Comparison of discrete and continuum community models: Insights from numerical ecology and Bayesian methods applied to Azorean plant communities

Pavão, D.C., Elias, R.E. & Silva, L. (2019) Comparison of discrete and continuum community models: Insights from numerical ecology and Bayesian methods applied to Azorean plant communities.

Ecological Modelling, 402, 93-106. DOI:10.1016/j.ecolmodel.2019.03.021 (IF2019 2,497; Q2 Ecology)
  • Team:
  • Category:
  • May, 2019


Our view of community ecology has evolved over time, beginning with two extreme visions of plant communities which were considered either as species associations driven by random coincidences or as complex organisms with clear interdependencies. More recently, biological communities tend to be viewed as a set of local community assemblages that are linked by dispersal of multiple potentially interacting species (i.e., a metacommunity), a concept that has been used to explain spatiotemporal dynamics. Several models have been proposed to explain the distribution patterns of species and communities along environmental gradients, ranging from discrete, individual community types, to a continuum of plant communities. The Azorean natural vegetation is a good study model to test those hypotheses, since it has been described in detail by several authors, therefore creating the opportunity to address theoretical questions within a conceptual metacommunity framework. Through a combination of numerical ecology and Bayesian analysis applied to natural forest community data from the Azores archipelago, the present study evaluated if the present data supports the existence of "discrete community types" or of a "continuum of communities". We used hierarchical clustering (Hellinger distance and UPGMA) and non-hierarchical clustering (k-means clustering), as well as a multinomial model in a Bayesian context to determine the number of plant community groups. A total of 139 plant communities and 85 species were sampled in four islands. The optimum number of plant community groups ranged from 4 to 6 for hierarchical clustering, and neared 43 for non-hierarchical clustering and about 70 for the multinomial analysis. The elevation distribution curves estimated suggest that species distributions are determined by physiological limits at the extremes, and by competition under intermediate conditions, with some niche partitioning between dominant species. Our results would be in agreement with an ecological view of the communities as a continuum, more than with a view considering the existence of discrete community types.