Fig 1.
Position of transect across the sandplains in south west Australia showing the associated rainfall gradient.
(A) Numbered locations indicate where sets of 16 quadrats were established. Three floristic zones were recognised based on rainfall isohyets (adapted from [19]). Background shows mean annual rainfall gradient (blue–high rainfall to brown–low rainfall), and isohyets calculated from gridded data 1961–1990 sourced from the Bureau of Meteorology [20]. (B) Profile of mean annual rainfall along vectors connecting the 10 locations (numbered circles) on the transect from south to north.
Fig 2.
Distribution of inter-quadrat distances and patterns in species accumulation, richness, and average ranges size encountered across the transect.
(A) Distribution of inter-quadrat distances. (B) Species accumulation curves from the south (high rainfall) to the north (arid). (C) Mean species richness for each of the ten locations showing trend line. (D) Average range size (km2) of species recorded at each of the 10 locations; loess smoothing line fitted. Vertical bars separate High Rainfall Zone (left) from Transitional Rainfall Zone (middle) and Arid Zone (right).
Fig 3.
Fitted I-splines of the GDM and relative importance of predictors.
Partial regression fits (A-H) of predictor variables making a significant contribution to explaining species turnover along the 870 km sandplain transect as measured by Sørensen dissimilarity. Variables arranged in decreasing order of importance value from geographic distance (A) to mean temperature of the driest quarter (F). The final three panels illustrate the relationship between: (G) observed floristic dissimilarity between each site pair in the dataset and the linear predictor of the GDM (termed ‘ecological distance’), (H) observed versus predicted dissimilarity and (I) relative importance of predictor variables determined by summing the coefficients of the I-splines from the GDM [26].
Fig 4.
Proportion of variance of the GDM explained by the spatial, climate and soil variables across the transect.
Graph showing the independent (geographic distance, G; climate, C; soil, S) and shared components (G-C, G-S, C-S, G-C-S) of the deviance explained for the fitted model across the 870 km transect. Total variance explained by the model was 87%.
Fig 5.
Proportion of variance of the GDM explained by the spatial, climate and soil variables at each of the 10 locations.
Bar graphs showing independent (geology, dark grey; soil, white; climate, black) and shared (light grey) components of the deviance explained for the fitted models from each of the 10 locations. Models for locations 4 and 5 have significant contributions from all three variable groups and the shared components have been pooled. Vertical bars separate High Rainfall Zone (left) from Transitional Rainfall Zone (middle) and Arid Zone (right).
Table 1.
Relative importance of predictor variables determined by summing the coefficients of the I-splines from each of the 10 location scale GDMs [26].
Fig 6.
Patterns in beta diversity measures along the transect.
(A) Individual location estimates (based on 16 quadrats within each location) of βSOR (solid squares) were uniformly high and showed no correlation with latitude. The decreasing trend seen in the species replacement component βSIM (open circles) was not significantly different from zero. (B) Patterns in Whittaker’s βW-1 (solid triangles) were similar, the slope was not significantly different from zero. Vertical bars separate High Rainfall Zone (left) from Transitional Rainfall Zone (middle) and Arid Zone (right).
Fig 7.
Changes in beta diversity measures with increasing linear extent.
(A) Changes in βSOR (solid squares) and βSIM (open circles) with increasing distance to north (controlling for number of quadrats). (B) Increases in Whittaker’s βW-1 over the same interval.