Table 2 Standardized coefficients from multi-predictor regression models to explain species richness of agamid lizards across Africa.

From: Historical colonization and dispersal limitation supplement climate and topography in shaping species richness of African lizards (Reptilia: Agaminae)

 

OLS

SAR

Coefficient

p

Coefficient

p

Intercept

1.885

***

1.819

***

DISP4

0.542

***

0.306

***

TEMP MAX

−0.146

**

−0.210

*

TEMP MIN

0.333

***

−0.126

n.s.

PREC

−0.251

***

−0.152

n.s.

PREC DRY

−0.107

*

−0.021

n.s.

PREC SEAS

−0.320

***

−0.313

***

PREC SEAS2

−0.373

***

0.144

**

LGM TEMP

0.096

**

0.368

***

LGM PREC

0.350

***

0.011

n.s.

PLIO TEMP

−0.296

***

−0.102

n.s.

MIO TEMP

0.314

***

0.172

*

MIO PREC

0.067

n.s.

0.022

n.s.

TOPO

0.546

***

0.217

***

R 2 PRED

0.450

 

0.276

 

R 2 FULL

—

 

0.891

 

Moran’s I

0.721

 

−0.012

 

p of Moran’s I

***

 

n.s.

 
  1. Two types of models are compared, a non-spatial ordinary least square (OLS) regression and a spatial simultaneous autoregressive (SAR) model. Significant linear effects detected in both OLS and SAR models are indicated by boldface type. PREC DRY and absolute values of LGM PREC were log(x + 1) transformed, all other predictor variables and the response variable (species richness) were untransformed (compare Table 1 for abbreviations and explanations of predictor variables). The explained variance of the environmental components (R2PRED), the explained variance of the full SAR model including both environment and space (R2FULL), the Moran’s I, and the p-value of Moran’s I are given. Significance of Moran’s I was determined by permutation tests (n = 999 permutations). Significance levels: ***p < 0.001; **p < 0.01; *p < 0.05. n.s., not significant.
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