《Table 4 Multiple regression of interpolated species richness against four selected factors (LA, STR

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《"Elevational patterns of bird species richness on the eastern slope of Mt.Gongga,Sichuan Province,China"》

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r2adj is the adjusted r2 value for multiple regressions Negative relationships are indicated by“-”LA land area，STR seasonal temperature range，IB invertebrate biomass，MDE the mid-domain effect Numbers in italics indicate significant r2 values （p<0.05）

The spatial autocorrelation in regression residuals and multicollinearity among explanatory variables could affect the credibility of the results and needs to be taken into account（Diniz et al.2003；Graham 2003）.However，multiple conditional autoregressive（CAR）analyses are not robust to small sample sizes（Wu et al.2013b）.Instead，multiple OLS models were used to assess the influence of spatial autocorrelation on the regression results.However，no p value was reported for the multiple regressions（Graham 2003；Brehm et al.2007）.Because MDT，EVI and SP were highly correlated with STR（Table 1），we conducted multiple regression models without MDT，SP and EVI to reduce the multicollinearity in the model.Only LA，IB，MDE and STR were tested in the multiple regressions for all species categories.All analyses were performed in the R packages“MuMIn”（Kamil 2018）and“vegan”（Oksanen et al.2013）.