Dead before detection: addressing the effects of left truncation on survival estimation and ecological inference for neonates

Neonate survival is a key life history trait, yet remains challenging to measure in wild populations because neonates can be difficult to capture at birth. Estimates of survival from neonates that are opportunistically captured might be inaccurate because some individuals die before sampling, resulting in data that are left truncated. The resulting overestimation of survival rates can further affect ecological inference through biased estimates of covariate effects in survival models, yet is not addressed in most studies of animal survival. Here, we quantify the effects of left truncation on survival estimates and subsequent ecological inference. Vaginal implant transmitters (VITs) enable capture of ungulates at birth, yielding data without left truncation. The effects of left truncation on survival estimation were quantified using age-dependent survival models for VIT and opportunistically captured neonatal deer. Differences in daily survival rates (DSRs) and cumulative survival probability were calculated for the first 70days of life. In addition, left truncation was simulated by removing fawns that died during the first 1 or 2days of life from the VIT-caught sample, isolating the effect of left truncation. Cumulative probability of survival during the first 70days of life was overestimated by 7-23% for fawns caught opportunistically compared with those caught by VIT, depending on model design. Differences in DSRs were large at age 1day, but had converged by age 30days. Simulated left truncation resulted in overestimates of survival of up to 31%. Model selection and covariate coefficients were strongly affected by left truncation, producing spurious ecological inference, including changes to sign and/or magnitude of inferred effects of all covariates. We recommend (i) every effort be made to capture neonates; (ii) consistent capture methods, using at least in part non-truncating techniques, be implemented across years and study areas; and (iii) exclusion of left-truncated data from survival estimates until DSRs converge with those calculated from non-truncated data. This work emphasizes the importance of accounting for left truncation in survival estimation for any species with strong age-dependent survival in order to prevent biased conclusions produced by sampling method rather than true ecological effects. 10.1111/(ISSN)2041-210X