A method of linking multivariate community structure to environmental variables

Abstract

The method of choice for multivariate representation of community structure is often non-metric multi-dimensional scaling (MDS). This has great flexibility in accomn~odating biologically relevant (i.e. non correlation-based) definitions of similarity In species composition of 2 samples, and in preserving the rank-order relations amongst those similarities in the placing of samples in an ordination. Correlation-based techniques (such as Canonical Correlation) are then inappropriate in linking the observed biotic structure to measured environmental variables; a more natural approach is simply to compare separate sample ordinations from biotic and abiotic variables and choose that subset of environmental variables which provides a good match between the 2 configurations. In fact, the fundamental constructs here are not the ordination plots but the (rank) similarity matrices which underlie them: a suitable measure of agreement between 2 such matrices is therefore proposed and used to define an optimal subset of environmental variables w h~c h 'best explains' the biotic structure. This simple technique is illustrated wlth 3 data sets, from studles of macrobenthic, meiobenthic and diatom communities in estuarine and coastal waters.

Riqueza, estrutura e interações edáficas em um gradiente de restinga do Parque Estadual do Acaraí, Estado de Santa Catarina, Brasil

“…Para explicar as diferenças estruturais entre as formações em função dos fatores edáficos foi empregado o teste de Mantel e adotado o protocolo bioenv (Clarke & Ainsworth 1993). Para tanto, foram construídas duas matrizes, uma incluindo a abundânica das espécies e outra com as variáveis de solo.…”

Branch to colony trajectory in a modular organism: Pattern formation in the Indo‐Pacific coral Stylophora pistillata

“…1c,d) from each of the 63 colonies were measured and analyzed. These MPs were subjected to Draftsman plot analysis (Shaish, 2004) to find and omit pairs of parameters sharing a high degree of correlation with each other (P Ͼ 0.95), meaning that they did not contribute additional information to the data analysis (Clarke and Ainsworth, 1993). The measurements were taken with digital calipers to the nearest 0.01 mm, and data were stored using EXCEL software.…”

“…Data analysis was performed by multivariate analysis methods using PRIMER 5 software (Clarke, 1993;Clarke and Ainsworth, 1993). Data were standardized by rescaling each category, which ensured that each of the characters contributed equally to the overall information on the colony's morphological structure.…”

“…In this analysis, the genets were represented by points on a two-dimensional graph. The closer the points were, the higher was their similarity (Clarke and Ainsworth, 1993). We also used the hierarchical agglomerative clustering analysis method, in which samples were organized in a tree-shaped diagram, according to their level of similarity (Clarke and Ainsworth, 1993).…”

Assessing a Quick Monitoring Method Using Rocky Intertidal Communities as a Bioindicator: A Multivariate Approach in Algeciras Bay

“…This analysis is a direct gradient technique in which the resulting ordenation of stations is directly related to the values of the environmental factors (Ter Braak, 1986). Relationships between multivariate biological structure and environmental variables were also examined using the BIO-ENV procedure (Clarke and Ainsworth, 1993). Percentage of similarity analysis (SIMPER) (Clarke, 1993) was used to determine the species involved in grouping of the different sampling localities.…”