A non-targeted metabolomics approach to quantifying differences in root storage between fast- and slow-growing plants.

Life history theory posits that slower-growing species should invest proportionally more resources to storage, structural (e.g. stems) or defence traits than fast-growing species. Previously, we showed that the slower-growing monocarpic plants had lower mortality rates and higher bolting probabilities after two defoliation events. Here, we consider a mechanistic explanation, that the slower-growing species invested relatively more resources to storage. We compared the relative levels of root storage compounds between eight monocarpic species using metabolomic profiling, and characterized plant growth using a size-corrected estimate of relative growth rate (RGR). Growth rate was negatively correlated with the proportional allocation of root metabolites identified as sucrose, raffinose and stachyose and with amino acids known for their roles in nitrogen storage, particularly proline and arginine. The total amount and concentration of energy-corrected carbohydrates were also negatively correlated with RGR. Our results show for the first time that slower-growing species invest proportionally more of their total root metabolites in carbon- and nitrogen-storage compounds. We conclude that the increased investment in these reserves is an important resource allocation strategy underlying the growth-survival trade-off in plants.

Plant growth rates and seed size: a re-evaluation.

Small-seeded plant species are often reported to have high relative growth rate or RGR. However, because RGR declines as plants grow larger, small-seeded species could achieve higher RGR simply by virtue of their small size. In contrast, size-standardized growth rate or SGR factors out these size effects. Differences in SGR can thus only be due to differences in morphology, allocation, or physiology. We used nonlinear regression to calculate SGR for comparison with RGR for 10 groups of species spanning a wide range of life forms. We found that RGR was negatively correlated with seed mass in nearly all groups, but the relationship between SGR and seed mass was highly variable. We conclude that small-seeded species only sometimes possess additional adaptations for rapid growth over and above their general size advantage.

Seed availability and insect herbivory limit recruitment and adult density of native tall thistle.

Understanding spatial and temporal variation in factors influencing plant regeneration is critical to predicting plant population growth. We experimentally evaluated seed limitation, insect herbivory, and their interaction in the regeneration and density of tall thistle (Cirsium altissimum) across a topographic ecosystem productivity gradient in tallgrass prairie over two years. On ridges and in valleys, we used a factorial experiment manipulating seed availability and insect herbivory to quantify effects of: seed input on seedling density, insect herbivory on juvenile density, and cumulative impacts of both seed input and herbivory on reproductive adult density. Seed addition increased seedling densities at three of five sites in 2006 and all five sites in 2007. Insect herbivory reduced seedling survival across all sites in both years, as well as rosette survival from the previous year's seedlings. In both years, insecticide treatment of seed addition plots led to greater adult tall thistle densities in the following year, reflecting the increase in juvenile thistle densities in the experimental year. Seedling survival was not density dependent. Our analytical projection model predicts a significant long-term increase in adult densities from seed input, with a greater increase under experimentally reduced insect herbivory. While plant community biomass and water stress varied significantly between ridges and valleys, the effects of seed addition and insect herbivory did not vary with gradient position. These results support conceptual models that predict seedling and adult densities of short-lived monocarpic perennial plants should be seed limited. Further, the experiment demonstrates that even at high juvenile plant densities, at which density dependence potentially could have overridden herbivore effects on plant survival, insect herbivory strongly affected juvenile thistle performance and adult densities of this native prairie species.

The costs and benefits of fast living.

Growth rates play a fundamental role in many areas of biology (Q. Rev. Biol., 67, 1992, 283; Life History Invariants. Some Explorations of Symmetry in Evolutionary Biology, 1993; Philos. Trans. R. Soc. Lond. B Biol. Sci., 351, 1996, 1341; Plant Strategies, Vegetation Processes, and Ecosystem Properties, 2002; Trends Ecol. Evol., 18, 2003, 471; Q. Rev. Biol., 78, 2003, 23; J. Ecol., 95, 2007, 926.) but the cost and benefits of different growth rates are notoriously difficult to quantify (Q. Rev. Biol., 72, 1997, 149; Funct. Ecol., 17, 2003, 328). This is because (1) growth rate typically declines with size and yet the most widely used growth measure - relative growth rate or RGR (conventionally measured as the log of the ratio of successive sizes divided by the time interval) - is not size-corrected and so confounds growth and size, (2) organisms have access to different amounts of resource and (3) it is essential to allow for the long-term benefits of larger size. Here we experimentally demonstrate delayed costs and benefits of rapid growth in seven plant species using a novel method to calculate size-corrected RGR. In control treatments, fast-growing plants benefited from increased reproduction the following year; however, fast-growing plants subjected to an experimental stress treatment (defoliation) showed strongly reduced survival and reproduction the following year. Importantly, when growth was estimated using the classical RGR measure, no costs or benefits were found. These results support the idea that life-history trade-offs have a dominant role in life-history and ecological theory and that the widespread failure to detect them is partly due to methodological shortcomings.

Seed dormancy and delayed flowering in monocarpic plants: selective interactions in a stochastic environment.

We explore the effects of temporal variation in multiple demographic rates on the joint evolution of delayed reproduction and seed dormancy using integral projection models (IPMs). To do this, we extend the standard IPM to include a discrete state variable representing the number of seeds in the seed bank, density-dependent recruitment, and temporal variation in demography. Parameter estimates for Carlina vulgaris and Carduus nutans are obtained from long-term studies. Carlina is relatively long lived and has a short-lived seed bank, whereas most Carduus plants flower in their first year and the seed bank is long lived. Using the evolutionarily stable strategy (ESS) approach, we predict the observed flowering and germination strategies. There is excellent agreement between the predictions and the field observations. The effects of temporal variation on the joint ESS are partitioned into components arising from nonlinear averaging (systematic changes in the mean resulting from the interaction between variability and nonlinearity) and nonequilibrium dynamics (fluctuations in fitness caused by temporal variation). This shows that temporal variation can have substantial effects on the observed flowering and germination strategies and that covariance between demographic processes is important. We extend the models to include spatial population structure and assess the robustness of the results from the nonspatial models.

Evolution of size-dependent flowering in a variable environment: partitioning the effects of fluctuating selection.

In a stochastic environment, two distinct processes, namely nonlinear averaging and non-equilibrium dynamics, influence fitness. We develop methods for decomposing the effects of temporal variation in demography into contributions from nonlinear averaging and non-equilibrium dynamics. We illustrate the approach using Carlina vulgaris, a monocarpic species in which recruitment, growth and survival all vary from year to year. In Carlina the absolute effect of temporal variation on the evolutionarily stable flowering strategy is substantial (ca. 50% of the evolutionarily stable flowering size) but the net effect is much smaller (ca. 10%) because the effects of temporal variation do not influence the evolutionarily stable strategy in the same direction.

Evolution of size-dependent flowering in a variable environment: construction and analysis of a stochastic integral projection model.

Understanding why individuals delay reproduction is a classic problem in evolutionary biology. In plants, the study of reproductive delays is complicated because growth and survival can be size and age dependent, individuals of the same size can grow by different amounts and there is temporal variation in the environment. We extend the recently developed integral projection approach to include size- and age-dependent demography and temporal variation. The technique is then applied to a long-term individually structured dataset for Carlina vulgaris, a monocarpic thistle. The parameterized model has excellent descriptive properties in terms of both the population size and the distributions of sizes within each age class. In Carlina, the probability of flowering depends on both plant size and age. We use the parameterized model to predict this relationship, using the evolutionarily stable strategy approach. Considering each year separately, we show that both the direction and the magnitude of selection on the flowering strategy vary from year to year. Provided the flowering strategy is constrained, so it cannot be a step function, the model accurately predicts the average size at flowering. Elasticity analysis is used to partition the size- and age-specific contributions to the stochastic growth rate, lambda(s). We use lambda(s) to construct fitness landscapes and show how different forms of stochasticity influence its topography. We prove the existence of a unique stochastic growth rate, lambda(s), which is independent of the initial population vector, and show that Tuljapurkar's perturbation analysis for log(lambda(s)) can be used to calculate elasticities.

Evolution of complex flowering strategies: an age- and size-structured integral projection model.

We explore the evolution of delayed age- and size-dependent flowering in the monocarpic perennial Carlina vulgaris, by extending the recently developed integral projection approach to include demographic rates that depend on size and age. The parameterized model has excellent descriptive properties both in terms of the population size and in terms of the distributions of sizes within each age class. In Carlina the probability of flowering depends on both plant size and age. We use the parameterized model to predict this relationship, using the evolutionarily stable strategy (ESS) approach. Despite accurately predicting the mean size of flowering individuals, the model predicts a step-function relationship between the probability of flowering and plant size, which has no age component. When the variance of the flowering-threshold distribution is constrained to the observed value, the ESS flowering function contains an age component, but underpredicts the mean flowering size. An analytical approximation is used to explore the effect of variation in the flowering strategy on the ESS predictions. Elasticity analysis is used to partition the agespecific contributions to the finite rate of increase (lambda) of the survival-growth and fecundity components of the model. We calculate the adaptive landscape that defines the ESS and generate a fitness landscape for invading phenotypes in the presence of the observed flowering strategy. The implications of these results for the patterns of genetic diversity in the flowering strategy and for testing evolutionary models are discussed. Results proving the existence of a dominant eigenvalue and its associated eigenvectors in general size- and age-dependent integral projection models are presented.

Evolution in the real world: stochastic variation and the determinants of fitness in Carlina vulgaris.

Empirical studies of life histories often ignore stochastic variation, despite theoretical demonstrations of its potential impact on life-history evolution. Here we use a novel approach to explore the effects of stochastic variation on life-history evolution and estimate the selection pressures operating on the monocarpic perennial Carlina vulgaris, in which flowering may be delayed by up to eight years. The approach is novel in that we use modern theoretical techniques to estimate selection pressures and the fitness landscape from a fully parameterised individual-based model. These approaches take into account temporal variation in demographic rates and density dependence. Analysis of 16 years' data revealed significant temporal variation in growth, mortality, and recruitment in our study population. Flowering was strongly size dependent and, unusually for such a species, also age dependent. Individual-based models of the flowering strategy, parameterized using field data, consistently underestimated the size at flowering, when temporal variation in demographic rates was ignored. In contrast, models that incorporated temporal variation in growth, mortality, and recruitment predicted sizes at flowering not significantly different from those observed in the field. Temporal variation in mortality, which had the largest effect on the flowering strategy, selected for increased size at flowering. An analytical approximation is presented to explain this result, extending the "1-year look-ahead criterion" presented in Rees et al. (2000). A fitness landscape generated by following the fate of rare mutant invaders with a broad range of alternative flowering strategies demonstrated that the observed parameters were adaptive. However, the fitness landscape reveals that approximately equal fitness is achieved by a broad range of strategies, providing a mechanism for the maintenance of genetic variation. To understand how the different parameters that defined our models determine the fitness of rare mutants, we numerically estimated the elasticities and sensitivities of mutant fitness. This demonstrated strong selection on a number of the parameters. Elasticities and sensitivities estimated in constant and random environments were significantly positively correlated, and both were negatively related to the standard error of the parameter. This last result is surprising and, we argue, reflects the genetic and phenotypic responses to selection.

Evolution of flowering strategies in Oenothera glazioviana: an integral projection model approach.

The timing of reproduction is a key determinant of fitness. Here, we develop parameterized integral projection models of size-related flowering for the monocarpic perennial Oenothera glazioviana and use these to predict the evolutionarily stable strategy (ESS) for flowering. For the most part there is excellent agreement between the model predictions and the results of quantitative field studies. However, the model predicts a much steeper relationship between plant size and the probability of flowering than observed in the field, indicating selection for a 'threshold size' flowering function. Elasticity and sensitivity analysis of population growth rate lambda and net reproductive rate R(0) are used to identify the critical traits that determine fitness and control the ESS for flowering. Using the fitted model we calculate the fitness landscape for invading genotypes and show that this is characterized by a ridge of approximately equal fitness. The implications of these results for the maintenance of genetic variation are discussed.