Extended Data Fig. 3: Comparison of flooding relationships with species turnover using two alternative procedures for populating cell compositional data.
From: One sixth of Amazonian tree diversity is dependent on river floodplains
While interpolating species abundances maximizes the number of cells where species turnover can be calculated, it introduces spatial autocorrelation. On the other hand, pooling inventories within grid cells reduces the number of cells where species turnover can be calculated, but it maintains spatial independence among cells. We compared both methods to assess the robustness of our results to spatial dependencies. For the approach based on pooling, species cell abundance information was pooled only from inventories located inside individual grid cells, rather than interpolated from inventories from a larger 300 km circular window, in order to avoid residual spatial autocorrelation. Quantile regression slopes (at tau = 0.1) and their 95% confidences intervals are shown for várzea- and igapó-terra firme. The lower bounds of várzea-terra firme species turnover with flooding are statistically equivalent between pooled compositional data (slope ± 95% CI = 1.29 × 10−2 ± 1.21 × 10−2, t = 2.20, n = 25, p = 0.038) and interpolated data (slope ± 95% CI = 1.21 × 10−2 ± 2.48 × 10−3, t = 9.57, n = 301, p < 0.001). The lower bounds for igapó-terra firme are likewise similar between pooled (slope ± 95% CI = 1.54 × 10−2 ± 1.19 × 10−2, t = 2.66, n = 22, p = 0.015) and interpolated methods (slope ± 95% CI = 1.05 × 10−2 ± 2.60 × 10−3, t = 7.86, n = 347, p < 0.001). Slopes from all comparisons were significant (p < 0.05) and had overlapping 95% confidence intervals.
