Fig 1.
Number of migrating adult salamanders across the 23-year study period.
Trends are shown for both males (dashed line) and females (solid line).
Fig 2.
Trends and relationships between seasonal climatic variables and salamander population characteristics.
Annual variation in winter-spring transition precipitation (A), minimum winter temperatures (C), and minimum summer temperatures (E). Variation in the total numbers of male (closed circles) and female (open circle) salamander migrants as a function of migration period precipitation (B). The migration start date for male (closed circles) and female (open circles) salamanders based on the 95th percentile arrival day of year (DOY) as a function of minimum previous winter temperature (D). Male (closed circles) and female (open circles) snout-vent lengths (SVL) as a function of minimum previous summer temperatures (F).
Table 1.
Top ranked generalized linear regression models for total abundance (for Akaike model weights [wi] > 0.1) based on no time-lag (t), a two-year time-lag (t– 2), and a three-year time-lag (t—3).
Models were ranked based on differences in AIC corrected for small sample size (ΔAICc), weights and evidence ratios (ER). Climate variable abbreviations can be found in the text or S1 Table.
Table 2.
Top ranked generalized linear regression models for sex ratios (for Akaike model weights [wi] > 0.1) based on no time-lag (t), a two-year time-lag (t– 2), and a three-year time-lag (t—3).
Models were ranked based on differences in AIC corrected for small sample size (ΔAICc), weights and evidence ratios (ER). Climate variable abbreviations can be found in the text or S1 Table.
Fig 3.
Relationship between the coefficient of variation in minimum previous summer temperatures and the snout-vent length (SVL) of migrating adults.
Regression lines are shown for males (closed circles) and females (open circles).
Table 3.
Top ranked generalized linear regression models for male snout-vent length (for Akaike model weights [wi] > 0.1) based on no time-lag (t), a two-year time-lag (t– 2), and a three-year time-lag (t—3).
Models were ranked based on differences in AIC corrected for small sample size (ΔAICc), weights and evidence ratios (ER). Climate variable abbreviations can be found in the text or S2 Table.
Table 4.
Top ranked generalized linear regression models for female snout-vent length (for Akaike model weights [wi] > 0.1) based on no time-lag (t), a two-year time-lag (t– 2), and a three-year time-lag (t– 3).
Models were ranked based on differences in AIC corrected for small sample size (ΔAICc), weights and evidence ratios (ER). Climate variable abbreviations can be found in the text or S2 Table.
Table 5.
Top ranked generalized linear regression models for migration timing statistics (for Akaike model weights [wi] > 0.1).
Models were ranked based on differences in AIC corrected for small sample size (ΔAICc), weights and evidence ratios (ER). Climate variable abbreviations can be found in the text or S1 Table.