Summary1. Efforts to understand the links between evolutionary and ecological dynamics hinge on our ability to measure and understand how genes influence phenotypes, fitness and population dynamics. Quantitative genetics provides a range of theoretical and empirical tools with which to achieve this when the relatedness between individuals within a population is known. 2. A number of recent studies have used a type of mixed-effects model, known as the animal model, to estimate the genetic component of phenotypic variation using data collected in the field. Here, we provide a practical guide for ecologists interested in exploring the potential to apply this quantitative genetic method in their research. 3. We begin by outlining, in simple terms, key concepts in quantitative genetics and how an animal model estimates relevant quantitative genetic parameters, such as heritabilities or genetic correlations. 4. We then provide three detailed example tutorials, for implementation in a variety of software packages, for some basic applications of the animal model. We discuss several important statistical issues relating to best practice when fitting different kinds of mixed models. 5. We conclude by briefly summarizing more complex applications of the animal model, and by highlighting key pitfalls and dangers for the researcher wanting to begin using quantitative genetic tools to address ecological and evolutionary questions.

The ability of individual organisms to alter morphological and life‐history traits in response to the conditions they experience is an example of phenotypic plasticity which is fundamental to any population's ability to deal with short‐term environmental change. We currently know little about the prevalence, and evolutionary and ecological causes and consequences of variation in life history plasticity in the wild. Here we outline an analytical framework, utilizing the reaction norm concept and random regression statistical models, to assess the between‐individual variation in life history plasticity that may underlie population level responses to the environment at both phenotypic and genetic levels. We discuss applications of this framework to date in wild vertebrate populations, and illustrate how natural selection and ecological constraint may alter a population's response to the environment through their effects at the individual level. Finally, we present future directions and challenges for research into individual plasticity.

Theoretical and laboratory research suggests that phenotypic plasticity can evolve under selection. However, evidence for its evolutionary potential from the wild is lacking. We present evidence from a Dutch population of great tits (Parus major) for variation in individual plasticity in the timing of reproduction, and we show that this variation is heritable. Selection favoring highly plastic individuals has intensified over a 32-year period. This temporal trend is concurrent with climate change causing a mismatch between the breeding times of the birds and their caterpillar prey. Continued selection on plasticity can act to alleviate this mismatch.

That senescence is rarely, if ever, observed in natural populations is an oft-quoted fallacy within bio-gerontology. We identify the roots of this fallacy in the otherwise seminal works of Medawar and Comfort, and explain that under antagonistic pleiotropy or disposable soma explanations for the evolution of senescence there is no reason why senescence cannot evolve to be manifest within the life expectancies of wild organisms. The recent emergence of long-term field studies presents irrefutable evidence that senescence is commonly detected in nature. We found such evidence in 175 different animal species from 340 separate studies. Although the bulk of this evidence comes from birds and mammals, we also found evidence for senescence in other vertebrates and insects. We describe how high-quality longitudinal field data allow us to test evolutionary explanations for differences in senescence between the sexes and among traits and individuals. Recent studies indicate that genes, prior environment and investment in growth and reproduction influence aging rates in the wild. We argue that – with the fallacy that wild animals do not senesce finally dead and buried – collaborations between bio-gerontologists and field biologists can begin to test the ecological generality of purportedly ‘public’ mechanisms regulating aging in laboratory models.