Literature DB >> 28313551

Competitive exclusion, or species aggregation? : An aid in deciding.

Lewi Stone1, Alan Roberts2.   

Abstract

There is a long-standing dispute over whether the analysis of species co-occurrence data, typically on islands in an archipelago, can disclose the forces at work in structuring a community. Here we present and utilise three "scores" S, C and T. S gives the mean number of islands shared by a species pair in the presence/absence data under study. The scores C and T are based on the way that a pair of species occurs on a pair of islands. When each species occurs on a different island, this adds to the "checkerboard score" C; if they occupy the same island, this increases the "togetherness score" T.In judging whether observed values of S, C and T are compatible with a null hypothesis assuming no species interaction, we follow Connor and Simberloff (1979) in generating a "control group" of (constrained) simulated incidence patterns.Presence/absence matrices can have paradoxical features, in combining a high mutual exclusion by species (checkerboardedness) with a degree of species aggregation that is also high. We show that this is in fact inevitable - that, given the usual contraints, C and T can differ only by a constant. This means that extreme checkerboardedness can be produced by forces making for species aggregation, just as well as by those making for avoidance.If we restrict our attention to a subset of species, the constraints are less rigid and the S, C and T scores are somewhat freer to vary. We consider the confamilial subsets in the Vanuatu archipelago as likely candidates for revealing any competition forces at work. Calculating the actual S, C and T scores for these subsets, we compare them with the corresponding scores in a sample of simulated colonization patterns.The actual species-distributions differ significantly from what we would expect if the colonization choices of different species were uncorrelated (save for some biological constraints). The confamilial species of the real world share more islands, and occur in a pattern less checkerboarded, and more aggregated, than their simulation counterparts. This suggests that competition pressures, if they exist, are overcome by countervailing factors.The method used is applicable in other ways, and to a wider class of problems, in analysing the forces behind community structure.

Keywords:  Bird distributions; Coexistence principle; Community structure; Species co-occurrence

Year:  1992        PMID: 28313551     DOI: 10.1007/BF00317632

Source DB:  PubMed          Journal:  Oecologia        ISSN: 0029-8549            Impact factor:   3.225


  5 in total

1.  Methods for detecting non-randomness in species co-occurrences: a contribution.

Authors:  J B Wilson
Journal:  Oecologia       Date:  1987-10       Impact factor: 3.225

2.  Factors contributing to non-randomness in species Co-occurrences on Islands.

Authors:  Michael E Gilpin; Jared M Diamond
Journal:  Oecologia       Date:  1982-01       Impact factor: 3.225

3.  The checkerboard score and species distributions.

Authors:  Lewi Stone; Alan Roberts
Journal:  Oecologia       Date:  1990-11       Impact factor: 3.225

4.  Examination of the "null" model of connor and simberloff for species co-occurrences on Islands.

Authors:  Jared M Diamond; Michael E Gilpin
Journal:  Oecologia       Date:  1982-01       Impact factor: 3.225

5.  Island-sharing by archipelago species.

Authors:  Alan Roberts; Lewis Stone
Journal:  Oecologia       Date:  1990-07       Impact factor: 3.225

  5 in total
  17 in total

1.  Patterns in the co-occurrence of fish species in streams: the role of site suitability, morphology and phylogeny versus species interactions.

Authors:  Pedro R Peres-Neto
Journal:  Oecologia       Date:  2004-05-08       Impact factor: 3.225

2.  Effects of habitat characteristics and interspecific interactions on co-occurrence patterns of saproxylic beetles breeding in tree boles after forest fire: null model analyses.

Authors:  Ermias T Azeria; Jacques Ibarzabal; Christian Hébert
Journal:  Oecologia       Date:  2011-11-05       Impact factor: 3.225

3.  Environmental filtering determines metacommunity structure in wetland microcrustaceans.

Authors:  Stéphanie Gascón; Ignasi Arranz; Miguel Cañedo-Argüelles; Alfonso Nebra; Albert Ruhí; Maria Rieradevall; Nuno Caiola; Jordi Sala; Carles Ibàñez; Xavier D Quintana; Dani Boix
Journal:  Oecologia       Date:  2016-01-19       Impact factor: 3.225

4.  Community assembly at the patch scale in a species rich tropical river.

Authors:  D Albrey Arrington; Kirk O Winemiller; Craig A Layman
Journal:  Oecologia       Date:  2005-05-11       Impact factor: 3.225

5.  Is the abundance of species determined by their functional traits? A new method with a test using plant communities.

Authors:  David Mouillot; Norman W H Mason; J Bastow Wilson
Journal:  Oecologia       Date:  2007-03-21       Impact factor: 3.225

6.  Stochastic and deterministic processes together determine alpine meadow plant community composition on the Tibetan Plateau.

Authors:  Zhongling Yang; Hui Guo; Jiayang Zhang; Guozhen Du
Journal:  Oecologia       Date:  2012-08-28       Impact factor: 3.225

7.  Biotic interactions as a structuring force in soil communities: evidence from the micro-arthropods of an Antarctic moss model system.

Authors:  Tancredi Caruso; Vladlen Trokhymets; Roberto Bargagli; Peter Convey
Journal:  Oecologia       Date:  2012-10-20       Impact factor: 3.225

8.  Predicting cryptic links in host-parasite networks.

Authors:  Tad Dallas; Andrew W Park; John M Drake
Journal:  PLoS Comput Biol       Date:  2017-05-25       Impact factor: 4.475

9.  Using ecological null models to assess the potential for marine protected area networks to protect biodiversity.

Authors:  Brice X Semmens; Peter J Auster; Michelle J Paddack
Journal:  PLoS One       Date:  2010-01-27       Impact factor: 3.240

10.  Environmental conditions and biotic interactions acting together promote phylogenetic randomness in semi-arid plant communities: new methods help to avoid misleading conclusions.

Authors:  Santiago Soliveres; Rubén Torices; Fernando T Maestre
Journal:  J Veg Sci       Date:  2012-10-01       Impact factor: 2.685

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.