Since first proposed by Levins (1969), the metapopulation concept has triggered many developments in evolutionary biology (Ronce, Perret & Olivieri 2000) and ecology (Hanski & Gilpin 1997; Hanski 1999). The metapopulation framework considers that species distribution over space and time results from a balance between extinction of local populations inhabiting a discrete network of suitable patches and colonization of empty patches. While such a framework has been extremely influential in the study of animal species, its relevance for studying plant species has been much more controversial (Bullock et al. 2002; Freckleton & Watkinson 2002, 2003; Ehrlén & Eriksson 2003). On the one hand, Husband & Barrett (1996) argued that the patchy structure of plant populations, as well as their supposedly high turnover, made them ideal candidates for metapopulation studies. On the other hand, Freckleton & Watkinson (2002) argued that specific plant characteristics could make the metapopulation model inadequate for capturing the regional dynamics of many plant species. Among these characteristics is the seed bank, which is a prevalent trait of plant species (Harper 1977; Thompson, Bakker & Bekker 1997) and that is known to have a major impact on regional dynamics. Indeed, by spreading seed germination and reproduction through time, prolonged seed dormancy that builds up the seed bank (Harper 1977) can represent a bet-hedging strategy that allows species to reduce temporal variation in fitness in unpredictably varying environments and thus mitigate the effects of unfavourable years (Cohen 1966; Evans et al. 2007; Venable 2007). Seed bank effects on regional dynamics may, however, not be captured when considering only colonization and extinction processes (Freckleton & Watkinson 2002; Ouborg & Eriksson 2004). Therefore, metapopulation dynamics of species possessing a seed bank have been poorly documented in the field because of the difficulty in characterizing the seed bank. The few empirical metapopulation studies conducted in plants either have ignored the potential effect of a documented seed bank on metapopulation persistence (Lesica 1992; see a review in Freckleton & Watkinson 2002) or have been developed for species with no seed bank (Dornier, Pons & Cheptou 2011). The specific problem associated with a seed bank is that species cannot be detected when present only below-ground. Consequently, such missing information makes it unclear whether a newly observed population is derived from colonization or from the germination of the seed bank. Similarly, it is not clear whether a previously occupied habitat corresponds to an extinction process or whether there are still some individuals left in the seed bank. Therefore, estimates of colonization and extinction probabilities are necessarily biased whenever prolonged seed dormancy is ignored for species with a seed bank.
In a monitoring context, field ecologists are able to obtain long-term presence–absence data from patch surveys above-ground. Such data sets have recently stimulated a large amount of work on the issue of imperfect detection (e.g. MacKenzie et al. 2003; Royle 2006; Royle & Kery 2007; and references therein). Repeated surveys within a season can be used to compensate for imperfect detection (MacKenzie et al. 2009). However, they do not help detect the presence of a seed bank, making standard patch occupancy models inappropriate. Patch occupancy surveys only allow occupancy to be assigned to the above-ground state, and thus present uncertainty for patch occupancy below-ground. The question remains whether such occupancy data above-ground can provide information about the presence of the species below-ground through the existence of a seed bank. Hidden Markov models, such as multievent models (Pradel 2005) and patch occupancy models (MacKenzie et al. 2009), decouple the observation process and the state process and thus enable to take into account the uncertainty in the assignment of state. In the context of plant metapopulations with a seed bank, the observation corresponds to the presence or absence of the species above-ground, and the states correspond to the combination of the presence or absence of the species above-ground and below-ground.
In this study, we highlight how hidden Markov models can be used to address the longstanding problem of unobservable stages in the life cycle, a problem that has hampered empirical studies of plant metapopulations. To do so, we performed stochastic simulations using a mechanistic model to generate patch histories of presence–absence for a species with a one-year seed bank, utilizing different colonization–extinction dynamics and metapopulation sizes. Using the program e-surge (Choquet, Rouan & Pradel 2009), we analysed these simulated data to evaluate the statistical performance of our model in (i) detecting the presence of a seed bank and (ii) providing accurate estimates of the model parameters for different sets of parameter values.