🔖 Human Evolution: Our Brains and Behavior by Robin Dunbar (Oxford University Press) marked as want to read.
Official release date: November 1, 2016
09/14/16: downloaded a review copy via NetGalley

human-evolution-our-brains-and-behavior-by-robin-dunbar-11-01-16

Description
The story of human evolution has fascinated us like no other: we seem to have an insatiable curiosity about who we are and where we have come from. Yet studying the “stones and bones” skirts around what is perhaps the realest, and most relatable, story of human evolution – the social and cognitive changes that gave rise to modern humans.

In Human Evolution: Our Brains and Behavior, Robin Dunbar appeals to the human aspects of every reader, as subjects of mating, friendship, and community are discussed from an evolutionary psychology perspective. With a table of contents ranging from prehistoric times to modern days, Human Evolution focuses on an aspect of evolution that has typically been overshadowed by the archaeological record: the biological, neurological, and genetic changes that occurred with each “transition” in the evolutionary narrative. Dunbar’s interdisciplinary approach – inspired by his background as both an anthropologist and accomplished psychologist – brings the reader into all aspects of the evolutionary process, which he describes as the “jigsaw puzzle” of evolution that he and the reader will help solve. In doing so, the book carefully maps out each stage of the evolutionary process, from anatomical changes such as bipedalism and increase in brain size, to cognitive and behavioral changes, such as the ability to cook, laugh, and use language to form communities through religion and story-telling. Most importantly and interestingly, Dunbar hypothesizes the order in which these evolutionary changes occurred-conclusions that are reached with the “time budget model” theory that Dunbar himself coined. As definitive as the “stones and bones” are for the hard dates of archaeological evidence, this book explores far more complex psychological questions that require a degree of intellectual speculation: What does it really mean to be human (as opposed to being an ape), and how did we come to be that way?

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🔖 Human Evolution: Our Brains and Behavior by Robin Dunbar (Oxford University Press) was originally published on Chris Aldrich | Boffo Socko

NIMBioS Tutorial: Evolutionary Quantitative Genetics 2016

NIMBioS Tutorial: Evolutionary Quantitative Genetics 2016 by NIMBioS (nimbios.org)

This tutorial will review the basics of theory in the field of evolutionary quantitative genetics and its connections to evolution observed at various time scales. Quantitative genetics deals with the inheritance of measurements of traits that are affected by many genes. Quantitative genetic theory for natural populations was developed considerably in the period from 1970 to 1990 and up to the present, and it has been applied to a wide range of phenomena including the evolution of differences between the sexes, sexual preferences, life history traits, plasticity of traits, as well as the evolution of body size and other morphological measurements. Textbooks have not kept pace with these developments, and currently few universities offer courses in this subject aimed at evolutionary biologists. There is a need for evolutionary biologists to understand this field because of the ability to collect large amounts of data by computer, the development of statistical methods for changes of traits on evolutionary trees and for changes in a single species through time, and the realization that quantitative characters will not soon be fully explained by genomics. This tutorial aims to fill this need by reviewing basic aspects of theory and illustrating how that theory can be tested with data, both from single species and with multiple-species phylogenies. Participants will learn to use R, an open-source statistical programming language, to build and test evolutionary models. The intended participants for this tutorial are graduate students, postdocs, and junior faculty members in evolutionary biology.

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NIMBioS Tutorial: Evolutionary Quantitative Genetics 2016 was originally published on Chris Aldrich | Boffo Socko

Penguin Revives Decades-Old Software for 30th Anniversary Edition of “The Blind Watchmaker” | The Digital Reader

Penguin Revives Decades-Old Software for 30th Anniversary Edition of “The Blind Watchmaker” | The Digital Reader

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Penguin Revives Decades-Old Software for 30th Anniversary Edition of “The Blind Watchmaker” | The Digital Reader was originally published on Chris Aldrich | Boffo Socko

16w5113: Stochastic and Deterministic Models for Evolutionary Biology | Banff International Research Station

Stochastic and Deterministic Models for Evolutionary Biology(Banff International Research Station)

A BIRS / Casa Matemática Oaxaca Workshop arriving in Oaxaca, Mexico Sunday, July 31 and departing Friday August 5, 2016

Evolutionary biology is a rapidly changing field, confronted to many societal problems of increasing importance: impact of global changes, emerging epidemics, antibiotic resistant bacteria… As a consequence, a number of new problematics have appeared over the last decade, challenging the existing mathematical models. There exists thus a demand in the biology community for new mathematical models allowing a qualitative or quantitative description of complex evolution problems. In particular, in the societal problems mentioned above, evolution is often interacting with phenomena of a different nature: interaction with other organisms, spatial dynamics, age structure, invasion processes, time/space heterogeneous environment… The development of mathematical models able to deal with those complex interactions is an ambitious task. Evolutionary biology is interested in the evolution of species. This process is a combination of several phenomena, some occurring at the individual level (e.g. mutations), others at the level of the entire population (competition for resources), often consisting of a very large number of individuals. the presence of very different scales is indeed at the core of theoretical evolutionary biology, and at the origin of many of the difficulties that biologists are facing. The development of new mathematical models thus requires a joint work of three different communities of researchers: specialists of partial differential equations, specialists of probability theory, and theoretical biologists. The goal of this workshop is to gather researchers from each of these communities, currently working on close problematics. Those communities have usually few interactions, and this meeting would give them the opportunity to discuss and work around a few biological thematics that are especially challenging mathematically, and play a crucial role for biological applications.

The role of a spatial structure in models for evolution: The introduction of a spatial structure in evolutionary biology models is often challenging. It is however well known that local adaptation is frequent in nature: field data show that the phenotypes of a given species change considerably across its range. The spatial dynamics of a population can also have a deep impact on its evolution. Assessing e.g. the impact of global changes on species requires the development of robust mathematical models for spatially structured populations.

The first type of models used by theoretical biologists for this type of problems are IBM (Individual Based Models), which describe the evolution of a finite number of individuals, characterized by their position and a phenotype. The mathematical analysis of IBM in spatially homogeneous situations has provided several methods that have been successful in the theoretical biology community (see the theory of Adaptive Dynamics). On the contrary, very few results exist so far on the qualitative properties of such models for spatially structured populations.

The second class of mathematical approach for this type of problem is based on ”infinite dimensional” reaction-diffusion: the population is structured by a continuous phenotypic trait, that affects its ability to disperse (diffusion), or to reproduce (reaction). This type of model can be obtained as a large population limit of IBM. The main difficulty of these models (in the simpler case of asexual populations) is the term modeling the competition from resources, that appears as a non local competition term. This term prevents the use of classical reaction diffusion tools such as the comparison principle and sliding methods. Recently, promising progress has been made, based on tools from elliptic equations and/or Hamilton-Jacobi equations. The effects of small populations can however not be observed on such models. The extension of these models and methods to include these effects will be discussed during the workshop.

Eco-evolution models for sexual populations:An essential question already stated by Darwin and Fisher and which stays for the moment without answer (although it continues to intrigue the evolutionary biologists) is: ”Why does sexual reproduction maintain?” Indeed this reproduction way is very costly since it implies a large number of gametes, the mating and the choice of a compatible partner. During the meiosis phasis, half of the genetical information is lost. Moreover, the males have to be fed and during the sexual mating, individual are easy preys for predators. A partial answer is that recombination plays a main role by better eliminating the deleterious mutations and by increasing the diversity. Nevertheless, this theory is not completely satisfying and many researches are devoted to understanding evolution of sexual populations and comparison between asexual and sexual reproduction. Several models exist to model the influence of sexual reproduction on evolving species. The difficulty compared to asexual populations is that a detailed description of the genetic basis of phenotypes is required, and in particular include recombinations. For sexual populations, recombination plays a main role and it is essential to understand. All models require strong biological simplifications, the development of relevant mathematical methods for such mechanisms then requires a joint work of mathematicians and biologists. This workshop will be an opportunity to set up such collaborations.

The first type of model considers a small number of diploid loci (typically one locus and two alleles), while the rest of the genome is considered as fixed. One can then define the fitness of every combination of alleles. While allowing the modeling of specific sexual effects (such as dominant/recessive alleles), this approach neglects the rest of the genome (and it is known that phenotypes are typically influenced by a large number of loci). An opposite approach is to consider a large number of loci, each locus having a small and additive impact on the considered phenotype. This approach then neglects many microscopic phenomena (epistasis, dominant/recessive alleles…), but allows the derivation of a deterministic model, called the infinitesimal model, in the case of a large population. The construction of a good mathematical framework for intermediate situation would be an important step forward.

The evolution of recombination and sex is very sensitive to the interaction between several evolutionary forces (selection, migration, genetic drift…). Modeling these interactions is particularly challenging and our understanding of the recombination evolution is often limited by strong assumptions regarding demography, the relative strength of these different evolutionary forces, the lack of spatial structure… The development of a more general theoretical framework based on new mathematical developments would be particularly valuable.

Another problem, that has received little attention so far and is worth addressing, is the modeling of the genetic material exchanges in asexual population. This phenomena is frequent in micro-organisms : horizontal gene transfers in bacteria, reassortment or recombination in viruses. These phenomena share some features with sexual reproduction. It would be interesting to see if the effect of this phenomena can be seen as a perturbation of existing asexual models. This would in particular be interesting in spatially structured populations (e.g. viral epidemics), since the the mathematical analysis of spatially structured asexual populations is improving rapidly.

Modeling in evolutionary epidemiology: Mathematical epidemiology has been developing since more than a century ago. Yet, the integration of population genetics phenomena to epidemiology is relatively recent. Microbial pathogens (bacteria and viruses) are particularly interesting organisms because their short generation times and large mutation rates allow them to adapt relatively fast to changing environments. As a consequence, ecological (demography) and evolutionary (population genetics) processes often occur at the same pace. This raises many interesting problems.

A first challenge is the modeling of the spatial dynamics of an epidemics. The parasites can evolve during the epidemics of a new host population, either to adapt to a heterogeneous environment, or because it will itself modify the environment as it invades. The applications of such studies are numerous: antibiotic management, agriculture… An aspect of this problem for which our workshop can bring a significant contribution (thanks to the diversity of its participants) is the evolution of the pathogen diversity. During the large expansion produced by an epidemics, there is a loss of diversity in the invading parasites, since most pathogens originate from a few parents. The development of mathematical models for those phenomena is challenging: only a small number of pathogens are present ahead of the epidemic front, while the number of parasites rapidly become very large after the infection. The interaction between a stochastic micro scale and a deterministic macro scale is apparent here, and deserves a rigorous mathematical analysis.

Another interesting phenomena is the effect of a sudden change of the environment on a population of pathogens. Examples of such situations are for instance the antibiotic treatment of an infected patients, or the transmission of a parasite to a new host species (transmission of the avian influenza to human beings, for instance). Related experiments are relatively easy to perform, and called evolutionary rescue experiments. So far, this question has received limited attention from the mathematical community. The key is to estimate the probability that a mutant well adapted to the new environment existed in the original population, or will appear soon after the environmental change. Interactions between biologists specialists of those questions and mathematicians should lead to new mathematical problems.

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16w5113: Stochastic and Deterministic Models for Evolutionary Biology | Banff International Research Station was originally published on Chris Aldrich | Boffo Socko

A new view of the tree of life

A new view of the tree of life

A new view of the tree of life(Nature Microbiology)

An update to the €˜tree of life has revealed a dominance of bacterial diversity in many ecosystems and extensive evolution in some branches of the tree. It also highlights how few organisms we have been able to cultivate for further investigation.

Abstract

The tree of life is one of the most important organizing principles in biology. Gene surveys suggest the existence of an enormous number of branches, but even an approximation of the full scale of the tree has remained elusive. Recent depictions of the tree of life have focused either on the nature of deep evolutionary relationships or on the known, well-classified diversity of life with an emphasis on eukaryotes. These approaches overlook the dramatic change in our understanding of life’s diversity resulting from genomic sampling of previously unexamined environments. New methods to generate genome sequences illuminate the identity of organisms and their metabolic capacities, placing them in community and ecosystem contexts. Here, we use new genomic data from over 1,000 uncultivated and little known organisms, together with published sequences, to infer a dramatically expanded version of the tree of life, with Bacteria, Archaea and Eukarya included. The depiction is both a global overview and a snapshot of the diversity within each major lineage. The results reveal the dominance of bacterial diversification and underline the importance of organisms lacking isolated representatives, with substantial evolution concentrated in a major radiation of such organisms. This tree highlights major lineages currently underrepresented in biogeochemical models and identifies radiations that are probably important for future evolutionary analyses.

Laura A. Hug, Brett J. Baker, Karthik Anantharaman, Christopher T. Brown, Alexander J. Probst, Cindy J. Castelle, Cristina N. Butterfield, Alex W. Hernsdorf, Yuki Amano, Kotaro Ise, Yohey Suzuki, Natasha Dudek, David A. Relman, Kari M. Finstad, Ronald Amundson, Brian C. Thomas & Jillian F. Banfield in Nature Microbiology, Article number: 16048 (2016) doi:10.1038/nmicrobiol.2016.48

 

A reformatted view of the tree in Fig. 1in which each major lineage represents the same amount of evolutionary distance.
A reformatted view of the tree in Fig. 1in which each major lineage represents the same amount of evolutionary distance.

Carl Zimmer also has a nice little write up of the paper in today’s New York Times:

Carl Zimmer
in Scientists Unveil New ‘Tree of Life’ from The New York Times 4/11/16

 

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A new view of the tree of life was originally published on Chris Aldrich | Boffo Socko