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geb780-sup-0001-si.txt1K Appendix S1 Null model computer code.
geb780-sup-0002-si.doc1368K Figure S1 Simulation results for the null model.
geb780-sup-0002-si.doc1368K Figure S2 Distribution of survey routes across and environmental loadings on the first two principal components axes.
geb780-sup-0002-si.doc1368K Figure S3 Structural equation model for raw spatial turnover, using variables selected in the multiple regression model with a delta Bayesian information criterion < 2.
geb780-sup-0002-si.doc1368K Figure S4 Structural equation models linking principal components, gamma diversity and turnover.
geb780-sup-0002-si.doc1368K Figure S5 Structural equation model for spatial null departure, using variables (including principal components axes) selected in the multiple regression model with a delta Bayesian information criterion < 2.
geb780-sup-0002-si.doc1368K Table S1 Environmental variable loadings on principal components axes.
geb780-sup-0002-si.doc1368K Table S2 Best fit multiple regression models using principal components axes.
geb780-sup-0002-si.doc1368K Table S3 Best fit multiple regression models accounting for spatial autocorrelation.
geb780-sup-0002-si.doc1368K Table S4 Best fit multiple regression models using principal components axes and accounting for spatial autocorrelation.

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