Figure 1 – Flowchart of procedures used for selecting the best
Geographically Weighted Regression (GWR) model. W Global - connectivity
between sampling sites defined as Euclidian distance between all sites;
W Basin - connectivity between sampling sites defined as Euclidian
distance between all sites present in a same hydrographic basin and W
FEOW - connectivity between sampling sites defined as Euclidian distance
between all sites present in the same ecoregion. AIC - Akaike
Information Criterion.
Figure 2 – Graph of the AIC and spatial autocorrelation by
distance class for the a) Global, b) Basin and c) FEOW matrix.
Figure 3 – Moran scatterplot for the a) Global, b) Basin (b)
and c) FEOW matrix.
Figure 4 – Autocorrelation values of fish richness and GWR
residuals using the global connectivity (W Global) matrix.
Figure 5 – Global adjustment of the GWR model done using a W
Global matrix considering a) total, b) Amazonian, c) Atlantic
North/Northeast transect, d) Tocantins, e) São Francisco, f) Atlantic
east transect, g) Paraná and h) Atlantic southeast transect data.
Figure 6 – Spatialization of the GWR regression coefficients
and classification of sites according to the hydrographic basin. a)
Annual Temperature Variation, b) Evapotranspiration in June, c)
Terrestrial Primary Production, d) Average Annual Precipitation, e)
Annual Precipitation Variation and f) Evapotranspiration in January.