Significance Plants have evolved diverse life history strategies to succeed in Earth’s varied environments. Some species grow quickly, produce copious seeds, and die within a few weeks. Other species grow slowly and rarely produce seeds but live thousands of years. We show that simple morphological measurements can predict where a species falls within the global range of life history strategies: species with large seeds, long-lived leaves, or dense wood have population growth rates influenced primarily by survival, whereas individual growth and fecundity have a stronger influence on the dynamics of species with small seeds, short-lived leaves, or soft wood. This finding increases the ability of scientists to represent complex population processes with a few easily measured character traits.

Summary 1.A wealth of population genetic studies have documented that many successful biological invasions stem from multiple introductions from genetically distinct source populations. Yet, mechanistic understanding of whether and how genetic mixture promotes invasiveness has lagged behind documentation that such mixture commonly occurs. We conducted a laboratory experiment to test the influence of genetic mixture on the velocity of invasive range expansion. 2. The mechanistic basis for effects of genetic mixture could include evolutionary responses (mixed invasions may harbour greater genetic diversity and thus elevated evolutionary potential) and/or fitness advantages of between-population mating (heterosis). If driven by evolution, positive effects of source population mixture should increase through time, as selection sculpts genetic variation. If driven by heterosis, effects of mixture should peak following first reproductive contact and then dissipate. 3. Using a laboratory model system (beetles spreading through artificial landscapes), we quantified the velocity of range expansion for invasions initiated with one, two, four or six genetic sources over six generations. Our experiment was designed to test predictions corresponding to the evolutionary and heterosis mechanisms, asking whether any effects of genetic mixture occurred in early or later generations of range expansion. We also quantified demography and dispersal for each experimental treatment, since any effects of mixture should be manifest in one or both of these traits. 4. Over six generations, invasions with any amount of genetic mixture (two, four and six sources) spread farther than single-source invasions. Our data suggest that heterosis provided a 'catapult effect', leaving a lasting signature on range expansion even though the benefits of outcrossing were transient. Individual-level trait data indicated that genetic mixture had positive effects on local demography (reduced extinction risk and enhanced population growth) during the initial stages of invasion but no consistent effects on dispersal ability. 5. Our work is the first to demonstrate that genetic mixture can alter the course of spatial expansion, the stage of invasion typically associated with the greatest ecological and economic impacts. We suggest that similar effects of genetic mixture may be a common feature of biological invasions in nature, but that these effects can easily go undetected.

Despite a global footprint of shifts in flowering phenology in response to climate change, the reproductive consequences of these shifts are poorly understood. Furthermore, it is unknown whether altered flowering times affect plant population viability. We examine whether climate change‐induced earlier flowering has consequences for population persistence by incorporating reproductive losses from frost damage (a risk of early flowering) into population models of a subalpine sunflower (Helianthella quinquenervis). Using long‐term demographic data for three populations that span the species’ elevation range (8–15 years, depending on the population), we first examine how snowmelt date affects plant vital rates. To verify vital rate responses to snowmelt date experimentally, we manipulate snowmelt date with a snow removal experiment at one population. Finally, we construct stochastic population projection models and Life Table Response Experiments for each population. We find that populations decline (λs < 1) as snowmelt dates become earlier. Frost damage to flower buds, a consequence of climate change‐induced earlier flowering, does not contribute strongly to population declines. Instead, we find evidence that negative effects on survival, likely due to increased drought risk during longer growing seasons, drive projected population declines under earlier snowmelt dates. Synthesis. Shifts in flowering phenology are a conspicuous and important aspect of biological responses to climate change, but here we show that the phenology of reproductive events can be unreliable measures of threats to population persistence, even when earlier flowering is associated with substantial reproductive losses. Evidence for shifts in reproductive phenology, along with scarcer evidence that these shifts actually influence reproductive success, are valuable but can paint an incomplete and even misleading picture of plant population responses to climate change.

There is an urgent need to synthesize the state of our knowledge on plant responses to climate. The availability of open-access data provide opportunities to examine quantitative generalizations regarding which biomes and species are most responsive to climate drivers. Here, we synthesize time series of structured population models from 162 populations of 62 plants, mostly herbaceous species from temperate biomes, to link plant population growth rates (λ) to precipitation and temperature drivers. We expect: (1) more pronounced demographic responses to precipitation than temperature, especially in arid biomes; and (2) a higher climate sensitivity in short-lived rather than long-lived species. We find that precipitation anomalies have a nearly three-fold larger effect on λ than temperature. Species with shorter generation time have much stronger absolute responses to climate anomalies. We conclude that key species-level traits can predict plant population responses to climate, and discuss the relevance of this generalization for conservation planning.