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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.