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Over the course of multiple divisions, cells accumulate diverse nongenetic, somatic damage including misfolded and aggregated proteins and cell wall defects. If the rate of damage accumulation exceeds the rate of dilution through cell growth, a dedicated mitigation strategy is required to prevent eventual population collapse. Strategies for somatic damage control can be divided into two categories, asymmetric allocation and repair, which are not, in principle, mutually exclusive. We explore a mathematical model to identify the optimal strategy, maximizing the total cell number, over a wide range of environmental and physiological conditions. The optimal strategy is primarily determined by extrinsic, damage-independent mortality and the physiological model for damage accumulation that can be either independent (linear) or increasing (exponential) with respect to the prior accumulated damage. Under the linear regime, the optimal strategy is either exclusively repair or asymmetric allocation, whereas under the exponential regime, the optimal strategy is a combination of asymmetry and repair. Repair is preferred when extrinsic mortality is low, whereas at high extrinsic mortality, asymmetric damage allocation becomes the strategy of choice. We hypothesize that at an early stage of life evolution, optimization over repair and asymmetric allocation of somatic damage gave rise to r and K selection strategists.

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AbstractHere, we propose a theory for the structure of communities of competing species. We include ecologically realistic assumptions, such as density dependence and stochastic fluctuations in the environment, and analyze how evolution caused by r- and K-selection will affect the packing of species in the phenotypic space as well as the species abundance distribution. Species-specific traits have the same matrix G of additive genetic variances and covariances, and evolution of mean traits is affected by fluctuations in population size of all species. In general, the model produces a shape of the distributions of log abundances that is skewed to the left, which is typical of most natural communities. Mean phenotypes of the species in the community are distributed approximately uniformly on the surface of a multidimensional sphere. However, environmental stochasticity generates selection that deviates species slightly from this surface; nonetheless, phenotypic distribution will be different from a random packing of species. This model of community evolution provides a theoretical framework that predicts a relationship between the structure of the phenotypic space and the form of species abundance distributions that can be compared against time series of variation in community structure.

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AbstractAdaptive topography is a central concept in evolutionary biology, describing how the mean fitness of a population changes with gene frequencies or mean phenotypes. We use expected population size as a quantity to be maximized by natural selection to show that selection on pairwise combinations of reproductive traits of collared flycatchers caused by fluctuations in population size generated an adaptive topography with distinct peaks often located at intermediate phenotypes. This occurred because r- and K-selection made phenotypes favored at small densities different from those with higher fitness at population sizes close to the carrying capacity K. Fitness decreased rapidly with a delay in the timing of egg laying, with a density-dependent effect especially occurring among early-laying females. The number of fledglings maximizing fitness was larger at small population sizes than when close to K. Finally, there was directional selection for large fledglings independent of population size. We suggest that these patterns can be explained by increased competition for some limiting resources or access to favorable nest sites at high population densities. Thus, r- and K-selection based on expected population size as an evolutionary maximization criterion may influence life-history evolution and constrain the selective responses to changes in the environment.

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The idea that selection works in different ways during free population growth and at the equilibrium population size has been present in theoretical biology for a long time. It was first expressed as an r and K selection concept and later clarified in the debate on fitness measures in life history theory. The latest discussion related to this topic is focused on the nest site lottery mechanism and the resulting new population growth model. In this mechanistic biphasic model, the suppression of growth is induced by a shortage of free nest sites for newborns. Before it occurs, the population can grow exponentially. In this paper, the continuous version of the model and its selective properties are analysed. We show a continuous smooth transition between different fitness measures operating during the exponential growth and suppressed growth phase and at the equilibrium population size. Then, the model is extended to the case of a population of parasites, where a constant number of nest sites is replaced by the dynamics of a population of their hosts, in the role of the limiting supply. Parasite strategies are selected under exponential and suppressed growth phases of the population of hosts. Transitions between different fitness measures and conditions for extinction of hosts by parasites are analysed. An interesting result is the possibility of a continuum of fitness measures of parasites for the unsuppressed exponential growth of the host population.

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Size determines the rate at which organisms acquire and use resources but it is unclear what size should be favoured under unpredictable resource regimes. Some theories claim smaller organisms can grow faster following a resource pulse, whereas others argue larger species can accumulate more resources and maintain growth for longer periods between resource pulses. Testing these theories has relied on interspecific comparisons, which tend to confound body size with other life-history traits. As a more direct approach, we used 280 generations of artificial selection to evolve a 10-fold difference in mean body size between small- and large-selected phytoplankton lineages of Dunaliella tertiolecta, while controlling for biotic and abiotic variables. We then quantified how body size affected the ability of this species to grow at nutrient-replete conditions and following periods of nitrogen or phosphorous deprivation. Overall, smaller cells showed slower growth, lower storage capacity and poorer recovery from phosphorous depletion, as predicted by the 'fasting endurance hypothesis'. However, recovery from nitrogen limitation was independent of size-a finding unanticipated by current theories. Phytoplankton species are responsible for much of the global carbon fixation and projected trends of cell size decline could reduce primary productivity by lowering the ability of a cell to store resources.

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In a stable environment, evolution maximizes growth rates in populations that are not density regulated and the carrying capacity in the case of density regulation. In a fluctuating environment, evolution maximizes a function of growth rate, carrying capacity and environmental variance, tending to r-selection and K-selection under large and small environmental noise, respectively. Here we analyze a model in which birth and death rates depend on density through the same function but with independent strength of density dependence. As a special case, both functions may be linear, corresponding to logistic dynamics. It is shown that evolution maximizes a function of the deterministic growth rate r0 and the lifetime reproductive success (LRS) R0 , both defined at small densities, as well as the environmental variance. Under large noise this function is dominated by r0 and average lifetimes are small, whereas R0 dominates and lifetimes are larger under small noise. Thus, K-selection is closely linked to selection for large R0 so that evolution tends to maximize LRS in a stable environment. Consequently, different quantities (r0 and R0 ) tend to be maximized at low and high densities, respectively, favoring density-dependent changes in the optimal life history.

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Understanding the variation in selection pressure on key life-history traits is crucial in our rapidly changing world. Density is rarely considered as a selective agent. To study its importance, we partition phenotypic selection in fluctuating environments into components representing the population growth rate at low densities and the strength of density dependence, using a new stochastic modelling framework. We analysed the number of eggs laid per season in a small song-bird, the great tit, and found balancing selection favouring large clutch sizes at small population densities and smaller clutches in years with large populations. A significant interaction between clutch size and population size in the regression for the Malthusian fitness reveals that those females producing large clutch sizes at small population sizes also are those that show the strongest reduction in fitness when population size is increased. This provides empirical support for ongoing r- and K-selection in this population, favouring phenotypes with large growth rates r at small population sizes and phenotypes with high competitive skills when populations are close to the carrying capacity K This selection causes long-term fluctuations around a stable mean clutch size caused by variation in population size, implying that r- and K-selection is an important mechanism influencing phenotypic evolution in fluctuating environments. This provides a general link between ecological dynamics and evolutionary processes, operating through a joint influence of density dependence and environmental stochasticity on fluctuations in population size.

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The intrinsic rate of natural increase (r m) is calculated for 72 primate species, using Cole's (1954) equation. The value of r m relative to body mass is then calculated by use of allometric analysis. Both r mand relative r m are used to test the prediction that animals in unpredictable and/or harsh habitats will have a higher r mthan will those in more predictable and/or less harsh habitats. No significant link between habitat type and r mis found. However, correlations between ecology and relative r msuggest that relative r mis high in primate species living in more open habitats and low in species found in primary rainforest. Although there are few correlations between relative r m and climate parameters, those that are found suggest that variable climates, dry climates and hot climates will select for a high relative r m.