Matrix projection models are among the most widely used tools in plant ecology. However, the way in which plant ecologists use and interpret these models differs from the way in which they are presented in the broader academic literature. In contrast to calls from earlier reviews, most studies of plant populations are based on < 5 matrices and present simple metrics such as deterministic population growth rates. However, plant ecologists also cautioned against literal interpretation of model predictions. Although academic studies have emphasized testing quantitative model predictions, such forecasts are not the way in which plant ecologists find matrix models to be most useful. Improving forecasting ability would necessitate increased model complexity and longer studies. Therefore, in addition to longer term studies with better links to environmental drivers, priorities for research include critically evaluating relative ⁄ comparative uses of matrix models and asking how we can use many short-term studies to understand long-term population dynamics.

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Uncertainty associated with ecological forecasts has long been recognized, but forecast accuracy is rarely quantified. We evaluated how well data on 82 populations of 20 species of plants spanning 3 continents explained and predicted plant population dynamics. We parameterized stage-based matrix models with demographic data from individually marked plants and determined how well these models forecast population sizes observed at least 5 years into the future. Simple demographic models forecasted population dynamics poorly; only 40% of observed population sizes fell within our forecasts' 95% confidence limits. However, these models explained population dynamics during the years in which data were collected; observed changes in population size during the data-collection period were strongly positively correlated with population growth rate. Thus, these models are at least a sound way to quantify population status. Poor forecasts were not associated with the number of individual plants or years of data. We tested whether vital rates were density dependent and found both positive and negative density dependence. However, density dependence was not associated with forecast error. Forecast error was significantly associated with environmental differences between the data collection and forecast periods. To forecast population fates, more detailed models, such as those that project how environments are likely to change and how these changes will affect population dynamics, may be needed. Such detailed models are not always feasible. Thus, it may be wiser to make risk-averse decisions than to expect precise forecasts from models.

Restoration is an important tool for reducing extinction risk of endangered plants. Population viabilities of few plant restorations have been modeled over decadal time periods and linked with genetic and ecological factors that drive restoration processes. We modeled viability of restored populations of Mead's milkweed (Asclepias meadii, Asclepiadaceae), a self‐incompatible perennial herb of eastern tallgrass prairie (TGP), federally listed as threatened in the U.S. From 1994 to 2004, we planted >600 seeds and >800 juvenile plants representing >50 genotypes across seven TGP sites. Propagule type, genotype, seed source, restoration site, precipitation and fire management significantly affected establishment, growth and viability. Plants established from seed had greater mortality and greater genetic and demographic attrition than did juveniles. Seedling growth rates also projected 20–30 yrs to reach flowering stage, and their survivorship provided a metric of site suitability for life cycle completion. Seed germination and juvenile plant size were greater in burned habitat, and juvenile size was also positively correlated with spring precipitation. Seed production required presence of multiple genotypes among flowering plants. Seedlings demonstrated a heterosis effect, with greater germination among seeds derived from inter‐population crosses. However, cumulative growth of planted juveniles as well as population growth (λ) on sub‐optimal habitat conditions tended to be lower for propagules derived from inter‐population crosses, demonstrating outbreeding depression. Although flowering occurred at multiple sites, positive population growth (λ > 1) occurred at only a single site, where increasing fire frequency decreased extinction probability. These results suggest that restoration of viable Mead's milkweed populations is possible in optimal habitat. However, restoration of this species is constrained by high demographic attrition and the long period (20 or more yrs) required to complete its life cycle. Crossing among populations to increase genetic diversity and compatible mating types may result in tradeoffs, with heterosis at early life history stages, but outbreeding depression expressed in older stages. Fire and precipitation are also critical interactive processes driving A. meadii growth and reproduction. They may be most effective when precipitation, a stochastic process, results in greater than average post‐burn rainfall. These constraints may have implications for restoration of other late‐successional plant species.