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Table 3 Squared semi-partial correlation and multiple correlation of spatial and environmental variables

From: Latitudinal diversity patterns of Chilean coastal fishes: searching for causal processes

  Squared semi-partial correlation Multiple regression
Habitat Variable df Parameter SE T P value sr2 F (1, 5) P value r 2
Intertidal Lat 1 0.01 0.01 1.01 0.35 0.01 13.81 <0.01 0.908
Chl-a 1 −0.29 0.18 −1.65 0.14 0.04
Chl-a2 1 0.10 0.06 1.75 0.12 0.04
Area 1 0 0 −1.33 0.23 0.02
SST 1 0.03 0.02 1.61 0.15 0.03
       Σ sr2= 0.15
Subtidal Lat 1 0.04 0.02 2.42 0.05 0.07 15.51 <0.01 0.917
Chl-a 1 −0.97 0.45 −2.16 0.07 0.05
Chl-a2 1 0.31 0.15 2.12 0.07 0.05
Area 1 −0.02 0.01 −2 0.09 0.05
SST 1 0.15 0.05 2.79 0.03 0.09
        Σ sr2= 0.32    
  1. Squared semi-partial correlation (sr2) and multiple correlation (r2) of spatial (Lat, latitude), and environmental variables (SST, sea surface temperature; Area, continental shelf area; and the linear (Chl-a) and quadratic component (Chl-a2) of chlorophyll-a) on the pattern of geographic variation in species richness of fish inhabiting the intertidal and subtidal along the Chilean coast. The sum Σ is the sum of the squared semi-partial correlation for each variable included in the regression model. P values in italics indicate a significant effect of a given parameter. SE, standard error.