Progress Series 245, 83–91.
Southwood T. R. E. (1978). ‘Ecological Methods: With Particular Reference to the Study of Insect Populations.’ (Chapman and Hall: London.)

Strong, C. W. (1966). An improved method for obtaining density from line-transect data. Ecology 47, 311–313.
Quinn G. P., and Keough M. J. (2003). ‘Experimental Design and Data Analysis for Biologists.’ (Cambridge University Press: Cambridge.)

Underwood A. J. (1997). ‘Experiments in Ecology. Their Logical Design and Interpretation using Analysis of Variance.’ (Cambridge University Press: Melbourne.)

Underwood, A. J. , Chapman, M. C. , and Connell, S. D. (2000). Observations in ecology: you can’t make progress on processes without understanding the patterns. Journal of Experimental Marine Biology and Ecology 250, 97–115.
Crossref | GoogleScholarGoogle Scholar | PubMed | Zar J. H. (1999). ‘Biostatistical Analysis.’ 4th edn. (Prentice Hall: Upper Saddle River, NJ.)