Genetic variation in dispersal ability may result in the spatial sorting of alleles during range expansion. Recent theory suggests that spatial sorting can favour the rapid evolution of life history traits at expanding fronts, and therefore modify the ecological dynamics of range expansion. Here we test this prediction by disrupting spatial sorting in replicated invasions of the bean beetle Callosobruchus maculatus across homogeneous experimental landscapes. We show that spatial sorting promotes rapid evolution of dispersal distance, which increases the speed and variability of replicated invasions: after 10 generations of range expansion, invasions subject to spatial sorting spread 8.9% farther and exhibit 41-fold more variable spread dynamics relative to invasions in which spatial sorting is suppressed. Correspondingly, descendants from spatially evolving invasions exhibit greater mean and variance in dispersal distance. Our results reveal an important role for rapid evolution during invasion, even in the absence of environmental filters, and argue for evolutionarily informed forecasts of invasive spread by exotic species or climate change migration by native species.

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.

Understanding the influence of environmental variability on population dynamics is a fundamental goal of ecology. Theory suggests that, for populations in variable environments, temporal correlations between demographic vital rates (e.g., growth, survival, reproduction) can increase (if positive) or decrease (if negative) the variability of year-to-year population growth. Because this variability generally decreases long-term population viability, vital rate correlations may importantly affect population dynamics in stochastic environments. Despite long-standing theoretical interest, it is unclear whether vital rate correlations are common in nature, whether their directions are predominantly negative or positive, and whether they are of sufficient magnitude to warrant broad consideration in studies of stochastic population dynamics. We used long-term demographic data for three perennial plant species, hierarchical Bayesian parameterization of population projection models, and stochastic simulations to address the following questions: (1) What are the sign, magnitude, and uncertainty of temporal correlations between vital rates? (2) How do specific pairwise correlations affect the year-toyear variability of population growth? (3) Does the net effect of all vital rate correlations increase or decrease year-to-year variability? (4) What is the net effect of vital rate correlations on the long-term stochastic population growth rate (λ s )? We found only four moderate to strong correlations, both positive and negative in sign, across all species and vital rate pairs; otherwise, correlations were generally weak in magnitude and variable in sign. The net effect of vital rate correlations ranged from a slight decrease to an increase in the year-to-year variability of population growth, with average changes in variance ranging from −1% to +22%. However, vital rate correlations caused virtually no change in the estimates of λ s (mean effects ranging from −0.01% to +0.17%). Therefore, the proportional changes in the variance of population growth caused by demographic correlations were too small on an absolute scale to importantly affect population growth and viability. We conclude that, in our three focal populations and perhaps more generally, vital rate correlations have little effect on stochastic population dynamics. This may be good news for population ecologists, because estimating vital rate correlations and incorporating them into population models can be data intensive and technically challenging.

Summary 1.One of the key components of an organism's life history is the delay of reproduction until it reaches or returns to an optimal size. While we know climate can influence vital rates that shape life-history strategies, it is also critical to understand the effects of climate change on rapid life history evolution, which might modify the influence of climate change on population dynamics. 2. We asked how realistic changes in temperature and precipitation influence vital rates, costs of reproduction, and ultimately, evolutionarily stable (ES) flowering size in a long-lived perennial plant, Orchis purpurea. We also explored how evolution of flowering size could influence population persistence under changing climate. 3. Our approach combined model selection methods to characterize climate dependence in vital rates, stochastic integral projection models to integrate vital rates into an estimate of fitness, and adaptive dynamics to identify ES flowering sizes. 4. Vital rates responded uniquely to seasonal temperature and precipitation, with the largest response in the size-dependent probability of flowering. The predicted ES flowering size closely matched that observed, and responded strongly to adjusting the frequencies of extreme climate years. For example, increasing the frequency of extreme drought conditions was predicted to favour smaller reproductive sizes (and hence a shorter reproductive delay), despite observation that smaller plants were less likely to flower in dry years. This apparent discrepancy stems from a smaller payoff to delaying reproduction due to lower costs of reproduction in dry years. 5. The model of stochastic population dynamics predicted long-term persistence of the focal populations, even under the most extreme climate scenarios, while incorporating rapid life history evolution into predictions reduced the sensitivity of population growth to changing climate. 6. Synthesis. Our results illustrate that long-lived organisms can exhibit complex demographic responses to changing climate regimes. Additionally, they highlight that long-term evolutionary responses may be in opposing directions from short-term plastic responses to climate and emphasize the need for demographic models to integrate ecological and evolutionary influences of climate across the life cycle.

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