The measurement of selection when detection is imperfect: how good are naïve methods?

The life spans of animals can be measured in natural populations by uniquely marking individuals and then releasing them into the field. Selection on survival (a component of fitness) can subsequently be quantified by regressing the life spans of these marked individuals on their trait values. However, marked individuals are not always seen on every subsequent catching occasion, and for this reason, imperfect detection is considered a problem when estimating survival selection in natural populations.
Capture–mark–recapture methods have been advocated as a powerful means to correct for imperfect detection. Here, we use simulated and field data sets to evaluate the effect of assuming perfect detection (‘naïve methods’), when detection is really imperfect. We compared the performance of the naïve methods with methods correcting for imperfect detection (mark–recapture methods, or MR).
Although the effects of trait-dependent recapture probability are mitigated when recapture probability is...