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

Summary1. Capturing metapopulation dynamics of plants that have seed banks is challenging, because of thedifficulty 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 thefocus species can be present in two forms, both above-ground and below-ground, the latter beingunobservable. We generated patch histories of presence–absence for a species with a one-year seedbank under different colonization–extinction dynamics and metapopulation sizes, using a mechanisticmodel that accounts for three different sources of seedlings (seed bank, newly locally producedseeds 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 hiddenMarkov model in detecting the presence of a seed bank and providing accurate estimates of themodel parameters for different sets of parameter values.3. Our simulation tests showed that the absence of a seed bank was very well detected when datasets were simulated with no seed bank, regardless the size of the metapopulation. Similarly, thepresence of a seed bank was well detected when data sets were simulated with a seed bank. In thislatter 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 metapopula-tion but still remained high for small metapopulation sizes. The two parameters reflecting the coloni-zation process and seed dormancy were those best estimated. In addition, we showed that ignoringthe 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 extinctionrates for plant metapopulations with a seed bank using time series of presence–absence data. There-fore, these models have the potential to provide valuable insights into the metapopulation dynamicsof many plant and animal species with an unobservable life form that have remained poorly studiedbecause of methodological constraints.Key-words: colonization, E-Surge, extinction, hidden Markov model, metapopulation dynamics,multievent model, patch occupancy, plant metapopulation, plant population and community dynamics,seed bankIntroduction

[1]  J. Bakker,et al.  The Soil Seed Banks of North West Europe: Methodology, Density and Longevity , 1996 .

[2]  A. Garnier,et al.  Estimation of Plant Demographic Parameters from Stage‐Structured Censuses , 2010, Biometrics.

[3]  R. Freckleton,et al.  Large‐scale spatial dynamics of plants: metapopulations, regional ensembles and patchy populations , 2002 .

[4]  J Andrew Royle,et al.  Site Occupancy Models with Heterogeneous Detection Probabilities , 2006, Biometrics.

[5]  J. Harper Population Biology of Plants , 1979 .

[6]  Nicholas J. Gotelli,et al.  Metapopulation Models: The Rescue Effect, the Propagule Rain, and the Core-Satellite Hypothesis , 1991, The American Naturalist.

[7]  P. Lesica Autecology of the Endangered Plant Howellia Aquatilis; Implications for Management and Reserve Design. , 1992, Ecological applications : a publication of the Ecological Society of America.

[8]  I. Olivieri,et al.  Evolutionarily Stable Dispersal Rates Do Not Always Increase with Local Extinction Rates , 2000, The American Naturalist.

[9]  P. Cheptou,et al.  Colonization and extinction dynamics of an annual plant metapopulation in an urban environment , 2011 .

[10]  D. L. Venable Bet hedging in a guild of desert annuals. , 2007, Ecology.

[11]  F. Rousset,et al.  THE JOINT EVOLUTION OF DISPERSAL AND DORMANCY IN A METAPOPULATION WITH LOCAL EXTINCTIONS AND KIN COMPETITION , 2013, Evolution; international journal of organic evolution.

[12]  J. Andrew Royle,et al.  A Bayesian state-space formulation of dynamic occupancy models. , 2007, Ecology.

[13]  B. Husband,et al.  A METAPOPULATION PERSPECTIVE IN PLANT POPULATION BIOLOGY , 1996 .

[14]  W. Stephan,et al.  Inference of seed bank parameters in two wild tomato species using ecological and genetic data , 2011, Proceedings of the National Academy of Sciences.

[15]  Darryl I. MacKenzie,et al.  Designing occupancy studies: general advice and allocating survey effort , 2005 .

[16]  R Choquet,et al.  A hybrid symbolic-numerical method for determining model structure. , 2012, Mathematical biosciences.

[17]  Determinants of extinction in fragmented plant populations: Crepis sancta (asteraceae) in urban environments , 2012, Oecologia.

[18]  R. Ferrière,et al.  Bet Hedging via Seed Banking in Desert Evening Primroses (Oenothera, Onagraceae): Demographic Evidence from Natural Populations , 2006, The American Naturalist.

[19]  O. Eriksson,et al.  Toward a Metapopulation Concept for Plants , 2004 .

[20]  K. Tielbörger,et al.  Bet-hedging germination in annual plants: a sound empirical test of the theoretical foundations , 2012 .

[21]  Robin E. Snyder Multiple risk reduction mechanisms: can dormancy substitute for dispersal? , 2006, Ecology letters.

[22]  O. Eriksson,et al.  Large‐scale spatial dynamics of plants: a response to Freckleton & Watkinson , 2003 .

[23]  M. Gilpin,et al.  Metapopulation Biology: Ecology, Genetics, and Evolution , 1997 .

[24]  P. Poschlod,et al.  The seed bank longevity index revisited: limited reliability evident from a burial experiment and database analyses. , 2009, Annals of botany.

[25]  David R. Anderson,et al.  Model selection and inference : a practical information-theoretic approach , 2000 .

[26]  K. Tielbörger,et al.  Dispersal-Dormancy Relationships in Annual Plants: Putting Model Predictions to the Test , 2010, The American Naturalist.

[27]  R. Levins Some Demographic and Genetic Consequences of Environmental Heterogeneity for Biological Control , 1969 .

[28]  Darryl I MacKenzie,et al.  Modeling species occurrence dynamics with multiple states and imperfect detection. , 2009, Ecology.

[29]  R. Freckleton,et al.  Are all plant populations metapopulations? , 2003 .

[30]  Roger Pradel,et al.  Program E-Surge: A Software Application for Fitting Multievent Models , 2009 .

[31]  Roger Pradel,et al.  Multievent: An Extension of Multistate Capture–Recapture Models to Uncertain States , 2005, Biometrics.

[32]  SCOTT A. FIELD,et al.  OPTIMIZING ALLOCATION OF MONITORING EFFORT UNDER ECONOMIC AND OBSERVATIONAL CONSTRAINTS , 2005 .

[33]  C. Baskin,et al.  Seeds: Ecology, Biogeography, and, Evolution of Dormancy and Germination , 1998 .

[34]  Atte Moilanen,et al.  SPOMSIM: software for stochastic patch occupancy models of metapopulation dynamics , 2004 .

[35]  D. Cohen Optimizing reproduction in a randomly varying environment. , 1966, Journal of theoretical biology.

[36]  J. Dennehy,et al.  GERM BANKING: BET‐HEDGING AND VARIABLE RELEASE FROM EGG AND SEED DORMANCY , 2005, The Quarterly Review of Biology.

[37]  C.J.F. ter Braak,et al.  Application of Stochastic Patch Occupancy Models to Real Metapopulations , 2004 .

[38]  J. Nichols,et al.  ESTIMATING SITE OCCUPANCY, COLONIZATION, AND LOCAL EXTINCTION WHEN A SPECIES IS DETECTED IMPERFECTLY , 2003 .

[39]  Joel s. Brown,et al.  The Selective Interactions of Dispersal, Dormancy, and Seed Size as Adaptations for Reducing Risk in Variable Environments , 1988, The American Naturalist.

[40]  Olivier Gimenez,et al.  Metapopulation Dynamics of Species with Cryptic Life Stages , 2013, The American Naturalist.