Feeding in Marine Mammals: Tables

TABLE 1. Linear regression analyses for Pinnipedimorpha and extant families’ diversity through time against climate and productivity variables: δ¹⁸O (variable A), δ¹³C (variable B), diatom species diversity (variable C), sea level changes (variable D). Best model, including one, two, three, or all four variables, is selected based on its AIC (Akaike’s Information Criterion) score. Diversity of each group is considered from the time bin of first occurrence (Chattian for Pinnipedimorpha, Burdigalian for extant families). Significant values (p < 0.05) are in bold. Only data (R², p-value, AIC) for the best model for each group are reported, for complete results see Appendix 2, Table S1.

TABLE 2. Linear regression analyses for Pinnipedimorpha habitat preference through time against climate and productivity variables: δ¹⁸O (variable A), δ¹³C (variable B), diatom species diversity (variable C), sea level changes (variable D). Best model, including one, two, three, or all four variables, is selected based on its AIC (Akaike’s Information Criterion) score. Only prevalent categories (with at least one time bin with a count > 5) were considered. Significant values (p < 0.05) are in bold. Only data (R², p-value, AIC) for the best model for each category are reported, for complete results see Appendix 2, Table S2.

TABLE 3. Linear regression analyses for Pinnipedimorpha prey type preference through time against climate and productivity variables: δ¹⁸O (variable A), δ¹³C (variable B), diatom species diversity (variable C), sea level changes (variable D). Best model, including one, two, three, or all four variables, is selected based on its AIC (Akaike’s Information Criterion) score. Only prevalent categories (with at least one time bin with a count > 5) were considered. Significant values (p < 0.05) are in bold. Only data (R², p-value, AIC) for the best model for each category are reported, for complete results see Appendix 2, Table S3.

TABLE 4. Linear regression analyses for Cetacea and Odontoceti and Mysticeti diversity through time against climate and productivity variables: δ¹⁸O (variable A), δ¹³C (variable B), diatom species diversity (variable C), sea level changes (variable D). Best model, including one, two, three, or all four variables, is selected based on its AIC (Akaike’s Information Criterion) score. Significant values (p < 0.05) are in bold. Only data (R², p-value, AIC) for the best model for each category are reported, for complete results see Appendix 2, Table S4.

TABLE 5. Linear regression analyses for Cetacea habitat preference through time against climate and productivity variables: δ¹⁸O (variable A), δ¹³C (variable B), diatom species diversity (variable C), sea level changes (variable D). Best model, including one, two, three, or all four variables, is selected based on its AIC (Akaike’s Information Criterion) score. Significant values (p < 0.05) are in bold. Only data (R², p-value, AIC) for the best model for each category are reported, for complete results see Appendix 2, Table S5.

TABLE 6. Linear regression analyses for Cetacea prey type preference through time against climate and productivity variables: δ¹⁸O (variable A), δ¹³C (variable B), diatom species diversity (variable C), sea level changes (variable D). Best model, including one, two, three, or all four variables, is selected based on its AIC (Akaike’s Information Criterion) score. Significant values (p < 0.05) are in bold. Only data (R², p-value, AIC) for the best model for each category are reported, for complete results see Appendix 2, Table S6.

TABLE 7. Linear regression analyses for Cetacea prey capture strategies through time against climate and productivity variables: δ¹⁸O (variable A), δ¹³C (variable B), diatom species diversity (variable C), sea level changes (variable D). Best model, including one, two, three, or all four variables, is selected based on its AIC (Akaike’s Information Criterion) score. Significant values (p < 0.05) are in bold. Only data (R², p-value, AIC) for the best model for each category are reported, for complete results see Appendix 2, Table S7.

TABLE 8. Linear regression analyses for Sirenia and Desmostylia diversity through time against climate and productivity variables: δ¹⁸O (variable A), δ¹³C (variable B), diatom species diversity (variable C), sea level changes (variable D). Best model, including one, two, three, or all four variables, is selected based on its AIC (Akaike’s Information Criterion) score. Diversity of Desmostylia is considered from the time bin of first occurrence to the last (from Rupelian to Tortonian). To account for their low diversity, these groups were also considered together (“Sirenia and Desmostylia combined”). Significant values (p < 0.05) are in bold. Only data (R², p-value, AIC) for the best model for each group are reported, for complete results see Appendix 2, Table S8.

TABLE 9. Correlation test (Pearson’s coefficient) for Sirenia, Desmostylia, and “Sirenia and Desmostylia combined” diversity through time with climate and productivity variables: δ¹⁸O, δ¹³C, diatom species diversity, sea level changes. Significant values (p < 0.05) are in bold. Cells for auto-correlated variables are grayed out. P-values for the correlations are reported in Appendix 2, Table S9.