<p><b>A</b>: Results of dbRDA applied to the acoustic distances among recordings, with factor “Time” as an explanatory variable. <b>B</b>: Results of dbRDA applied to the acoustic distances among recordings, with factor “Site” as an explanatory variable (A: Aoupinié, K: Koghis, M: Mandjélia). The length of the arrows represents residuals: each arrow connects the position of a recording predicted by the time in which it was done or the site in which it was done (where the arrow starts) to its real position based on raw data (real acoustic composition where the arrow ends).</p
A non-linear version of redundancy analysis is introduced. The technique is called REDUNDALS. It is ...
<p>Vectors indicate direction of the parameter effect in the ordination plot. Chl <i>a</i> = Ln of s...
<p>Results from a Mantel test analyzing the relationship between vocal variation (Euclidean distance...
A Spearman’s dissimilarity matrix was used as the input for each dbRDA. (TIFF)</p
<p>These four plots provide a visualization of the corresponding multivariate multiple regression mo...
<p>Distance-based redundancy analysis (dbRDA) of macroinvertebrate samples in autumn, overlaid with ...
<p>Distance-based redundancy analysis (dbRDA) of macroinvertebrate samples in spring, overlaid with ...
Distance-based redundancy analysis (db-RDA) results for relationships of environmental and landscape...
<p>Vectors represent correlations of variables with community structure along the first two dbRDA ax...
<p>Distance based redundancy analysis (DbRDA) ordinations of models with the lowest AICc value of al...
<p>Vectors are overlaid to represent the different environmental variables most important in each mo...
Vectors represent the effect of environmental variables on dragonfly (A), beetle (B) and bug (C) spe...
<p>The distance-based redundancy analysis was constrained by the environmental data. The lengths of ...
<p>This is as seen in Fig. 2, however here vectors for the 13 most influential fish species in the a...
<p>(a) Main environmental variables (organic matter, turbidity and total vegetation and algal cover)...
A non-linear version of redundancy analysis is introduced. The technique is called REDUNDALS. It is ...
<p>Vectors indicate direction of the parameter effect in the ordination plot. Chl <i>a</i> = Ln of s...
<p>Results from a Mantel test analyzing the relationship between vocal variation (Euclidean distance...
A Spearman’s dissimilarity matrix was used as the input for each dbRDA. (TIFF)</p
<p>These four plots provide a visualization of the corresponding multivariate multiple regression mo...
<p>Distance-based redundancy analysis (dbRDA) of macroinvertebrate samples in autumn, overlaid with ...
<p>Distance-based redundancy analysis (dbRDA) of macroinvertebrate samples in spring, overlaid with ...
Distance-based redundancy analysis (db-RDA) results for relationships of environmental and landscape...
<p>Vectors represent correlations of variables with community structure along the first two dbRDA ax...
<p>Distance based redundancy analysis (DbRDA) ordinations of models with the lowest AICc value of al...
<p>Vectors are overlaid to represent the different environmental variables most important in each mo...
Vectors represent the effect of environmental variables on dragonfly (A), beetle (B) and bug (C) spe...
<p>The distance-based redundancy analysis was constrained by the environmental data. The lengths of ...
<p>This is as seen in Fig. 2, however here vectors for the 13 most influential fish species in the a...
<p>(a) Main environmental variables (organic matter, turbidity and total vegetation and algal cover)...
A non-linear version of redundancy analysis is introduced. The technique is called REDUNDALS. It is ...
<p>Vectors indicate direction of the parameter effect in the ordination plot. Chl <i>a</i> = Ln of s...
<p>Results from a Mantel test analyzing the relationship between vocal variation (Euclidean distance...