Susanne Schindler

Demography, not inheritance, drives phenotypic change in hunted bighorn sheep

Significance Understanding the consequences that selective harvest has on a targeted trait, such as body size, is a great challenge. This is principally because it is difficult to evaluate the relative importance of the evolutionary and demographic factors that underlie a change in the distribution of a selected trait in a hunted population. Here we use a novel and recently developed two-sex integral projection model to tease apart the underlying demographic and evolutionary mechanisms of trait change in a trophy-hunted bighorn sheep population. We find that body size is weakly inherited and that subsequently demographic change, and not evolutionary change, as previously thought, is the principle driver of trait shifts in hunted bighorn sheep. Selective harvest, such as trophy hunting, can shift the distribution of a quantitative character such as body size. If the targeted character is heritable, then there will be an evolutionary response to selection, and where the trait is not, then any response will be plastic or demographic. Identifying the relative contributions of these different mechanisms is a major challenge in wildlife conservation. New mathematical approaches can provide insight not previously available. Here we develop a size- and age-based two-sex integral projection model based on individual-based data from a long-term study of hunted bighorn sheep (Ovis canadensis) at Ram Mountain, Canada. We simulate the effect of trophy hunting on body size and find that the inheritance of body mass is weak and that any perceived decline in body mass of the bighorn population is largely attributable to demographic change and environmental factors. To our knowledge, this work provides the first use of two-sex integral projection models to investigate the potential eco-evolutionary consequences of selective harvest.

Sex‐specific demography and generalization of the Trivers–Willard theory

The Trivers–Willard theory proposes that the sex ratio of offspring should vary with maternal condition when it has sex‐specific influences on offspring fitness. In particular, mothers in good condition in polygynous and dimorphic species are predicted to produce an excess of sons, whereas mothers in poor condition should do the opposite. Despite the elegance of the theory, support for it has been limited. Here we extend and generalize the Trivers–Willard theory to explain the disparity between predictions and observations of offspring sex ratio. In polygynous species, males typically have higher mortality rates, different age‐specific reproductive schedules and more risk‐prone life history tactics than females; however, these differences are not currently incorporated into the Trivers–Willard theory. Using two‐sex models parameterized with data from free‐living mammal populations with contrasting levels of sex differences in demography, we demonstrate how sex differences in life history traits over the entire lifespan can lead to a wide range of sex allocation tactics, and show that correlations between maternal condition and offspring sex ratio alone are insufficient to conclude that mothers adaptively adjust offspring sex ratio.

The Influence of Nonrandom Mating on Population Growth

When nonrandom mating alters offspring numbers or the distribution of offspring phenotypes, it has the potential to impact the population growth rate. Similarly, sex-specific demographic parameters that influence the availability of mating partners can leave a signature on the population growth rate. We develop a general framework to explore how mating patterns and sex differences influence the population growth rate. We do this by constructing a two-sex integral projection model to explore ways in which altering the mating behavior from random to nonrandom mating (assortative, disassortative, or selection for size) and altering demographic parameters in one or both sexes (growth, survival, and parental contribution to offspring phenotype) affect the population growth rate. We demonstrate our framework using data from a population of Columbian ground squirrels. Our results suggest that the population growth rate is substantially affected when nonrandom mating is linked to sex differences in demographic parameters or parental contributions to offspring phenotype, but interestingly, the effect of the mating pattern alone is rather small. Our results also suggest that the population growth rate of Columbian ground squirrels would increase with the degree of disassortative mating and with the degree of the mating advantage of large individuals.

Modeling Adaptive and Nonadaptive Responses of Populations to Environmental Change.

Understanding how the natural world will be impacted by environmental change over the coming decades is one of the most pressing challenges facing humanity. Addressing this challenge is difficult because environmental change can generate both population-level plastic and evolutionary responses, with plastic responses being either adaptive or nonadaptive. We develop an approach that links quantitative genetic theory with data-driven structured models to allow prediction of population responses to environmental change via plasticity and adaptive evolution. After introducing general new theory, we construct a number of example models to demonstrate that evolutionary responses to environmental change over the short-term will be considerably slower than plastic responses and that the rate of adaptive evolution to a new environment depends on whether plastic responses are adaptive or nonadaptive. Parameterization of the models we develop requires information on genetic and phenotypic variation and demography that will not always be available, meaning that simpler models will often be required to predict responses to environmental change. We consequently develop a method to examine whether the full machinery of the evolutionarily explicit models we develop will be needed to predict responses to environmental change or whether simpler nonevolutionary models that are now widely constructed may be sufficient.

Linking the population growth rate and the age-at-death distribution

The population growth rate is linked to the distribution of age at death. We demonstrate that this link arises because both the birth and death rates depend on the variance of age-at-death. This bears the prospect to separate the influences of the age patterns of fertility and mortality on population growth rate. Here, we show how the age pattern of death affects population growth. Using this insight we derive a new approximation of the population growth rate that uses the first and second moments of the age-at-death distribution. We apply our new approximation to 46 mammalian life tables (including humans) and show that it is on par with the most prominent other approximations.

Quantitative Genetics Meets Integral Projection Models: Unification of Widely Used Methods from Ecology and Evolution

Micro-evolutionary predictions are complicated by ecological feedbacks like density dependence, while ecological predictions can be complicated by evolutionary change. A widely used approach in micro-evolution, quantitative genetics, struggles to incorporate ecological processes into predictive models, while structured population modelling, a tool widely used in ecology, rarely incorporates evolution explicitly. In this paper we develop a flexible, general framework that links quantitative genetics and structured population models. We use the quantitative genetic approach to write down the phenotype as an additive map. We then construct integral projection models for each component of the phenotype. The dynamics of the distribution of the phenotype are generated by combining distributions of each of its components. Population projection models can be formulated on per generation or on shorter time steps. We introduce the framework before developing example models with parameters chosen to exhibit specific dynamics. These models reveal (i) how evolution of a phenotype can cause populations to move from one dynamical regime to another (e.g. from stationarity to cycles), (ii) how additive genetic variances and covariances (the G matrix) are expected to evolve over multiple generations, (iii) how changing heritability with age can maintain additive genetic variation in the face of selection and (iii) life history, population dynamics, phenotypic characters and parameters in ecological models will change as adaptation occurs. Our approach unifies population ecology and evolutionary biology providing a framework allowing a very wide range of questions to be addressed. The next step is to apply the approach to a variety of laboratory and field systems. Once this is done we will have a much deeper understanding of eco-evolutionary dynamics and feedbacks.

Searching for a Cancer-Proof Organism: It’s the Journey That Teaches You About the Destination

Despite an obvious focus of cancer as a medical phenomenon affecting human lifespan, cancer occurs across multicellular life. We argue that cancer research could benefit from moving from considering other species’ cancers as mere models of those of humans to embracing the differences across species, as these dictate the logic of natural selection and its ability to “see” cancer as a relevant problem in an organism’s ecology and life history. Simultaneously, cancer should be incorporated more strongly in evolutionary thinking itself. At the origin of multicellularity, there is a gray zone between offspring production and cancer, and the association between sexual reproduction and a unicellular stage in a metazoan life history could prove interesting in this context. The idea that links sex with possibilities to discard “faulty” products of cell divisions is particularly clear in a basal metazoan, the hydra. In larger species with clearly differentiated tissues, there is much to gain from investigating the coevolution of senescence and cancer robustness: prolonging the lifespan of cell lineages (e.g., via telomerase) can be counterproductive for the lifespan of the entire organism, and organisms that live long and are now miniaturized compared with their ancestors (such as birds) should show great promise as study species.

Adaptive and Non-adaptive Responses of Populations to Environmental Change

Understanding how the natural world will be impacted by environmental change over the coming decades is one of the most pressing challenges facing humanity. Addressing this challenge is difficult because environmental change can generate both population level plastic and evolutionary responses, with plastic responses being either adaptive or non-adaptive. We develop an approach that links quantitative genetic theory with data-driven structured models to allow prediction of population responses to environmental change via plasticity and adaptive evolution. After introducing general new theory, we construct a number of example models to demonstrate that evolutionary responses to environmental change over the short-term will be considerably slower than plastic responses, and that the rate of adaptive evolution to a new environment depends upon whether plastic responses are adaptive or non-adaptive. Parameterization of the models we develop requires information on genetic and phenotypic variation and demography that will not always be available, meaning that simpler models will often be required to predict responses to environmental change. We consequently develop a method to examine whether the full machinery of the evolutionarily explicit models we develop will be needed to predict responses to environmental change, or whether simpler non-evolutionary models that are now widely constructed may be sufficient.

Sex-Specific Heterogeneity in Fixed Morphological Traits Influences Individual Fitness in a Monogamous Bird Population

Theoretical work has emphasized the important role of individual traits on population dynamics, but empirical models are often based on average or stage-dependent demographic rates. In this study on a monogamous bird, the Eurasian hoopoe (Upupa epops), we show how the interactions between male and female fixed and dynamic heterogeneity influence demographic rates and population dynamics. We built an integral projection model including individual sex, age, condition (reflecting dynamic heterogeneity), and fixed morphology (reflecting fixed heterogeneity). Fixed morphology was derived from a principal component analysis of six morphological traits. Our results revealed that reproductive success and survival were linked to fixed heterogeneity, whereas dynamic heterogeneity influenced mainly the timing of reproduction. Fixed heterogeneity had major consequences for the population growth rate, but interestingly, its effect on population dynamics differed between the sexes. Female fixed morphology was directly linked to annual reproductive success, whereas male fixed morphology also influenced annual survival, being twice higher in large than in small males. Even in a monogamous bird with shared parental care, large males can reach 10% higher fitness than females. Including the dynamics of male and female individual traits in population models refines our understanding of the individual mechanisms that influence demographic rates and population dynamics and can help in identifying differences in sex-specific strategies.

Reply to Hedrick et al.: Trophy hunting influences the distribution of trait values through demographic impacts

Coltman et al. (1) claimed that the “production of smaller-horned, lighter rams and fewer trophies” is “an evolutionary response to sport hunting of bighorn trophy rams.” Using data from the same population, we conclude (2) that the very rapid shift in body mass they report was principally demographic in origin rather than evolutionary. Our conclusions are further supported by additional research (3) that has demonstrated that the approach Coltman et al. (1) used to detect trends in breeding values gives unreliable results that are highly anticonservative.