  Survival is a key life history parameter that can inform management decisions
and life history research. Because true survival is often confounded with
permanent and temporary emigration from the study area, many studies must
estimate apparent survival (i.e., probability of surviving and remaining inside
the study area), which can be much lower than true survival for highly mobile
species. One method for estimating true survival is the Barker joint
live-recapture/live-resight (JLRLR) model, which combines capture data from a
study area (hereafter the capture site) with resighting data from a broader
geographic area. This model assumes that live resights occur throughout the
entire area where animals can disperse to and this assumption is often not met
in practice. Here we use simulation to evaluate survival bias from a JLRLR
model under study design scenarios that differ in the site selection for
resights: global, random, fixed including the capture site, and fixed excluding
the capture site. Simulation results indicate that fixed designs that included
the capture site showed negative survival bias, whereas fixed designs that
excluded the capture site exhibited positive survival bias. The magnitude of
the bias was dependent on movement and survival, where scenarios with high
survival and frequent movement had minimal bias. In effort to help minimize
bias, we developed a multistate version of the JLRLR and demonstrated
reductions in survival bias compared to the single-state version for most
designs. Our results suggest minimizing bias can be accomplished by: 1) using a
random resight design when feasible and global sampling is not possible, 2)
using the multistate JLRLR model when appropriate, 3) including the capture
site in the resight sampling frame when possible, and 4) reporting survival as
apparent survival if fixed sites are used for resight with the single state
JLRLR model.
