Ecological & Community Analysis

Quantitative methods for analyzing species assemblages, diversity patterns, and community-environment relationships

H'
Shannon Diversity
Index
nMDS
Non-metric MDS
Ordination
SIMPER
Similarity
Percentages
CCA
Canonical
Correspondence

Overview

Ecological community analysis provides the statistical toolkit for understanding how species assemblages are structured, how they differ between habitats or treatments, and what environmental factors drive these patterns. This field bridges ecology and multivariate statistics, with methods ranging from diversity indices (Shannon H', Simpson's D, species richness) to ordination techniques (nMDS, CCA, RDA) that visualize community composition in reduced dimensions. Hypothesis testing via ANOSIM, PERMANOVA, and SIMPER identifies which groups differ and which species contribute most to those differences. In marine ecology these methods are applied to benthic invertebrate surveys, fish assemblages, plankton communities, and coral reef monitoring.

Key Concepts

Diversity Indices

Shannon index H' = -Σ pᵢ ln(pᵢ) measures uncertainty in species identity. Simpson's D = Σ pᵢ² measures dominance. Pielou's evenness J' = H'/ln(S). Species richness S is the simplest measure. Rarefaction standardizes comparison across samples with different abundances.

H' = -Σᵢ₌₁ˢ pᵢ ln(pᵢ)
D = 1 - Σᵢ₌₁ˢ pᵢ²
J' = H' / ln(S)

nMDS Ordination

Non-metric multidimensional scaling represents community dissimilarity in 2D/3D. Based on rank-order of Bray-Curtis distances. Stress < 0.1 = good fit; < 0.2 = useful. Points close together = similar communities. Environmental vectors can be overlaid.

ANOSIM & PERMANOVA

ANOSIM (Analysis of Similarity) tests whether between-group dissimilarity exceeds within-group. R statistic ranges 0–1. PERMANOVA partitions variation using distance matrices with permutation tests — more powerful and flexible. Both are non-parametric.

SIMPER Analysis

Similarity Percentages (SIMPER) identifies which species contribute most to observed dissimilarity between groups. Decomposes Bray-Curtis dissimilarity into species-level contributions. Useful for identifying indicator species but sensitive to high-abundance taxa.

CCA / RDA

Canonical Correspondence Analysis relates species composition to environmental gradients (temperature, salinity, depth, sediment type). Constrained ordination axes are linear combinations of environmental variables. RDA for linear species responses; CCA for unimodal.

Species-Area & Rarefaction

Species-area relationship S = cAᶻ describes how richness increases with area. Individual-based rarefaction curves estimate richness at equal sample size. Extrapolation methods (Chao1, ACE) estimate total richness including unseen species.

Interactive Visualizations

nMDS Ordination of Marine Benthic Communities

Species Rarefaction Curves by Habitat

SIMPER — Species Contribution to Group Dissimilarity

Key References

  1. Clarke, K.R. & Warwick, R.M. (2001). Change in Marine Communities: An Approach to Statistical Analysis and Interpretation, 2nd Ed. PRIMER-E, Plymouth.
  2. Anderson, M.J. (2001). A new method for non-parametric multivariate analysis of variance. Austral Ecology, 26, 32–46.
  3. Legendre, P. & Legendre, L. (2012). Numerical Ecology, 3rd English Ed. Elsevier.
  4. Magurran, A.E. (2004). Measuring Biological Diversity. Blackwell Publishing.
  5. ter Braak, C.J.F. (1986). Canonical correspondence analysis: a new eigenvector technique for multivariate direct gradient analysis. Ecology, 67(5), 1167–1179.