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  • 1 Griffith University School of Environment Nathan Queensland Australia 4111
  • | 2 Monash University Dept. Computer Science and Software Engineering Clayton Victoria Australia
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Many methods of cluster analysis do not explicitly account for correlation between attributes. In this paper we explicitly model any correlation using a single factor within each cluster: i.e., the correlation of atributes within each cluster is adequately described by a single component axis. However, the use of a factor is not required in every cluster. Using a Minimum Message Length criterion, we can determine the number of clusters and also whether the model of any cluster is improved by introducing a factor. The technique allows us to seek clusters which reflect directional changes rather than imposing a zonation constrained by spatial (and implicitly temporal) position. Minimal message length is a means of utilising Okham’s Razor in inductive analysis. The ‘best’ model is that which allows most compression of the data, which results in a minimal message length for the description. Fit to the data is not a sufficient criterion for choosing models because more complicated models will almost always fit better. Minimum message length combines fit to the data with an encoding of the model and provides a Bayesian probability criterion as a means of choosing between models (and classes of model). Applying the analysis to a pollen diagram from Southern Chile, we find that the introduction of factors does not improve the overall quality of the mixture model. The solution without axes in any cluster provides the most parsimonious solution. Examining the cluster with the best case for a factor to be incorporated in its description shows that the attributes highly loaded on the axis represent a contrast of herbaceous vegetation and dominant forests types. This contrast is also found when fitting the entire population, and in this case the factor solution is the preferred model. Overall, the cluster solution without factors is much preferred. Thus, in this case classification is preferred to ordination although more data are desirable to confirm such a conclusion.

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Senior editors

Editor(s)-in-Chief: Podani, János

Editor(s)-in-Chief: Jordán, Ferenc

Honorary Editor(s): Orlóci, László

Editorial Board

  • Madhur Anand, CAN (forest ecology, computational ecology, and ecological complexity)
  • S. Bagella, ITA (temporal dynamics, including succession, community level patterns of species richness and diversity, experimental studies of plant, animal and microbial communities, plant communities of the Mediterranean)
  • P. Batáry, HUN (landscape ecology, agroecology, ecosystem services)
  • P. A. V. Borges, PRT (community level patterns of species richness and diversity, sampling in theory and practice)
  • A. Davis, GER (supervised learning, multitrophic interactions, food webs, multivariate analysis, ecological statistics, experimental design, fractals, parasitoids, species diversity, community assembly, ticks, biodiversity, climate change, biological networks, cranes, olfactometry, evolution)
  • Z. Elek, HUN (insect ecology, invertebrate conservation, population dynamics, especially of long-term field studies, insect sampling)
  • T. Kalapos, HUN (community level plant ecophysiology, grassland ecology, vegetation-soil relationship)
  • G. M. Kovács, HUN (microbial ecology, plant-fungus interactions, mycorrhizas)
  • W. C. Liu,TWN (community-based ecological theory and modelling issues, temporal dynamics, including succession, trophic interactions, competition, species response to the environment)
  • L. Mucina, AUS (vegetation survey, syntaxonomy, evolutionary community ecology, assembly rules, global vegetation patterns, mediterranean ecology)
  • P. Ódor, HUN (plant communities, bryophyte ecology, numerical methods)
  • F. Rigal, FRA (island biogeography, macroecology, functional diversity, arthropod ecology)
  • D. Rocchini, ITA (biodiversity, multiple scales, spatial scales, species distribution, spatial ecology, remote sensing, ecological informatics, computational ecology)
  • F. Samu, HUN (landscape ecology, biological control, generalist predators, spiders, arthropods, conservation biology, sampling methods)
  • U. Scharler, ZAF (ecological networks, food webs, estuaries, marine, mangroves, stoichiometry, temperate, subtropical)
  • D. Schmera, HUN (aquatic communities, functional diversity, ecological theory)
  • M. Scotti, GER (community-based ecological theory and modelling issues, trophic interactions, competition, species response to the environment, ecological networks)
  • B. Tóthmérész, HUN (biodiversity, soil zoology, spatial models, macroecology, ecological modeling)
  • S. Wollrab, GER (aquatic ecology, food web dynamics, plankton ecology, predator-prey interactions)

 

Advisory Board

  • S. Bartha, HUN
  • S.L. Collins, USA
  • T. Czárán, HUN
  • E. Feoli, ITA
  • N. Kenkel, CAN
  • J. Lepš, CZE
  • S. Mazzoleni, ITA
  • Cs. Moskát, HUN
  • B. Oborny, HUN
  • M.W. Palmer, USA
  • G.P. Patil, USA
  • V. de Patta Pillar, BRA
  • C. Ricotta, ITA
  • Á. Szentesi, HUN

PODANI, JÁNOS
E-mail: podani@ludens.elte.hu


JORDÁN, FERENC
E-mail: jordan.ferenc@gmail.com

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Community Ecology
Language English
Size A4
Year of
Foundation
2000
Volumes
per Year
1
Issues
per Year
2
Founder Akadémiai Kiadó
Founder's
Address
H-1117 Budapest, Hungary 1516 Budapest, PO Box 245
Publisher Akadémiai Kiadó
Springer Nature Switzerland AG
Publisher's
Address
H-1117 Budapest, Hungary 1516 Budapest, PO Box 245.
CH-6330 Cham, Switzerland Gewerbestrasse 11.
Responsible
Publisher
Chief Executive Officer, Akadémiai Kiadó
ISSN 1585-8553 (Print)
ISSN 1588-2756 (Online)