Inferring seed bank from hidden Markov models: new insights into metapopulation dynamics in plants



  1. Capturing metapopulation dynamics of plants that have seed banks is challenging, because of the difficulty in characterizing the seed bank in the field.
  2. To account for the presence of a seed bank, we developed a hidden Markov model, where the focus species can be present in two forms, both above-ground and below-ground, the latter being unobservable. We generated patch histories of presence–absence for a species with a one-year seed bank under different colonization–extinction dynamics and metapopulation sizes, using a mechanistic model that accounts for three different sources of seedlings (seed bank, newly locally produced seeds and migrant seeds) as well as a disturbance process reflecting extinction. Using the program e-surge, we analysed these simulated data to evaluate the statistical performance of the hidden Markov model in detecting the presence of a seed bank and providing accurate estimates of the model parameters for different sets of parameter values.
  3. Our simulation tests showed that the absence of a seed bank was very well detected when data sets were simulated with no seed bank, regardless the size of the metapopulation. Similarly, the presence of a seed bank was well detected when data sets were simulated with a seed bank. In this latter case, detection of the seed bank improved with increasing size of the metapopulation.
  4. The quality of the estimates of the model parameters increased with the size of the metapopulation but still remained high for small metapopulation sizes. The two parameters reflecting the colonization process and seed dormancy were those best estimated. In addition, we showed that ignoring the presence of a seed bank unvaryingly led to overestimations of colonization and extinction rates.
  5. Synthesis. Hidden Markov models offer a reliable way to estimate colonization and extinction rates for plant metapopulations with a seed bank using time series of presence–absence data. Therefore, these models have the potential to provide valuable insights into the metapopulation dynamics of many plant and animal species with an unobservable life form that have remained poorly studied because of methodological constraints.