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    Description

    Population viability analysis (PVA) is a valuable tool for rare plant conservation, but PVA for plants with persistent seed banks is difficult without reliable information on seed bank processes. We modeled the population dynamics of the Snake River Plains ephemeral Lepidium papilliferum using data from an 11-yr artificial seed bank experiment to estimate age-specific vital rates for viability loss and germination. We related variation in postgermination demographic parameters to annual variation in precipitation patterns and used these relationships to construct a stochastic population model using precipitation driver variables. This enabled us to incorporate realistic levels of environmental variability into the model. A model incorporating best estimates for parameter values resulted in a mean trajectory for seed bank size that remained essentially stable through time, although there was a measurable risk of extinction over a 100-yr period for the study population under this scenario. Doubling the annual seed viability loss rate resulted in near-certain extinction, as did increasing first-year germination to 100%, showing the importance of the persistent seed bank. Interestingly, increasing environmental variance substantially decreased the risk of extinction, presumably because this plant relies on extremely good years to restock the persistent seed bank, while extremely bad years have little impact. If every year were average in this desert environment, the species could not persist. Simulated effects of livestock trampling resulted in greatly increased extinction risk, even over time frames as short as 15 years.

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    Citation

    Meyer, Susan E.; Quinney, Dana; Weaver, Jay. 2006. A stochastic population model for Lepidium papilliferum (Brassicaceae), a rare desert ephemeral with a persistent seed bank. American Journal of Botany. 93(6): 891-902.

    Keywords

    demography, endangered species, Jensen's inequality, population viability analysis, seed bank, simulation, slick spot peppergrass, stochastic model

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https://www.fs.usda.gov/treesearch/pubs/39166