Summary 1.Exotic invasive plants can have strong effects on native communities. Centaurea maculosa , a forb that is native to Eurasia, has created near-monocultures in many parts of its invaded range in western North America and produces the root exudate (±)-catechin. Controlled laboratory experiments suggest that the phytotoxic effects of (±)-catechin may be stronger on some North American species than on some European species. 2. We conducted experiments in the field in two different years in the native (Romania) and invaded (MT, USA) ranges of C. maculosa , testing the effects of (±)-catechin on species that co-occur with C. maculosa in both ranges. 3. (±)-Catechin reduced the growth of native plant species in Montana in both years, although there was some variability between species in the effect of (±)-catechin on leaf growth in 2005. There was no effect of (±)-catechin on plants in Romania. 4. This first in situ test of the novel weapons hypothesis supports the notion that novel biochemical constituents of some invasive species may contribute to their success. 5. Synthesis . In addition to providing information useful for understanding invasions, our results indicate that some species in the native range of C. maculosa may be adapted to its particular biochemical traits, raising the possibility that interactions among plant species may be affected by a common evolutionary history.

Summary 1.Interactions among plants and their consumers, pollinators and dispersers are central to evolutionary theory, but interactions among plants themselves have received much less attention. Thus focusing more attention on the evolutionary role of plant-plant interactions may provide greater insight into the processes that organize communities. 2. Here, we integrate divergent themes in the literature in an effort to provide a synthesis of empirical evidence and ideas about how plant interactions may affect evolution and how evolution may affect plant interactions. 3. First, we discuss the idea of niche partitioning evolving through competitive interactions among plants, the idea of niche construction evolving through facilitative interactions, and the connections between these ideas and more recent research on diversity and ecosystem function and trait-based community organization. 4. We then review how a history of coexistence within a region might affect competitive outcomes and explore the mechanisms by which plants exert selective forces on each other. Next, we consider recent research on invasions suggesting that plant interactions can reflect regional evolutionary trajectories. Finally, we place these lines of research into the context of extended phenotypes and the geographic mosaic of co-evolution. 5. Synthesis. Our synthesis of separate lines of inquiry is a step towards understanding the evolutionary importance of interactions among plants, and suggests that the evolutionary consequences of interactions contribute to communities that are more than assemblages of independent populations.

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.

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