<p>The sense of the relationships is shown with + in case of positive relationships and – for negative relationships (i.e. lower abundance with high values for the variable). When the regression was almost flat (scale parameter value<±0.001), we considered it unclear. The deviance explained in each case is shown in bottom row (in percentage). We used n = 55 in the 100 m scale, n = 50 in 500, and n = 36 in 2500 m.</p
<p>1: P-values for intercepts not indicated because they have no sensible interpretation.</p><p>2: T...
<p> = 0.05;</p><p> = 0.005;</p><p> = 0.0005.</p><p>Strong (>0.70) and highly significant (p<0.0005) ...
<p>There was a strong overall positive relationship. However, plotting and fitting linear regression...
<p>The sense of the relationships is shown with + in case of positive relationships and – for negati...
<p>The sense of the relationships is shown with + in case of positive relationships and – for negati...
<p>The sense of the relationships is shown with + in case of positive relationships and – for negati...
<p>Summary results of a GLM - multiple regression analysis, testing the relationship between indepen...
GLM-based relations between the 18 individual predictor variables and tree species richness.</p
<p>Regression coefficients are presented; their absolute value indicate the relative importance of t...
<p>The percent deviance explained (R<sup>2</sup>) when each geographic variable was modelled indepen...
<p><i>df</i> represents the degrees of freedom for the sources of variation. Bold numbers indicate s...
<p>S.E. represents the standard error of the coefficients. Bold numbers indicate significant P-value...
<p>Relationships between the differences in explained deviance (%D<sup>2</sup>) and AUC between CQO ...
<p>Significant <i>p</i>-values and subsequent R<sup>2</sup> values are noted in bold. All slopes/rel...
<p>Values of deviance for each factor, residual deviance (res. dev.), change in deviance, percentage...
<p>1: P-values for intercepts not indicated because they have no sensible interpretation.</p><p>2: T...
<p> = 0.05;</p><p> = 0.005;</p><p> = 0.0005.</p><p>Strong (>0.70) and highly significant (p<0.0005) ...
<p>There was a strong overall positive relationship. However, plotting and fitting linear regression...
<p>The sense of the relationships is shown with + in case of positive relationships and – for negati...
<p>The sense of the relationships is shown with + in case of positive relationships and – for negati...
<p>The sense of the relationships is shown with + in case of positive relationships and – for negati...
<p>Summary results of a GLM - multiple regression analysis, testing the relationship between indepen...
GLM-based relations between the 18 individual predictor variables and tree species richness.</p
<p>Regression coefficients are presented; their absolute value indicate the relative importance of t...
<p>The percent deviance explained (R<sup>2</sup>) when each geographic variable was modelled indepen...
<p><i>df</i> represents the degrees of freedom for the sources of variation. Bold numbers indicate s...
<p>S.E. represents the standard error of the coefficients. Bold numbers indicate significant P-value...
<p>Relationships between the differences in explained deviance (%D<sup>2</sup>) and AUC between CQO ...
<p>Significant <i>p</i>-values and subsequent R<sup>2</sup> values are noted in bold. All slopes/rel...
<p>Values of deviance for each factor, residual deviance (res. dev.), change in deviance, percentage...
<p>1: P-values for intercepts not indicated because they have no sensible interpretation.</p><p>2: T...
<p> = 0.05;</p><p> = 0.005;</p><p> = 0.0005.</p><p>Strong (>0.70) and highly significant (p<0.0005) ...
<p>There was a strong overall positive relationship. However, plotting and fitting linear regression...