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Evolutionary maternal effects occur whenever a mother’s phenotypic traits directly affect her offspring’s phenotype, independent of the offspring’s genotype. Some of the phenotypic traits that result in maternal effects have a genetic basis, whereas others are environmentally determined. For example, the size of a litter produced by a mammalian mother—a trait with a strong genetic basis—can affect the growth rate of her offspring, while a mother’s dominance rank—an environmentally determined trait—can affect the dominance rank of her offspring.

            The first volume published on the subject in more than a decade, Maternal Effects in Mammals reflects advances in genomic, ecological, and behavioral research, as well new understandings of the evolutionary interplay between mothers and their offspring. Dario Maestripieri and Jill M. Mateo bring together a learned group of contributors to synthesize the vast literature on a range of species, highlight evolutionary processes that were previously overlooked, and propose new avenues of research. Maternal Effects in Mammals will serve as the most comprehensive compendium on and stimulus for interdisciplinary treatments of mammalian maternal effects.

Over the last several decades, mathematical models have become central to the study of social evolution, both in biology and the social sciences. But students in these disciplines often seriously lack the tools to understand them. A primer on behavioral modeling that includes both mathematics and evolutionary theory, Mathematical Models of Social Evolution aims to make the student and professional researcher in biology and the social sciences fully conversant in the language of the field.

Teaching biological concepts from which models can be developed, Richard McElreath and Robert Boyd introduce readers to many of the typical mathematical tools that are used to analyze evolutionary models and end each chapter with a set of problems that draw upon these techniques. Mathematical Models of Social Evolution equips behaviorists and evolutionary biologists with the mathematical knowledge to truly understand the models on which their research depends. Ultimately, McElreath and Boyd’s goal is to impart the fundamental concepts that underlie modern biological understandings of the evolution of behavior so that readers will be able to more fully appreciate journal articles and scientific literature, and start building models of their own.

Plants produce a considerable number of structures of one kind, like leaves, flowers, fruits, and seeds, and this reiteration is a quintessential feature of the body plan of higher plants. But since not all structures of the same kind produced by a plant are identical—for instance, different branches on a plant may be male or female, leaf sizes in the sun differ from those in the shade, and fruit sizes can vary depending on patterns of physiological allocation among branches—a single plant genotype generally produces a multiplicity of phenotypic versions of the same organ.

Multiplicity in Unity uses this subindividual variation to deepen our understanding of the ecological and evolutionary factors involved in plant-animal interactions. On one hand, phenotypic variation at the subindividual scale has diverse ecological implications for animals that eat plants. On the other hand, by choosing which plants to consume, these animals may constrain or modify plant ontogenetic patterns, developmental stability, and the extent to which feasible phenotypic variants are expressed by individuals.

An innovative study of the ecology, morphology, and evolution of modular organisms, Multiplicity in Unity addresses a topic central to our understanding of the diversity of life and the ways in which organisms have coevolved to cope with variable environments.