A multievent approach to estimating pair fidelity and heterogeneity in state transitions

Abstract

Fidelity rates of pair-bonded individuals are of considerable interest to behavioral and population biologists as they can influence population structure, mating rates, population productivity, and gene flow. Estimates of fidelity rates calculated from direct observations of pairs in consecutive breeding seasons may be biased because (i) individuals that are not seen are assumed to be dead, (ii) variation in the detectability of individuals is ignored, and (iii) pair status must be known with certainty. This can lead to a high proportion of observations being ignored. This approach also restricts the way variation in fidelity rates for different types of individuals, or the covariation between fidelity and other vital rates (e.g., survival) can be analyzed. In this study, we develop a probabilistic multievent capture–mark–recapture (MECMR) modeling framework for estimating pair fidelity rates that accounts for imperfect detection rates and capture heterogeneity, explicitly incorporates uncertainty in the assessment of pair status, and allows estimates of state-dependent survival and fidelity rates to be obtained simultaneously. We demonstrate the utility of our approach for investigating patterns of fidelity in pair-bonded individuals, by applying it to 30 years of breeding data from a wild population of great tits Parus major Linnaeus. Results of model selection supported state-dependent recapture, survival, and fidelity rates. Recapture rates were higher for individuals breeding with their previous partner than for those breeding with a different partner. Faithful birds that were breeding with the same partner as in the previous breeding season (i.e., at t − 1) experienced substantially higher survival rates (between t and t + 1) and were also more likely to remain faithful to their current partner (i.e., to remain in the faithful state at t + 1). First year breeders were more likely to change partner than older birds. These findings imply that traditional estimates, which do not account for state-dependent parameters, may be both inaccurate and biased, and hence, inferences based on them may conceal important biological effects. This was demonstrated in the analysis of simulated capture histories, which showed that our MECMR model was able to estimate state-dependant survival and pair fidelity rates in the face of varying state-dependant recapture rates robustly, and more accurately, than the traditional method. In addition, this new modeling approach provides a statistically rigorous framework for testing hypothesis about the causes and consequences of fidelity to a partner for natural populations. The novel modeling approach described here can readily be applied, either in its current form or via extension, to other populations and other types of dyadic interactions (e.g., between nonpaired individuals, such as parent–offspring relationships, or between individuals and locations, such as nest-site fidelity).

Social status mediates the fitness costs of infection with canine distemper virus in Serengeti spotted hyenas

“…It is often recommended to parameterize the observation process (here: detection and assignment), before the biological one (e.g. Culina, Lachish, Pradel, Choquet, & Sheldon, ). Starting with a constant‐only model, we sequentially parameterized the: (1) assignment of infection states, (2) detection, (3) survival, (4) infection, (5) social transitions and (6) breeding transitions, testing for effects of social, demographic and infection states on those processes.…”

Survival costs of within‐ and between‐season mate change in the European blackbirdTurdus merula

“…We believe that the survival costs of changing partners may be profound within and between seasons, but all the work done so far in the context of survival has been on betweenseason mate fidelity (Nicolai et al 2012, Culina et al 2013, 2015b. To the best of our knowledge, this analysis is the first to additionally explore the problem of within-season faithfulness in terms of apparent survival costs related to the costs of reproduction.…”

“…A series of conditional probabilities allows each event to be related to one or more states. Culina et al (2013) defines seven possible exclusive events which can be observed in the studied population as: 1) event 0 = the focal individual is not captured in the current breeding season (i.e. at t), its partner from the previous season (t -1) is either not captured at t -1 or t, or is captured breeding at t at an active nest with an unknown partner; 2) event 1 = the focal individual is captured at t and is breeding with its partner from t -1; 3) event 2 = the focal individual is captured at t but is breeding with a different partner to that from t -1; 4) event 3 = the focal individual is captured at t but it is not known whether its current partner, which is captured, is the same as the one from t -1; 5) event 4 = the focal individual is captured at t, its current partner is not captured, but its partner from t -1 is captured at t at a different nest (and hence is not breeding with the focal individual at t); 6) event 5 = the focal individual is captured at t, its current partner is not captured, and its partner from t -1 is either not captured at t or was not known at t -1; 7) event 6 = the focal individual is not captured at t (and hence its current partner is unknown), but its partner from t -1 is captured breeding with another individual at t.…”

Trading up: the fitness consequences of divorce in monogamous birds

“…Results of a few studies suggest that divorce (and other forms of partner change) might also negatively affect survival (Nicolai et al, 2012;Culina et al, 2013). Results of a few studies suggest that divorce (and other forms of partner change) might also negatively affect survival (Nicolai et al, 2012;Culina et al, 2013).…”