Science Advances

Supplementary Materials

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  • Supplementary Text
  • fig. S1. Locations of the three P. multocida–associated disease events (1981, 1988, and 2015) in the Betpak-dala population and control sites at which calving proceeded without a die-off since 1979, used in the climate analysis (x and y units are longitude and latitude).
  • fig. S2. Photographs depicting the die-off of saiga and their clinical signs and pathology.
  • fig. S3. Fluorescence in situ hydridization (FISH) photomicrograph showing position of fluorescing P. multocida bacteria.
  • fig. S4. Box plots for cases (die-off sites) and controls (no die-off) using the full data set, with real dates of onset if available or 9 May if not, showing the relationship between cases/controls and selected climate metrics aggregated over 10-day periods before onset.
  • fig. S5. Contributions of variables to components 1 and 2 of the PCA using the full data set, with real dates of onset if available or 9 May if not.
  • table S1. PCR primers used for microorganism detection.
  • table S2. A summary of the largest MMEs in saiga attributed to Pasteurellaceae-related syndromes.
  • table S3. Results of an ICP-MS analysis of livers (w/w) of three dead saigas from May 2015 (Tengiz group).
  • table S4. Assuming a diagnosis of HS as a primary cause of death, this table is a list of possible stressors, which may cause suppressed immunity in the host or
    increased virulence and invasion of a commensal parasite such as P. multocida, subsequent septicemia in infected hosts, and/or enhanced transmission.
  • table S5. Comparison of means for cases and controls using the full data set (all MME years); real dates of onset or 9 May; and climate metrics aggregated over the 10 days to onset.
  • table S6. Long-term climate anomaly data at Kostanai sites (ERA data using actual die-off site, NCEP data using pixel, covering entire Torgai area).

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