2.4 Multistate mark-recapture models
To estimate the probabilities of survival (Φ), encounter (or
recapture, ρ) , and transition (ψ ) between states (breeder,
non-breeder, and prebreeder), multistate mark-recapture models were
constructed using program MARK and the ‘RMark’ package in R (White &
Burnham 1999; Laake 2013). Within these models, a group effect for
colony (Robben Island and Stony Point) was included to evaluate colony
differences in the estimates. Known parameters were fixed to improve
model performance; since only breeders were marked in 2013 across both
colonies (with nonbreeders marked in subsequent years, Table A1),
survival and transition rates for nonbreeders and prebreeders were fixed
to zero during 2013–14, as was recapture in 2014 in both colonies.
Additionally, no nonbreeders were marked in 2014 at Robben Island, so
prebreeder survival and transition during 2014–15, and prebreeder
recapture in 2015 were also fixed to zero for this colony.
Initially, a general model was developed assuming time, state, and
colony dependence for survival, recapture, and transition probabilities.
Simpler model structures were also tested for recapture whereby years
were pooled into two groups to represent before and after ground readers
were installed in each colony. For survival and transition, simpler
models were also included whereby time dependence was replaced with both
combined and separated annual sardine and anchovy spawner biomass WoCA
to determine whether fish abundance offered better predictive power for
survival and transition probabilities than the fully time-dependent
model.
Recapture probabilities were modelled first, with the best fitting model
taken forward to assess survival probabilities, followed by transition.
Model selection was based on Akaike’s Information Criterion corrected
for over-dispersion and small sample size (QAICc) (Lebreton et
al. 1992). When models differed by QAICc <2, they were
considered approximately equivalent (Burnham & Anderson 2002), and the
model with the lowest number of parameters was considered the most
parsimonious. Goodness-of-fit (GOF) tests for the general model (JMV
model; Pradel et al. 2003) were performed using package ‘R2ucare’
(Gimenez et al. 2018) in Program R.