Accurately measuring nest survival is challenging because nests must be discovered to be monitored, but nests are typically not found on the first day of the nesting interval. Studies of nest survival therefore often monitor a sample that overrepresents older nests. To account for this sampling bias, a daily survival rate (DSR) is estimated and then used to calculate nest survival to the end of the interval. However, estimates of DSR (and thus nest survival) can still be biased if DSR changes with nest age and nests are not found at age 0. Including nest age as a covariate of DSR and carefully considering the method of estimating nest survival can prevent such biases, but many published studies have not fully accounted for changes in DSR with nest age. I used a simulation study to quantify biases in estimates of nest survival resulting from changes in DSR with nest age under a variety of scenarios. I tested four methods of estimating nest survival from the simulated datasets and evaluated the bias and variance of each estimate. Nest survival estimates were often strongly biased when DSR varied with age but DSR was assumed to be constant, as well as when the model included age as a covariate but calculated nest survival from DSR at the mean monitored nest age (the method typically used in previous studies). In contrast, biases were usually avoided when nest survival was calculated as the product of age-specific estimates of DSR across the full nesting interval. However, the unbiased estimates often showed large variance, especially when few nests were found at young ages. Future field studies can maximize the accuracy and precision of nest survival estimates by aiming to find nests at young ages, including age as a covariate in the DSR model, and calculating nest survival as the product of age-specific estimates of DSR when DSR changes with nest age.
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28 June 2021
Fully accounting for nest age reduces bias when quantifying nest survival
Emily L. Weiser
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Ornithological Applications
Vol. 123 • No. 3
August 2021
Vol. 123 • No. 3
August 2021
Bayesian
bayesiano
bias
daily survival rate
éxito del nido
logistic-exposure model
Mayfield method