On the environmental zero-point problem in microevolutionary climate response predictions

It is well documented that populations adapt to climate change by means of phenotypic plasticity, but few reports on adaptation by means of genetically based microevolution caused by selection. Disentanglement of these separate effects requires that the environmental zero-point is defined, and this should not be done arbitrarily. Together with parameter values, the zero-point can be estimated from environmental, phenotypic and fitness data. A prediction error method for this purpose is described, with the feasibility shown by simulations. An estimated environmental zero-point may have large errors, especially for small populations, but may still be a better choice than use of an initial environmental value in a recorded time series, or the mean value, which is often used. Another alternative may be to use the mean value of a past and stationary stochastic environment, which the population is judged to have been fully adapted to, in the sense that the mean fitness was at a global maximum. An exception is here cases with constant phenotypic plasticity, where the microevolutionary change per generation follows directly from phenotypic and environmental data, independent of the chosen environmental zero-point.

The costs and benefits of dispersal in small populations

Dispersal has three major effects on adaptation. First, the gene flow mixes alleles adapted to different environments, potentially hindering (swamping) adaptation. Second, it inflates genetic variance: this aids adaptation to spatially (and temporally) varying environments but if selection is hard, it lowers the mean fitness of the population. Third, neighbourhood size, which determines how weak genetic drift is, increases with dispersal -- when genetic drift is strong, increase of neighbourhood size with dispersal aids adaptation. In this note I focus on the role of dispersal in environments which change smoothly across space, and when local populations are quite small such that genetic drift has a significant effect. Using individual-based simulations, I show that in small populations, even leptokurtic dispersal benefits adaptation, by reducing the power of genetic drift. This has implications for management of small marginal populations: increased gene flow appears beneficial as long as adaptations involves a quantitative, rather than a discrete, trait. However, heavily leptokurtic dispersal will swamp continuous adaptation along steep environmental gradients so that only patches of locally adapted subpopulations remain.

The stagnation paradox: the ever-improving but (more or less) stationary population fitness

Fisher's fundamental theorem states that natural selection improves mean fitness. Fitness, in turn, is often equated with population growth. This leads to an absurd prediction that life evolves to ever-faster growth rates, yet no one seriously claims generally slower population growth rates in the Triassic compared with the present day. I review here, using non-technical language, how fitness can improve yet stay constant (stagnation paradox), and why an unambiguous measure of population fitness does not exist. Subfields use different terminology for aspects of the paradox, referring to stasis, cryptic evolution or the difficulty of choosing an appropriate fitness measure; known resolutions likewise use diverse terms from environmental feedback to density dependence and ‘evolutionary environmental deterioration’. The paradox vanishes when these concepts are understood, and adaptation can lead to declining reproductive output of a population when individuals can improve their fitness by exploiting conspecifics. This is particularly readily observable when males participate in a zero-sum game over paternity and population output depends more strongly on female than male fitness. Even so, the jury is still out regarding the effect of sexual conflict on population fitness. Finally, life-history theory and genetic studies of microevolutionary change could pay more attention to each other.

Inbreeding depression drives evolution of dispersal and polyandry

Inbreeding depression, defined as the reduction in fitness components of offspring of related individuals compared to offspring of unrelated individuals, is a widespread phenomenon and has profound demographic and evolutionary consequences. It can reduce the mean fitness of a population and increase extinction risk, and it can affect traits evolution. Inbreeding depression is widely hypothesized to be a key driver of the evolution of, among other traits, dispersal (individual movements potentially leading to spatial gene flow) and polyandry (female mating with multiple males within a single reproductive bout), as mechanisms to avoid inbreeding. In turn, both dispersal and polyandry can change the relatedness structure within and among populations, thus affecting opportunity for inbreeding and consequent evolution of inbreeding depression. However, despite this potential major shared driver, and despite the large amount of both theoretical and empirical work, evolution of dispersal and polyandry given inbreeding have been so far studied separately, and thus we still do not know whether and how dispersal and polyandry affect each other’s evolution, and how they may feed-back onto evolution of inbreeding depression itself. Here, using a genetically-explicit individual-based model, which models realistic distributions of selection and dominance coefficients of deleterious recessive mutations underpinning inbreeding depression, I show that: 1) inbreeding depression indeed drives evolution of dispersal and polyandry; 2) there is a negative feedback between dispersal evolution and polyandry evolution, which therefore evolve as alternative inbreeding avoidance strategies; 3) inbreeding depression is mainly shaped by the level of dispersal, while polyandry has a much more limited effect.

On the genetic divergence of two adjacent populations living in a homogeneous habitat

The purpose is to study the mechanisms leading to the genetic divergence, i.e. stable genetic differences between two adjacent populations coupled by migration of individuals. We considered the case when the fitness of individuals is strictly determined genetically by a single diallelic locus with alleles A and a, the population is panmictic and Mendel's laws of inheritance hold. The dynamic model contains three phase variables: concentration of allele A in each population and fraction (weight) of the first population in the total population size. We assume that the numbers of coupled populations change independently or strictly synchronously. In the first case, the growth rates are determined by fitness of homo- and heterozygotes, the mean fitness of the each population and the initial concentrations of alleles. In the second case, the growth rates are the same. Methods. To study the model, we used the qualitative theory of differential equations studies, including the construction of parametric and phase portraits, basins of attraction and bifurcation diagrams. We studied local bifurcations that provide the fundamental possibility of genetic divergence. Results. If heterozygote fitness is higher than homozygotes, then both populations are polymorphic with the same concentration of homologous alleles. If the heterozygotes fitness is reduced, then over time the populations will have the same monomorphism in one allele, regardless of the type of population changes. In this case, the dynamics is bistable. We showed that the divergence in the model is a result of subcritical pitchfork bifurcation of an unstable polymorphic state. As a result, the genetic divergent state is unstable and exists as part of the transient process to one of monomorphic state. Conclusion. Divergence is stable only for populations that maintain a population ratio in a certain way. In this case, it is preceded by a saddle-node bifurcation and dynamics is quad-stable, i.e. depending on the initial conditions, two types of stable monomorphism and divergence are possible simultaneously.

The Alignment of Natural and Sexual Selection

Sexual selection has the potential to decrease mean fitness in a population through an array of costs to nonsexual fitness. These costs may be offset when sexual selection favors individuals with high nonsexual fitness, causing the alignment of sexual and natural selection. We review the many laboratory experiments that have manipulated mating systems aimed at quantifying the net effects of sexual selection on mean fitness. These must be interpreted in light of population history and the diversity of ways manipulations have altered sexual interactions, sexual conflict, and sexual and natural selection. Theory and data suggest a net benefit is more likely when sexually concordant genetic variation is enhanced and that ecological context can mediate the relative importance of these different effects. Comparative studies have independently examined the consequences of sexual selection for population/species persistence. These provide little indication of a benefit, and interpreting these higher-level responses is challenging. Expected final online publication date for the Annual Review of Ecology, Evolution, and Systematics, Volume 52 is November 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Precise Measurement of the Fitness Effects of Spontaneous Mutations by Droplet Digital PCR in Burkholderia cenocepacia

Understanding how mutations affect survivability is a key component to knowing how organisms and complex traits evolve. However, most mutations have a minor effect on fitness and these effects are difficult to resolve using traditional molecular techniques. Therefore, there is a dire need for more accurate and precise fitness measurements methods. Here, we measured the fitness effects in Burkholderia cenocepacia HI2424 mutation accumulation (MA) lines using droplet-digital polymerase chain reaction (ddPCR). Overall, the fitness measurements from ddPCR-MA are correlated positively with fitness measurements derived from traditional phenotypic marker assays (r = 0.297, p = 0.05), but showed some differences. First, ddPCR had significantly lower measurement variance in fitness (F = 3.78, p < 2.6x10−13) in control experiments. Second, the mean fitness from ddPCR-MA measurements were significantly lower than phenotypic marker assays (-0.0041 vs -0.0071, p = 0.006). Consistent with phenotypic marker assays, ddPCR-MA measurements observed multiple (27/43) lineages that significantly deviated from mean fitness, suggesting that a majority of the mutations are neutral or slightly deleterious and intermixed with a few mutations that have extremely large effects. Of these mutations, we found a significant excess of mutations within DNA excinuclease and Lys R transcriptional regulators that have extreme deleterious and beneficial effects, indicating that modifications to transcription and replication may have a strong effect on organismal fitness. This study demonstrates the power of ddPCR as a ubiquitous method for high-throughput fitness measurements in both DNA and RNA-based organisms regardless of cell type or physiology.

The quantitative genetics of fitness in a wild bird population

Additive genetic variance in fitness equals the change in mean fitness due to selection. It is a prerequisite for adaptation, as a trait must be genetically correlated with fitness in order to evolve. Despite its relevance, additive genetic variance in fitness has not often been estimated in wild populations. Here, we investigate additive genetic variance in lifetime fitness, as well as its underlying components, in common terns (Sterna hirundo). Using a series of animal models applied to 28 years of data comprising ca. 6000 pedigreed individuals, we find nominally zero additive genetic variance in the Zero-inflated component of lifetime fitness, and low but unreliable variance in the Poisson component. We also find low but likely nonzero additive genetic variance in adult annual reproductive success, but not in survival. As such, our study (i) suggests heritable variance in common tern fitness to result mostly from heritable variance in reproductive success, rather than in early-life or adult survival, (ii) shows how studying the genetic architecture of fitness in natural populations remains challenging, and (iii) highlights the importance of maintaining long-term individual-based studies such that a major research aim in evolutionary ecology will come within better reach in the next decade.

Embodied Computational Evolution: Feedback Between Development and Evolution in Simulated Biorobots

Given that selection removes genetic variance from evolving populations, thereby reducing exploration opportunities, it is important to find mechanisms that create genetic variation without the disruption of adapted genes and genomes caused by random mutation. Just such an alternative is offered by random epigenetic error, a developmental process that acts on materials and parts expressed by the genome. In this system of embodied computational evolution, simulated within a physics engine, epigenetic error was instantiated in an explicit genotype-to-phenotype map as transcription error at the initiation of gene expression. The hypothesis was that transcription error would create genetic variance by shielding genes from the direct impact of selection, creating, in the process, masquerading genomes. To test this hypothesis, populations of simulated embodied biorobots and their developmental systems were evolved under steady directional selection as equivalent rates of random mutation and random transcriptional error were covaried systematically in an 11 × 11 fully factorial experimental design. In each of the 121 different experimental conditions (unique combinations of mutation and transcription error), the same set of 10 randomly created replicate populations of 60 individuals were evolved. Selection for the improved locomotor behavior of individuals led to increased mean fitness of populations over 100 generations at nearly all levels and combinations of mutation and transcription error. When the effects of both types of error were partitioned statistically, increasing transcription error was shown to increase the final genetic variance of populations, incurring a fitness cost but acting on variance independently and differently from genetic mutation. Thus, random epigenetic errors in development feed back through selection of individuals with masquerading genomes to the population’s genetic variance over generational time. Random developmental processes offer an additional mechanism for exploration by increasing genetic variation in the face of steady, directional selection.