Supplementary figures S1-S5 from Temperature is a poor proxy for synergistic climate forcing of plankton evolution

• Main Authors: Anieke Brombacher, Wilson, Paul A., Bailey, Ian, Ezard, Thomas H. G.
• Format: Text
• Language: unknown
• Published: The Royal Society 2018
• Subjects: Evolutionary Biology; FOS Biological sciences; Environmental Science; 40308 Palaeontology incl. Palynology; FOS Earth and related environmental sciences; North Atlantic
• Online Access: https://dx.doi.org/10.6084/m9.figshare.6743357.v1; https://rs.figshare.com/articles/Supplementary_figures_S1-S5_from_Temperature_is_a_poor_proxy_for_synergistic_climate_forcing_of_plankton_evolution/6743357/1

S1: Study species Globoconella puncticulata (a) and Truncorotalia crassaformis (b). The scale bars represent 100 μm. S2: Map of study site IODP Site U1313 in the North Atlantic. S3: Autocorrelation plots for traits of Globoconella puncticulata showing autocorrelation in the original time series (a-c) but not in the first differences (d-f). S4: Autocorrelation plots for traits of Truncorotalia crassaformis showing autocorrelation in the original time series (a-c) but not in the first differences (d-f ). Only area in T. crassaformis still contained a small amount of autocorrelation in the first differences time series. However, comparison of two Generalized Least Squares models with and without autocorrelation (by setting the continuous auto-correlation parameter phi=0.3 and phi=0.1, which converges to 0 under maximum likelihood, respectively) show lower AIC values for the model without autocorrelation, implying that the model with temporal autocorrelation is actually a poorer fit to the data than that without. S5: ΔAIC values showing the added relative importance of each environmental parameter or combination of parameters to the total model.