<p>Distance based redundancy analysis (DbRDA) ordinations of models with the lowest AICc value of all competing models for: a) total sponge abundance; b) sponge abundance when <i>Lamellodysidea herbacea</i> was excluded; and c) <i>Lamellodysidea herbacea</i> abundance.</p
To be able to fit a parametric model successfully using maximum likelihood, all the parameters need ...
Soil samples: [Ct], Control; [Ag], Arctocephalus gazella; [Ml], Mirounga leonina; [Ld], Larus domini...
<p>These four plots provide a visualization of the corresponding multivariate multiple regression mo...
<p>Distance based redundancy ordination (DbRDA) of the model with the lowest AICc value for the mult...
<p>(a) Main environmental variables (organic matter, turbidity and total vegetation and algal cover)...
<p>The DISTLM partitioned the variance in phytoplankton fatty acids explained by the predictor varia...
<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 ...
<p>The DistLM models presented are: layers integrated for 0–1000 m depth (upper) and layers integrat...
<p>Vectors indicate direction of the parameter effect in the ordination plot. Chl <i>a</i> = Ln of s...
Distance-based redundancy analysis (db-RDA) results for relationships of environmental and landscape...
<p>The distance-based redundancy analysis was constrained by the environmental data. The lengths of ...
<p>Vectors represent correlations of variables with community structure along the first two dbRDA ax...
<p>The hulls identify the centroids of each dataset. (B) Relative abundance of selected genera in th...
<p><b>A</b>: Results of dbRDA applied to the acoustic distances among recordings, with factor “Time”...
To be able to fit a parametric model successfully using maximum likelihood, all the parameters need ...
Soil samples: [Ct], Control; [Ag], Arctocephalus gazella; [Ml], Mirounga leonina; [Ld], Larus domini...
<p>These four plots provide a visualization of the corresponding multivariate multiple regression mo...
<p>Distance based redundancy ordination (DbRDA) of the model with the lowest AICc value for the mult...
<p>(a) Main environmental variables (organic matter, turbidity and total vegetation and algal cover)...
<p>The DISTLM partitioned the variance in phytoplankton fatty acids explained by the predictor varia...
<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 ...
<p>The DistLM models presented are: layers integrated for 0–1000 m depth (upper) and layers integrat...
<p>Vectors indicate direction of the parameter effect in the ordination plot. Chl <i>a</i> = Ln of s...
Distance-based redundancy analysis (db-RDA) results for relationships of environmental and landscape...
<p>The distance-based redundancy analysis was constrained by the environmental data. The lengths of ...
<p>Vectors represent correlations of variables with community structure along the first two dbRDA ax...
<p>The hulls identify the centroids of each dataset. (B) Relative abundance of selected genera in th...
<p><b>A</b>: Results of dbRDA applied to the acoustic distances among recordings, with factor “Time”...
To be able to fit a parametric model successfully using maximum likelihood, all the parameters need ...
Soil samples: [Ct], Control; [Ag], Arctocephalus gazella; [Ml], Mirounga leonina; [Ld], Larus domini...
<p>These four plots provide a visualization of the corresponding multivariate multiple regression mo...