Figure 1. Two separate SSMs were set up, one for females and the other for males. The models were applied to all encounter histories of females and males, including those with zero and multiple lover-changes. For clarity, the model diagram is divided in two panels. In (a), we represent the transitions of the ‘old’ states and the first year ‘new’ states. In (b), we depict the transitions of the ‘new’ states, which revert to ‘old’ after the third breeding attempt (see below and §2d in the main text). The states are: successful (SDated) or failed (FDated) birds breeding with the old mate; successful (SNew) or failed (FBrand new) individuals breeding with a new mate, where a relationship is defined as ‘new’ for the first 3 years (S/Fnew1, S/Fnew2, S/Fnew3), after which the individuals automatically transition to the ‘old’ states; non-breeding (NonB), if they skipped breeding and their partner was alive; widowed (Wid), if their previous mate died and they did not breed with a new one. In both panels, the same names are used for the same states-i.e. NonB in (b) is the same state as in (a). The different colours are used to represent successful and failed breeders (both with an old and a new mate), non breeders and widowed. The transition probabilities between states (?), shown in the equation boxes at the bottom of (a), are driven by state-specific parameters. The complete set of state-specific parameters, determining the transitions between states, were: probability of retaining the previous mate (breed); probability of breeding after mate-change (breedButton); breeding success with the first mate (succDated) or with subsequent mates (succThe); individual survival (fa); partner survival (fmate). In the equation boxes, the breed parameters for the different states are represented using bold underlined text to highlight that, within the model formulation, the environmental effects on the state-specific breed parameters were quantified using logistic regression. (Online version in colour.)
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Within both men and women SSM preparations, to analyze environmentally friendly motorists out-of divorce, we utilized univariate logistic regression to investigate the consequences of SSTA and you may Cinch into probability of preserving the earlier partner (breed). The significance of the newest covariates was examined having fun with inclusion probability variables w (electronic additional material).
As described above, this SSM was used to analyse the encounter histories of all individuals in our colonies, also including those that never changed mate. This was advantageous for the retrieval of unbiased ‘breed’ and ‘breedKey‘ parameters. However, the breeding success parameters estimated in this model were not conditional on mate-change having occurred. Moreover, owing to model convergence issues, it was not possible to specify different breeding success parameters for birds that changed mate owing to divorce and owing to widowing. Therefore, separately for females and males, we designed a second SSM (electronic supplementary material) to quantify the breeding success before and after mate-change, using different parameters for birds that changed mate owing to divorce and widowing. To ensure that the estimated breeding success rates were conditional on mate-change having occurred and in order to simplify the model formulation and reach model convergence, we retained in the analysis only those individuals that changed mate once owing to widowing or divorce.
(e) Condition area design implementation
The fresh SSM investigation was performed in the JAGS app executed owing to Roentgen via the R2JAGS bundle . The latest ple regarding the posterior distribution each and every SSM factor. For everybody patterns, i produced about three chains of at least 31 100 iterations Rate My Date dating sites. I made sure that chains was well-mixed and that the brand new Gelman–Rubin diagnostic overlap fact is actually below step one.02 for everyone variables.