Co-Correspondence Analysis: A New Ordination Method to Relate Two Community Compositions

Abstract

A new ordination method, called co‐correspondence analysis, is developed to relate two types of communities (e.g., a plant community and an animal community) sampled at a common set of sites in a direct way. The method improves the simple, indirect approach of applying correspondence analysis (reciprocal averaging) to the separate species data sets and correlating the resulting ordination axes. Co‐correspondence analysis maximizes the weighted covariance between weighted averaged species scores of one community and weighted averaged species scores of the other community. It thus attempts to identify the patterns that are common to both communities. Both a symmetric descriptive and an asymmetric predictive form are developed. The symmetric form relates to co‐inertia analysis and the asymmetric, predictive form to partial least‐squares regression. In two examples the predictive power of co‐correspondence analysis is compared with that of canonical correspondence analyses on syntaxonomic and environmental data. In the first example, carabid beetles in roadside verges are shown to be more closely related to plant species composition than to vegetation structure (biomass, height, roughness, among others), and, in the second example, bryophytes in spring meadows are shown to be more closely related to the species composition of the vascular plants than to the measured water chemistry.

How do plant communities and flower visitors relate? A case study of semi-natural xerothermic grasslands

“…The ordination method, co-correspondence, which relates two community compositions (plant and animal), was originally tested on the carabid beetle and vascular plant species along roadside verges in the Netherlands. Among others [16] found first two axes of Co-CA significant as well as high positive correlations between the first two axes of DCA. Also, it was reported that 28% of the variance in the species composition of water beetles was explained by wetland plants [41].…”

“…To calculate the abundance of insects for the plots, the total number of individuals was analyzed. The two species data matrixes were subjected to co-correspondence analysis (Co-CA), the latest ordination technique that examines the relationships between two communities [16]. Data on insects were treated as a dependent variable in this analysis.…”

“…A study that lasted less than ten days was unlikely to identify all of the pollinators of even a moderately generalized species. Moreover, other studies on the sampling of arthropod assemblages [16,26,41] of particular taxa, which used different methods, lasted several months over a period of two years or a site was visited at least twice a year. Plant cover turned out not to be a predictor of insect richness.…”

“…There are some reports on the relationship between insect and plant species composition, using phytosociological data [16,17], but they do not cover all of those aspects. Our study was done under only one condition.…”

Testing a new multigroup inference approach to reconstructing past environmental conditions

“…If this is the case then greater use of sediment traps and data loggers (e.g., Kamenik & Schmidt 2005b) may suggest a practical way forwards for environmental factors with a large seasonal fluctuation, such as water temperature. Finally a different mathematical way forwards might be to try to adapt the co-correspondence analysis approach (ter Braak & Schaffers 2004) to ordination, which relates one environmental data matrix to another data matrix, to address the problem of multigroup inference.…”