, Volume 142, Issue 3, pp 450–457 | Cite as

Assessing determinants of community biomass composition in two-species plant competition studies

  • John ConnollyEmail author
  • Peter Wayne
Community Ecology


A method is proposed for assessing the relative importance of species identity, neighbour species influence and environment as determinants of change in community biomass composition in two-species short-term competition experiments. The method is based on modelling the differences in relative growth rates (RGR) of species (hence called the RGRD method). Using a multiple regression approach it quantifies the effects of initial species’ abundance, species identity and environment on RGRD and hence on change in community biomass composition. The RGRD approach is relatively simple to use and deals readily with statistical difficulties associated with correlated responses between species from the same stand. It can be easily adapted to analyse sequential harvest data. An example based on data from two-species mixtures of the annual species Stellaria media and Poa annua is used to illustrate the method. The main determinant of change in community biomass composition was species identity, reflected in the difference in growth rates between the species. Change in community composition was not, in general, significantly affected by the influence of neighbours or fertiliser level. The unimportance of the influence of neighbours in affecting the composition of these communities contrasts with the strong role of intra- and interspecific competition in determining the size of individuals of both species (Connolly et al. in Oecologia 82:513–526, 1990).


Outcome of competition Community composition Stellaria media Poa annua RGRD 



Thanks are due to Fakhri Bazzaz for hosting J.C. during repeated visits to his laboratory and for his encouragement and constructive comments. We also thank David Gibson and Teresa Sebastia for helpful comments. We wish to thank two anonymous referees for very useful comments on earlier drafts. This work was partly supported by EPA (Ireland) programme AG-BIOTA, grant 2001-CD/B1-M1, by an Enterprise Ireland International Collaboration Programme grant in 2001 and by the EU Concerted Action COST 852.


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Copyright information

© Springer-Verlag 2004

Authors and Affiliations

  1. 1.Department of Organismic and Evolutionary Biology, Biological LaboratoriesHarvard UniversityCambridgeUSA
  2. 2.Department of Statistics and Actuarial ScienceUniversity College DublinDublinIreland
  3. 3.Department of ResearchNew England School of AcupunctureWatertownUSA

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