(A) Multivariate Regression Tree (MVRT) for benthic assemblages of the Fernando de Noronha Archipelago, off NE Brazil. Environmental drivers for each split are given in the upper portion, while organisms responsible for the split and the relative contribution of the split to total model variation explained are given in the lower portion. (B) Principal Component Analysis (PCA) plot showing separation between the five distinct assemblages identified by the MVRT. (C) Spatial distribution of the five typical assemblages according to depth strata and sampling sites. Codes for sampling stations as in Fig 1.</p
<div><p>As marine ecosystems are influenced by global and regional processes, standardized informati...
<p>The explanatory variables were: site, topographic complexity, habitat diversity, coral species ri...
<p>Poster presentation at ATLAS 3rd General Assembly.</p> <p> </p> <p>An objective statistical app...
Optimal settings and predictive performance of boosted regression tree (BRT) analyses used for model...
<p>(A) Spatial variation in benthic habitat on reefs at the transect level, shown for the first two ...
<div><p>Marine physical and geochemical data can be valuable surrogates for predicting the distribut...
The explanatory variables were: coral species, depth, and reef zone. For each of the terminal nodes ...
The best tree structure from a multivariate regression tree analysis of the counts of 10 species pre...
As marine ecosystems are influenced by global and regional processes, standardized information on co...
As marine ecosystems are influenced by global and regional processes, standardized information on co...
<p>Top panel: samples classified according to habitat; Bottom panel: samples classified according to...
As marine ecosystems are influenced by global and regional processes, standardized information on co...
As marine ecosystems are influenced by global and regional processes, standardized information on co...
<p>The explanatory variables were: site, topographic complexity, habitat diversity, coral species ri...
Relative contributions (%) of explanatory variables are given. Taxa/functional groups are shown in d...
<div><p>As marine ecosystems are influenced by global and regional processes, standardized informati...
<p>The explanatory variables were: site, topographic complexity, habitat diversity, coral species ri...
<p>Poster presentation at ATLAS 3rd General Assembly.</p> <p> </p> <p>An objective statistical app...
Optimal settings and predictive performance of boosted regression tree (BRT) analyses used for model...
<p>(A) Spatial variation in benthic habitat on reefs at the transect level, shown for the first two ...
<div><p>Marine physical and geochemical data can be valuable surrogates for predicting the distribut...
The explanatory variables were: coral species, depth, and reef zone. For each of the terminal nodes ...
The best tree structure from a multivariate regression tree analysis of the counts of 10 species pre...
As marine ecosystems are influenced by global and regional processes, standardized information on co...
As marine ecosystems are influenced by global and regional processes, standardized information on co...
<p>Top panel: samples classified according to habitat; Bottom panel: samples classified according to...
As marine ecosystems are influenced by global and regional processes, standardized information on co...
As marine ecosystems are influenced by global and regional processes, standardized information on co...
<p>The explanatory variables were: site, topographic complexity, habitat diversity, coral species ri...
Relative contributions (%) of explanatory variables are given. Taxa/functional groups are shown in d...
<div><p>As marine ecosystems are influenced by global and regional processes, standardized informati...
<p>The explanatory variables were: site, topographic complexity, habitat diversity, coral species ri...
<p>Poster presentation at ATLAS 3rd General Assembly.</p> <p> </p> <p>An objective statistical app...