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Emigration effects on estimates of age- and sex-specific survival of two sciurids.

Matthew James WeldyDamon B LesmeisterClinton W Epps
Published in: Ecology and evolution (2022)
Age- and sex-specific survival estimates are crucial to understanding important life history characteristics, and variation in these estimates can be a key driver of population dynamics. When estimating survival using Cormack-Jolly-Seber (CJS) models, emigration is typically unknown but confounded with apparent survival. Consequently, especially for populations or age classes with high dispersal rates, apparent survival estimates are often biased low and temporal patterns in survival might be masked when site fidelity varies temporally. We used 9 years of annual mark-recapture data to estimate age-, sex-, and time-specific apparent survival of Humboldt's flying squirrels ( Glaucomys oregonensis ) and Townsend's chipmunks ( Neotamias townsendii ). For Humboldt's flying squirrels, these estimates support a small body of research investigating potential variation in survival among age and sex classes, but age- and sex-specific survival has not been evaluated for Townsend's chipmunks. We also quantified the effects of age- and sex-specific emigration on confounded estimates of apparent survival. Our estimates of juvenile flying squirrel survival were high relative to other small mammal species and estimates for both species were variable among years. We found survival differed moderately among age and sex classes for Humboldt's flying squirrels, but little among age and sex classes for Townsend's chipmunks, and that the degree to which emigration confounded apparent survival estimates varied substantially among years. Our results demonstrate that emigration can influence commonly used estimates of apparent survival. Unadjusted estimates confounded the interpretation of differences in survival between age and sex classes and masked potential temporal patterns in survival because the magnitude of adjustment varied among years. We conclude that apparent survival estimators are robust during some time periods; however, when emigration rates vary in time, the effects of emigration should be carefully considered and accounted for.
Keyphrases
  • free survival
  • machine learning
  • risk assessment
  • climate change