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    <title>Pinboard (cshalizi)</title>
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    <description>recent bookmarks from cshalizi</description>
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	<rdf:li rdf:resource="https://journals.aps.org/pre/abstract/10.1103/PhysRevE.102.062410"/>
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	<rdf:li rdf:resource="http://press.princeton.edu/titles/11175.html"/>
	<rdf:li rdf:resource="http://www.pnas.org/content/114/30/7838.abstract"/>
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	<rdf:li rdf:resource="http://press.uchicago.edu/ucp/books/book/chicago/M/bo20952527"/>
	<rdf:li rdf:resource="http://press.princeton.edu/titles/10914.html"/>
	<rdf:li rdf:resource="http://www.pnas.org/content/113/34/9492.abstract.html"/>
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  </channel><item rdf:about="https://link.springer.com/article/10.1007/s10955-025-03533-7">
    <title>Branching with selection and mutation II: Mutant fitness of Gumbel type | Journal of Statistical Physics</title>
    <dc:date>2025-11-20T20:43:20+00:00</dc:date>
    <link>https://link.springer.com/article/10.1007/s10955-025-03533-7</link>
    <dc:creator>cshalizi</dc:creator><description><![CDATA["We study a model of a branching process subject to selection, modeled by giving each family an individual fitness acting as a branching rate, and mutation, modeled by resampling the fitness of a proportion of offspring in each generation. For two large classes of fitness distributions of Gumbel type we determine the growth of the population, almost surely on survival. We then study the empirical fitness distribution in a simplified model, which is numerically indistinguishable from the original model, and show the emergence of a Gaussian travelling wave."]]></description>
<dc:subject>to:NB branching_processes evolutionary_biology</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:cshalizi/b:dea55482dfcd/</dc:identifier>
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	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:branching_processes"/>
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<item rdf:about="https://www.science.org/doi/10.1126/science.adr2756?et_rid=40172509&amp;et_cid=5536942">
    <title>Experimental evolution of evolvability | Science</title>
    <dc:date>2025-09-05T16:17:24+00:00</dc:date>
    <link>https://www.science.org/doi/10.1126/science.adr2756?et_rid=40172509&amp;et_cid=5536942</link>
    <dc:creator>cshalizi</dc:creator><description><![CDATA["Can the capacity to evolve be selected by natural selection for greater ability to evolve? Barnett et al. designed experiments in which lineages of bacteria cycled between two selective environments (see the Perspective by Kussell). In response to changing conditions, a multistep evolutionary dynamic emerged in which selection first acts to elevate transcription rates at a single regulatory gene. An increase in frameshift mutations occurs at the same locus that also allows hitchhiking of secondary, possibly adaptive mutations. This phenomenon provides an evolutionary mechanism for increasing the capacity for evolvability toward specific adaptive outcomes. "]]></description>
<dc:subject>to:NB biology evolutionary_biology</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:cshalizi/b:d6137a6f9cd9/</dc:identifier>
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<item rdf:about="https://www.pnas.org/doi/10.1073/pnas.2413847122">
    <title>Reconciling ecology and evolutionary game theory or “When not to think cooperation” | PNAS</title>
    <dc:date>2025-04-22T15:32:57+00:00</dc:date>
    <link>https://www.pnas.org/doi/10.1073/pnas.2413847122</link>
    <dc:creator>cshalizi</dc:creator><description><![CDATA["Evolutionary game theory (EGT)—overwhelmingly employed today for the study of cooperation in various systems, from microbes to cancer and from insect to human societies—started with the seminal 1973 paper by Maynard Smith and Price showing that limited animal conflict can be selected at the individual level. Owing to the explanatory potential of this paper and enabled by the powerful machinery of the soon-to-be-developed replicator dynamics, EGT took off at an accelerated pace and began to shape expectations across systems and scales. But, even as EGT has expanded its reach, and even as its mathematical foundations expanded with the development of adaptive dynamics and inclusion of stochastic processes, the replicator equation remains, half a century later, its most widely used equation. Owing to its early development and its staying power, the replicator dynamics has helped set both the baseline expectations and the terminology of the field. However, much like the original 1973 paper, replicator dynamics rests on the assumption that individual differences in reproduction are determined only by the payoff from the game (i.e., in isolation, all individuals, regardless of their strategy, have identical intrinsic growth rates). Here, we argue that this assumption limits the scope of replicator dynamics to such an extent as to warrant not just a more deliberative application process, but also a reconsideration of the broad predictions and terminology that it has generated. Simultaneously, we reestablish a dialog with ecology that can be mutually fruitful, e.g., by providing an explanation for how diverse ecological communities can assemble evolutionarily."]]></description>
<dc:subject>to:NB evolutionary_biology evolutionary_game_theory ecology evolution_of_cooperation via:?</dc:subject>
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<dc:identifier>https://pinboard.in/u:cshalizi/b:3025bb8e6a9d/</dc:identifier>
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<item rdf:about="https://www.degruyter.com/document/doi/10.1515/9780691262406/html">
    <title>Evolution Evolving</title>
    <dc:date>2024-10-10T13:12:07+00:00</dc:date>
    <link>https://www.degruyter.com/document/doi/10.1515/9780691262406/html</link>
    <dc:creator>cshalizi</dc:creator><description><![CDATA["A new scientific view of evolution is emerging—one that challenges and expands our understanding of how evolution works. Recent research demonstrates that organisms differ greatly in how effective they are at evolving. Whether and how each organism adapts and diversifies depends critically on the mechanistic details of how that organism operates—its development, physiology, and behavior. That is because the evolutionary process itself has evolved over time, and continues to evolve. The scientific understanding of evolution is evolving too, with groundbreaking new ways of explaining evolutionary change. In this book, a group of leading biologists draw on the latest findings in evolutionary genetics and evo-devo, as well as novel insights from studies of epigenetics, symbiosis, and inheritance, to examine the central role that developmental processes play in evolution.
"Written in an accessible style, and illustrated with fascinating examples of natural history, the book presents recent scientific discoveries that expand evolutionary biology beyond the classical view of gene transmission guided by natural selection. Without undermining the central importance of natural selection and other Darwinian foundations, new developmental insights indicate that all organisms possess their own characteristic sets of evolutionary mechanisms. The authors argue that a consideration of developmental phenomena is needed for evolutionary biologists to generate better explanations for adaptation and biodiversity. This book provides a new vision of adaptive evolution."]]></description>
<dc:subject>in_NB books:noted evolutionary_biology developmental_biology evo-devo downloaded</dc:subject>
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<item rdf:about="https://www.prospectmagazine.co.uk/essays/59478/bill-hamilton">
    <title>Bill Hamilton (2003)</title>
    <dc:date>2023-11-16T16:50:56+00:00</dc:date>
    <link>https://www.prospectmagazine.co.uk/essays/59478/bill-hamilton</link>
    <dc:creator>cshalizi</dc:creator><dc:subject>have_read lives_of_the_scientists evolutionary_biology genetics hamilton.william psychoceramics</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:cshalizi/b:71f082ea431c/</dc:identifier>
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<item rdf:about="https://homicidallyinclinedpersonsofnofixedaddress.com/2023/05/28/more-gygaxs-finches/">
    <title>More Gygax’s Finches</title>
    <dc:date>2023-10-25T17:30:47+00:00</dc:date>
    <link>https://homicidallyinclinedpersonsofnofixedaddress.com/2023/05/28/more-gygaxs-finches/</link>
    <dc:creator>cshalizi</dc:creator><dc:subject>role-playing_games funny:geeky have_read evolutionary_biology</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:cshalizi/b:246204dab632/</dc:identifier>
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<item rdf:about="https://homicidallyinclinedpersonsofnofixedaddress.com/2023/04/20/gygaxs-finches/">
    <title>Gygax’s Finches</title>
    <dc:date>2023-10-25T17:29:57+00:00</dc:date>
    <link>https://homicidallyinclinedpersonsofnofixedaddress.com/2023/04/20/gygaxs-finches/</link>
    <dc:creator>cshalizi</dc:creator><dc:subject>role-playing_games evolutionary_biology funny:geeky have_read</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:cshalizi/b:df6ecad518fc/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:role-playing_games"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:evolutionary_biology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:funny:geeky"/>
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</item>
<item rdf:about="https://www.nature.com/articles/s41598-019-39558-8">
    <title>De novo origins of multicellularity in response to predation | Scientific Reports</title>
    <dc:date>2022-12-27T19:06:31+00:00</dc:date>
    <link>https://www.nature.com/articles/s41598-019-39558-8</link>
    <dc:creator>cshalizi</dc:creator><description><![CDATA["The transition from unicellular to multicellular life was one of a few major events in the history of life that created new opportunities for more complex biological systems to evolve. Predation is hypothesized as one selective pressure that may have driven the evolution of multicellularity. Here we show that de novo origins of simple multicellularity can evolve in response to predation. We subjected outcrossed populations of the unicellular green alga Chlamydomonas reinhardtii to selection by the filter-feeding predator Paramecium tetraurelia. Two of five experimental populations evolved multicellular structures not observed in unselected control populations within ~750 asexual generations. Considerable variation exists in the evolved multicellular life cycles, with both cell number and propagule size varying among isolates. Survival assays show that evolved multicellular traits provide effective protection against predation. These results support the hypothesis that selection imposed by predators may have played a role in some origins of multicellularity."

!!!?!]]></description>
<dc:subject>to_read evolutionary_biology evolution_of_complexity developmental_biology in_NB</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:cshalizi/b:330fe710e938/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:to_read"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:evolutionary_biology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:evolution_of_complexity"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:developmental_biology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:in_NB"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://www.biorxiv.org/content/10.1101/2022.07.02.498577v1">
    <title>The cost of information acquisition by natural selection | bioRxiv</title>
    <dc:date>2022-07-19T13:31:40+00:00</dc:date>
    <link>https://www.biorxiv.org/content/10.1101/2022.07.02.498577v1</link>
    <dc:creator>cshalizi</dc:creator><description><![CDATA["Natural selection enriches genotypes that are well-adapted to their environment. Over successive generations, these changes to the frequencies of types accumulate information about the selective conditions. Thus, we can think of selection as an algorithm by which populations acquire information about their environment. Kimura (1961) pointed out that every bit of information that the population gains this way comes with a minimum cost in terms of unrealized fitness (substitution load). Due to the gradual nature of selection and ongoing mismatch of types with the environment, a population that is still gaining information about the environment has lower mean fitness than a counter-factual population that already has this information. This has been an influential insight, but here we find that experimental evolution of Escherichia coli with mutations in a RNA polymerase gene (rpoB) violates Kimura’s basic theory. To overcome the restrictive assumptions of Kimura’s substitution load and develop a more robust measure for the cost of selection, we turn to ideas from computational learning theory. We reframe the ‘learning problem’ faced by an evolving population as a population versus environment (PvE) game, which can be applied to settings beyond Kimura’s theory – such as stochastic environments, frequency-dependent selection, and arbitrary environmental change. We show that the learning theoretic concept of ‘regret’ measures relative lineage fitness and rigorously captures the efficiency of selection as a learning process. This lets us establish general bounds on the cost of information acquisition by natural selection. We empirically validate these bounds in our experimental system, showing that computational learning theory can account for the observations that violate Kimura’s theory. Finally, we note that natural selection is a highly effective learning process in that selection is an asymptotically optimal algorithm for the problem faced by evolving populations, and no other algorithm can consistently outperform selection in general. Our results highlight the centrality of information to natural selection and the value of computational learning theory as a perspective on evolutionary biology."

--- Huh, I guess Haldane's measure of selection _is_ like a log-probability-loss.]]></description>
<dc:subject>to:NB to_read information_theory evolutionary_biology low-regret_learning bergstrom.carl_t. re:do-institutions-evolve</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:cshalizi/b:db39fe1ff713/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:to:NB"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:to_read"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:information_theory"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:evolutionary_biology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:low-regret_learning"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:bergstrom.carl_t."/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:re:do-institutions-evolve"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://press.uchicago.edu/ucp/books/book/chicago/P/bo45713172">
    <title>Phylogenetic Ecology: A History, Critique, and Remodeling, Swenson</title>
    <dc:date>2022-07-10T23:41:04+00:00</dc:date>
    <link>https://press.uchicago.edu/ucp/books/book/chicago/P/bo45713172</link>
    <dc:creator>cshalizi</dc:creator><description><![CDATA["Over the past decade, ecologists have increasingly embraced phylogenetics, the study of evolutionary relationships among species. As a result, they have come to discover the field’s power to illuminate present ecological patterns and processes. Ecologists are now investigating whether phylogenetic diversity is a better measure of ecosystem health than more traditional metrics like species diversity, whether it can predict the future structure and function of communities and ecosystems, and whether conservationists might prioritize it when formulating conservation plans.
"In Phylogenetic Ecology, Nathan G. Swenson synthesizes this nascent field’s major conceptual, methodological, and empirical developments to provide students and practicing ecologists with a foundational overview. Along the way, he highlights those realms of phylogenetic ecology that will likely increase in relevance—such as the burgeoning subfield of phylogenomics—and shows how ecologists might lean on these new perspectives to inform their research programs."]]></description>
<dc:subject>in_NB books:noted evolutionary_biology ecology books:suggest_to_library downloaded</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:cshalizi/b:42453c6bbffd/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:in_NB"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:books:noted"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:evolutionary_biology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:ecology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:books:suggest_to_library"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:downloaded"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://www-jstor-org.cmu.idm.oclc.org/stable/j.ctt16gzcs3?refreqid%3Dpub-view%253A176a702a9b7313b5a6a4f22654fc7b54">
    <title>The 7 Sexes: Biology of Sex Determination on JSTOR</title>
    <dc:date>2022-07-10T23:10:41+00:00</dc:date>
    <link>https://www-jstor-org.cmu.idm.oclc.org/stable/j.ctt16gzcs3?refreqid%3Dpub-view%253A176a702a9b7313b5a6a4f22654fc7b54</link>
    <dc:creator>cshalizi</dc:creator><description><![CDATA[Last tag is of course really "to have ready in my mind, in case the lecture on ascribed vs. achieved statuses gets into tricky territory".]]></description>
<dc:subject>books:noted evolutionary_biology developmental_biology sex_differences to_teach:statistics_of_inequality_and_discrimination downloaded to_teach:if_i_ever_really_need_to_get_cancelled in_NB</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:cshalizi/b:7f4ff2993876/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:books:noted"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:evolutionary_biology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:developmental_biology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:sex_differences"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:to_teach:statistics_of_inequality_and_discrimination"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:downloaded"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:to_teach:if_i_ever_really_need_to_get_cancelled"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:in_NB"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://oxford.universitypressscholarship.com/view/10.1093/oso/9780198832140.001.0001/oso-9780198832140?rskey=JBow6v&amp;result=466">
    <title>Evolutionary Parasitology: The Integrated Study of Infections, Immunology, Ecology, and Genetics - Oxford Scholarship</title>
    <dc:date>2022-07-03T15:40:28+00:00</dc:date>
    <link>https://oxford.universitypressscholarship.com/view/10.1093/oso/9780198832140.001.0001/oso-9780198832140?rskey=JBow6v&amp;result=466</link>
    <dc:creator>cshalizi</dc:creator><description><![CDATA["Parasites are ubiquitous and shape almost every aspect of their hosts, including physiology, behaviour, life histories, the structure of the microbiota, and entire communities. Hence, parasitism is one of the most potent forces in nature and, without parasites, the world would look very different. The book gives an overview over the parasite groups and the diversity of defences that hosts have evolved, such as immune systems. Principles of evolutionary biology and ecology analyse major elements of host–parasite interactions, including virulence, infection processes, tolerance, resistance, specificity, memory, polymorphisms, within-host dynamics, diseases spaces, and many other aspects. Genetics is always one of the key elements in these topics. Modelling, furthermore, can predict best strategies for host and parasites. Similarly, the spread of an infectious disease in epidemiology combines with molecular data and genomics. Furthermore, parasites have evolved ways to overcome defences and to manipulate their hosts. Hosts and parasites, therefore, continuously co-evolve, with changes sometimes occurring very rapidly, and sometimes requiring geological times. Many infectious diseases of humans have emerged from a zoonotic origin, in processes governed by the basic principles discussed in the different sections. Hence, this book integrates different fields to study the diversity of host–parasite processes and phenomena. It summarizes the essential topics for the study of evolutionary parasitology and will be useful for a broad audience."]]></description>
<dc:subject>in_NB books:noted evolutionary_biology parasites to_download</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:cshalizi/b:87f8d64d76c0/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:in_NB"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:books:noted"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:evolutionary_biology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:parasites"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:to_download"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://www.cambridge.org/core/books/failures-of-mathematical-antievolutionism/A95C44708846F7439E7997D5832E2241#fndtn-information">
    <title>The Failures of Mathematical Anti-Evolutionism</title>
    <dc:date>2022-07-03T02:51:00+00:00</dc:date>
    <link>https://www.cambridge.org/core/books/failures-of-mathematical-antievolutionism/A95C44708846F7439E7997D5832E2241#fndtn-information</link>
    <dc:creator>cshalizi</dc:creator><description><![CDATA["Anti-scientific misinformation has become a serious problem on many fronts, including vaccinations and climate change. One of these fronts is the persistence of anti-evolutionism, which has recently been given a superficially professional gloss in the form of the intelligent design movement. Far from solely being of interest to researchers in biology, anti-evolutionism must be recognized as part of a broader campaign with a conservative religious and political agenda. Much of the rhetorical effectiveness of anti-evolutionism comes from its reliance on seemingly precise mathematical arguments. This book, the first of its kind to be written by a mathematician, discusses and refutes these arguments. Along the way, it also clarifies common misconceptions about both biology and mathematics. Both lay audiences and professionals will find the book to be accessible and informative."]]></description>
<dc:subject>to:NB books:noted debunking evolutionary_biology creationism mathematics</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:cshalizi/b:377b3d98a8b9/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:to:NB"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:books:noted"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:debunking"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:evolutionary_biology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:creationism"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:mathematics"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://arxiv.org/abs/2206.02279">
    <title>[2206.02279] Assembly Theory Explains and Quantifies the Emergence of Selection and Evolution</title>
    <dc:date>2022-06-09T08:39:12+00:00</dc:date>
    <link>https://arxiv.org/abs/2206.02279</link>
    <dc:creator>cshalizi</dc:creator><description><![CDATA["Since the time of Darwin, scientists have struggled to reconcile the evolution of biological forms in a universe determined by fixed laws. These laws underpin the origin of life, evolution, human culture and technology, as set by the boundary conditions of the universe, however these laws cannot predict the emergence of these things. By contrast evolutionary theory works in the opposite direction, indicating how selection can explain why some things exist and not others. To understand how open-ended forms can emerge in a forward-process from physics that does not include their design, a new approach to understand the non-biological to biological transition is necessary. Herein, we present a new theory, Assembly Theory (AT), which explains and quantifies the emergence of selection and evolution. In AT, the complexity of an individual observable object is measured by its Assembly Index (a), defined as the minimal number of steps needed to construct the object from basic building blocks. Combining a with the copy number defines a new quantity called Assembly which quantifies the amount of selection required to produce a given ensemble of objects. We investigate the internal structure and properties of assembly space and quantify the dynamics of undirected exploratory processes as compared to the directed processes that emerge from selection. The implementation of assembly theory allows the emergence of selection in physical systems to be quantified at any scale as the transition from undirected-discovery dynamics to a selected process within the assembly space. This yields a mechanism for the onset of selection and evolution and a formal approach to defining life. Because the assembly of an object is easily calculatable and measurable it is possible to quantify a lower limit on the amount of selection and memory required to produce complexity uniquely linked to biology in the universe."]]></description>
<dc:subject>evolutionary_biology complexity complexity_measures lachmann.michael kith_and_kin in_NB</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:cshalizi/b:ce0d1ead4858/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:evolutionary_biology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:complexity"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:complexity_measures"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:lachmann.michael"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:kith_and_kin"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:in_NB"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://doi.org/10.1093/beheco/arab137">
    <title>nature of privilege: intergenerational wealth in animal societies | Behavioral Ecology | Oxford Academic</title>
    <dc:date>2022-01-10T21:15:13+00:00</dc:date>
    <link>https://doi.org/10.1093/beheco/arab137</link>
    <dc:creator>cshalizi</dc:creator><description><![CDATA["Wealth inequality is widespread across human societies, from pastoral and small-scale agricultural groups to large modern social structures. The intergenerational transfer of wealth privileges some individuals over others through the transmission of resources external to an individual organism. Privileged access to household wealth (e.g., land, shelter, silver) positively influences the destinies of some (and their descendants) over others in human societies. Strikingly parallel phenomena exist in animal societies. Inheritance of nongenetic commodities (e.g., a nest, territory, tool) external to an individual also contributes greatly to direct fitness in animals. Here, we illustrate the evolutionary diversity of privilege and its disparity-generating effects on the evolutionary trajectories of lineages across the Tree of Life. We propose that integration of approaches used to study these patterns in humans may offer new insights into a core principle from behavioral ecology—differential access to inherited resources—and help to establish a broad, comparative framework for studying inequality in animals."]]></description>
<dc:subject>inequality transmission_of_inequality ecology evolutionary_biology to_teach:statistics_of_inequality_and_discrimination via:yorksranter in_NB</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:cshalizi/b:8f038b483605/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:inequality"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:transmission_of_inequality"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:ecology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:evolutionary_biology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:to_teach:statistics_of_inequality_and_discrimination"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:via:yorksranter"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:in_NB"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://www.theatlantic.com/science/archive/2015/09/parasitic-wasps-genetically-engineer-caterpillars-domesticated-viruses/405874/">
    <title>Parasitic Wasps Genetically Engineer Caterpillars Using Domesticated Viruses - The Atlantic</title>
    <dc:date>2021-08-06T05:34:30+00:00</dc:date>
    <link>https://www.theatlantic.com/science/archive/2015/09/parasitic-wasps-genetically-engineer-caterpillars-domesticated-viruses/405874/</link>
    <dc:creator>cshalizi</dc:creator><dc:subject>evolutionary_biology insects viruses parasite_porn</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:cshalizi/b:aa93a6b27e8c/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:evolutionary_biology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:insects"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:viruses"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:parasite_porn"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://arxiv.org/abs/2106.16201">
    <title>[2106.16201] Evolving genealogies for branching populations under selection and competition</title>
    <dc:date>2021-07-01T15:50:53+00:00</dc:date>
    <link>https://arxiv.org/abs/2106.16201</link>
    <dc:creator>cshalizi</dc:creator><description><![CDATA["For a continuous state branching process with two types of individuals which are subject to selection and density dependent competition, we characterize the joint evolution of population size, type configurations and genealogies as the unique strong solution of a system of SDE's. Our construction is achieved in the lookdown framework and provides a synthesis as well as a generalization of cases considered separately in two seminal papers by Donnelly and Kurtz (1999), namely fluctuating population sizes under neutrality, and selection with constant population size. As a conceptual core in our approach, we introduce the selective lookdown space which is obtained from its neutral counterpart through a state-dependent thinning of "potential" selection/competition events whose rates interact with the evolution of the type densities. The updates of the genealogical distance matrix at the "active" selection/competition events are obtained through an appropriate sampling from the selective lookdown space. The solution of the above mentioned system of SDE's is then mapped into the joint evolution of population size and symmetrized type configurations and genealogies, i.e. marked distance matrix distributions. By means of Kurtz's Markov mapping theorem, we characterize the latter process as the unique solution of a martingale problem. For the sake of transparency we restrict the main part of our presentation to a prototypical example with two types, which contains the essential features. In the final section we outline an extension to processes with multiple types including mutation."]]></description>
<dc:subject>to:NB evolutionary_biology branching_processes stochastic_processes</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:cshalizi/b:f8347b059c16/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:to:NB"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:evolutionary_biology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:branching_processes"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:stochastic_processes"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://press.uchicago.edu/ucp/books/book/chicago/C/bo22982546">
    <title>Catastrophic Thinking: Extinction and the Value of Diversity from Darwin to the Anthropocene, Sepkoski</title>
    <dc:date>2021-06-28T03:18:57+00:00</dc:date>
    <link>https://press.uchicago.edu/ucp/books/book/chicago/C/bo22982546</link>
    <dc:creator>cshalizi</dc:creator><description><![CDATA["We live in an age in which we are repeatedly reminded—by scientists, by the media, by popular culture—of the looming threat of mass extinction. We’re told that human activity is currently producing a sixth mass extinction, perhaps of even greater magnitude than the five previous geological catastrophes that drastically altered life on Earth. Indeed, there is a very real concern that the human species may itself be poised to go the way of the dinosaurs, victims of the most recent mass extinction some 65 million years ago.
"How we interpret the causes and consequences of extinction and their ensuing moral imperatives is deeply embedded in the cultural values of any given historical moment. And, as David Sepkoski reveals, the history of scientific ideas about extinction over the past two hundred years—as both a past and a current process—is implicated in major changes in the way Western society has approached biological and cultural diversity. It seems self-evident to most of us that diverse ecosystems and societies are intrinsically valuable, but the current fascination with diversity is a relatively recent phenomenon. In fact, the way we value diversity depends crucially on our sense that it is precarious—that it is something actively threatened, and that its loss could have profound consequences. In Catastrophic Thinking, Sepkoski uncovers how and why we learned to value diversity as a precious resource at the same time as we learned to think catastrophically about extinction."]]></description>
<dc:subject>to:NB books:noted history_of_ideas evolutionary_biology diversity extinction books:suggest_to_library</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:cshalizi/b:b64e4a39db55/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:to:NB"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:books:noted"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:history_of_ideas"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:evolutionary_biology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:diversity"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:extinction"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:books:suggest_to_library"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://arxiv.org/abs/2106.03667">
    <title>[2106.03667] Acceleration of Evolutionary Processes by Learning and Extended Fisher's Fundamental Theorem</title>
    <dc:date>2021-06-10T02:02:41+00:00</dc:date>
    <link>https://arxiv.org/abs/2106.03667</link>
    <dc:creator>cshalizi</dc:creator><description><![CDATA["Natural selection is general and powerful concept not only to explain evolutionary processes of biological organisms but also to design engineering systems such as genetic algorithms and particle filters. There is a surge of interest, both from biology and engineering, in considering natural selection of intellectual agents that can learn individually. Learning by individual agents of better behaviors for survival may accelerate the evolutionary processes by natural selection. We have accumulating pieces of evidence that organisms can transmit its information to the next generation via epigenetic states or memes. Also, such idea is important for engineering applications. To accelerate the evolutionary process, an agent should change their strategy so that the population fitness increases the most. Equivalently, an agent should update the strategy towards a gradient of the population fitness. However, it has not yet been clarified whether and how an agent can estimate the gradient and accelerate the evolutionary process. We also lack methodology to quantify the acceleration to understand and predict the impact of learning. In this paper, we address these problems. We show that an learning agent can accelerate the evolutionary process by proposing ancestral learning, which uses the information transmitted from the ancestor (ancestral information). We next show that the ancestral information is sufficient to estimate the gradient. In particular, learning can accelerate the evolutionary process without communications between agents. Finally, to quantify the acceleration, we extend the Fisher's fundamental theorem (FF-thm) for natural selection to ancestral learning. Our extended FF-thm relates the acceleration of the evolutionary process to the variety of individual fitness of the agent. By the theorem, we can quantitatively understand when and why learning is beneficial."]]></description>
<dc:subject>to:NB evolutionary_biology learning_in_games baldwin_effect</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:cshalizi/b:71187ea1d135/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:to:NB"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:evolutionary_biology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:learning_in_games"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:baldwin_effect"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://journals.aps.org/pre/abstract/10.1103/PhysRevE.103.052408">
    <title>Phys. Rev. E 103, 052408 (2021) - Mechanisms underlying vaccination protocols that may optimally elicit broadly neutralizing antibodies against highly mutable pathogens</title>
    <dc:date>2021-05-18T20:00:30+00:00</dc:date>
    <link>https://journals.aps.org/pre/abstract/10.1103/PhysRevE.103.052408</link>
    <dc:creator>cshalizi</dc:creator><description><![CDATA["Effective prophylactic vaccines usually induce the immune system to generate potent antibodies that can bind to an antigen and thus prevent it from infecting host cells. B cells produce antibodies by a Darwinian evolutionary process called affinity maturation (AM). During AM, the B cell population evolves in response to the antigen to produce antibodies that bind specifically and strongly to the antigen. Highly mutable pathogens pose a major challenge to the development of effective vaccines because antibodies that are effective against one strain of the virus may not protect against a mutant strain. Antibodies that can protect against diverse strains of a mutable pathogen have high “breadth” and are called broadly neutralizing antibodies (bnAbs). In spite of extensive studies, an effective vaccination strategy that can generate bnAbs in humans does not exist for any highly mutable pathogen. Here we study a minimal model to explore the mechanisms underlying how the selection forces imposed by antigens can be optimally chosen to guide AM to maximize the evolution of bnAbs. For logistical reasons, only a finite number of antigens can be administered in a finite number of vaccinations; that is, guiding the nonequilibrium dynamics of AM to produce bnAbs must be accomplished nonadiabatically. The time-varying Kullback-Leibler divergence (KLD) between the existing B cell population distribution and the fitness landscape imposed by antigens is a quantitative metric of the thermodynamic force acting on B cells. If this force is too small, adaptation is minimal. If the force is too large, contrary to expectations, adaptation is not faster; rather, the B cell population is extinguished for reasons that we describe. We define the conditions necessary for the force to be set optimally such that the flux of B cells from low to high breadth states is maximized. Even in this case we show why the dynamics of AM prevent perfect adaptation. If two shots of vaccination are allowed, the optimal protocol is characterized by a relatively low optimal KLD during the first shot that appropriately increases the diversity of the B cell population so that the surviving B cells have a high chance of evolving into bnAbs upon subsequently increasing the KLD during the second shot. Phylogenetic tree analysis further reveals the evolutionary pathways that lead to bnAbs. The connections between the mechanisms revealed by our analyses and recent simulation studies of bnAb evolution, the problem of generalist versus specialist evolution, and learning theory are discussed."]]></description>
<dc:subject>to:NB evolutionary_biology immunology information_theory re:fitness_sampling</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:cshalizi/b:3939038e9753/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:to:NB"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:evolutionary_biology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:immunology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:information_theory"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:re:fitness_sampling"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://arxiv.org/abs/2105.05520">
    <title>[2105.05520] Simulating short- and long-term evolutionary dynamics on rugged landscapes</title>
    <dc:date>2021-05-13T14:18:41+00:00</dc:date>
    <link>https://arxiv.org/abs/2105.05520</link>
    <dc:creator>cshalizi</dc:creator><description><![CDATA["We propose a minimal model to simulate long waiting times followed by evolutionary bursts on rugged landscapes. It combines point and inversions-like mutations as sources of genetic variation. The inversions are intended to simulate one of the main chromosomal rearrangements. Using the well-known family of NK fitness landscapes, we simulate random adaptive walks, i.e. successive mutational events constrained to incremental fitness selection. We report the emergence of different time scales: a short-term dynamics mainly driven by point mutations, followed by a long-term (stasis-like) waiting period until a new mutation arises. This new mutation is an inversion which can trigger a burst of successive point mutations, and then drives the system to new short-term increasing-fitness period. We analyse the effect of genes epistatic interactions on the evolutionary time scales. We suggest that the present model mimics the process of evolutionary innovation and punctuated equilibrium."

--- Arxiv seems determined to serve up blasts from the past today...]]></description>
<dc:subject>to:NB nk_model evolutionary_biology re:do-institutions-evolve</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:cshalizi/b:0b41513b21b7/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:to:NB"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:nk_model"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:evolutionary_biology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:re:do-institutions-evolve"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://www.nature.com/articles/d41586-021-00977-1">
    <title>Life in a carbon dioxide world</title>
    <dc:date>2021-04-24T20:39:46+00:00</dc:date>
    <link>https://www.nature.com/articles/d41586-021-00977-1</link>
    <dc:creator>cshalizi</dc:creator><dc:subject>biochemical_networks evolutionary_biology via:paul_mcauley have_read</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:cshalizi/b:15719c0774da/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:biochemical_networks"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:evolutionary_biology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:via:paul_mcauley"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:have_read"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://science.sciencemag.org/content/372/6540/412?rss=1">
    <title>Timing the SARS-CoV-2 index case in Hubei province | Science</title>
    <dc:date>2021-04-23T03:01:54+00:00</dc:date>
    <link>https://science.sciencemag.org/content/372/6540/412?rss=1</link>
    <dc:creator>cshalizi</dc:creator><description><![CDATA["Understanding when severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged is critical to evaluating our current approach to monitoring novel zoonotic pathogens and understanding the failure of early containment and mitigation efforts for COVID-19. We used a coalescent framework to combine retrospective molecular clock inference with forward epidemiological simulations to determine how long SARS-CoV-2 could have circulated before the time of the most recent common ancestor of all sequenced SARS-CoV-2 genomes. Our results define the period between mid-October and mid-November 2019 as the plausible interval when the first case of SARS-CoV-2 emerged in Hubei province, China. By characterizing the likely dynamics of the virus before it was discovered, we show that more than two-thirds of SARS-CoV-2–like zoonotic events would be self-limited, dying out without igniting a pandemic. Our findings highlight the shortcomings of zoonosis surveillance approaches for detecting highly contagious pathogens with moderate mortality rates."]]></description>
<dc:subject>to:NB evolutionary_biology coronavirus_pandemic_of_2019-- plagues_and_peoples</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:cshalizi/b:6aaa3f221600/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:to:NB"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:evolutionary_biology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:coronavirus_pandemic_of_2019--"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:plagues_and_peoples"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://arxiv.org/abs/2104.10191">
    <title>[2104.10191] Extinction in complex communities as driven by adaptive dynamics</title>
    <dc:date>2021-04-22T15:30:56+00:00</dc:date>
    <link>https://arxiv.org/abs/2104.10191</link>
    <dc:creator>cshalizi</dc:creator><description><![CDATA["In a complex community, species continuously adapt to each other. On rare occasions, the adaptation of a species can lead to the extinction of others, and even its own. "Adaptive dynamics" is the standard mathematical framework to describe evolutionary changes in community interactions, and in particular, predict adaptation driven extinction. Unfortunately, most authors implement the equations of adaptive dynamics through computer simulations, that require assuming a large number of questionable parameters and fitness functions. In this study we present analytical solutions to adaptive dynamics equations, thereby clarifying how outcomes depend on any computational input. We develop general formulas that predict equilibrium abundances over evolutionary time scales. Additionally, we predict which species will go extinct next, and when this will happen."]]></description>
<dc:subject>to:NB evolutionary_biology ecology re:do-institutions-evolve</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:cshalizi/b:1a66797cc0a5/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:to:NB"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:evolutionary_biology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:ecology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:re:do-institutions-evolve"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://arxiv.org/abs/2104.10427">
    <title>[2104.10427] Dynamics of lineages in adaptation to a gradual environmental change</title>
    <dc:date>2021-04-22T15:24:35+00:00</dc:date>
    <link>https://arxiv.org/abs/2104.10427</link>
    <dc:creator>cshalizi</dc:creator><description><![CDATA["We investigate a simple quantitative genetics model subjet to a gradual environmental change from the viewpoint of the phylogenies of the living individuals. We aim to understand better how the past traits of their ancestors are shaped by the adaptation to the varying environment. The individuals are characterized by a one-dimensional trait. The dynamics -- births and deaths -- depend on a time-changing mortality rate that shifts the optimal trait to the right at constant speed. The population size is regulated by a nonlinear non-local logistic competition term. The macroscopic behaviour can be described by a PDE that admits a unique positive stationary solution. In the stationary regime, the population can persist, but with a lag in the trait distribution due to the environmental change. For the microscopic (individual-based) stochastic process, the evolution of the lineages can be traced back using the historical process, that is, a measure-valued process on the set of continuous real functions of time. Assuming stationarity of the trait distribution, we describe the limiting distribution, in large populations, of the path of an individual drawn at random at a given time T. Freezing the non-linearity due to competition allows the use of a many-to-one identity together with Feynman-Kac's formula. This path, in reversed time, remains close to a simple Ornstein-Uhlenbeck process. It shows how the lagged bulk of the present population stems from ancestors once optimal in trait but still in the tail of the trait distribution in which they lived."

--- A model for historical lag?]]></description>
<dc:subject>to:NB evolutionary_biology branching_processes stochastic_processes re:do-institutions-evolve to_read</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:cshalizi/b:05fecae67d7b/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:to:NB"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:evolutionary_biology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:branching_processes"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:stochastic_processes"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:re:do-institutions-evolve"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:to_read"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://journals.aps.org/pre/abstract/10.1103/PhysRevE.103.042415">
    <title>Phys. Rev. E 103, 042415 (2021) - Robustness and predictability of evolution in bottlenecked populations</title>
    <dc:date>2021-04-21T16:12:13+00:00</dc:date>
    <link>https://journals.aps.org/pre/abstract/10.1103/PhysRevE.103.042415</link>
    <dc:creator>cshalizi</dc:creator><description><![CDATA["Deterministic and stochastic evolutionary processes drive adaptation in natural populations. The strength of each component process is determined by the population size: deterministic components prevail in very large populations, while stochastic components are the driving mechanisms in small ones. Many natural populations, however, experience intermittent periods of growth, moving through states in which either stochastic or deterministic processes prevail. This growth is often countered by population bottlenecks, which abound in both natural and laboratory populations. Here we investigate how population bottlenecks shape the process of adaptation. We demonstrate that adaptive trajectories in populations experiencing regular bottlenecks can be naturally scaled in time units of generations; with this scaling the time courses of adaptation, fitness variance, and genetic diversity all become relatively insensitive to the timing of population bottlenecks, provided the bottleneck size exceeds a few thousand individuals. We also include analyses at the genotype level to investigate the impact of population bottlenecks on the predictability and distribution of evolutionary pathways. Irrespective of the timing of population bottlenecks, we find that predictability increases with population size. We also find that predictability of the adaptive pathways increases in increasingly rugged fitness landscapes. Overall, our work reveals that both the adaptation rate and the predictability of evolutionary trajectories are relatively robust to population bottlenecks."]]></description>
<dc:subject>to:NB evolutionary_biology stochastic_processes re:do-institutions-evolve</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:cshalizi/b:39dbecc3aed4/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:to:NB"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:evolutionary_biology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:stochastic_processes"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:re:do-institutions-evolve"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://arxiv.org/abs/2104.03406">
    <title>[2104.03406] Evolutionary rates of information gain and decay in fluctuating environments</title>
    <dc:date>2021-04-10T04:27:39+00:00</dc:date>
    <link>https://arxiv.org/abs/2104.03406</link>
    <dc:creator>cshalizi</dc:creator><description><![CDATA["In this paper, we wish to investigate the dynamics of information transfer in evolutionary dynamics. We use information theoretic tools to track how much information an evolving population has obtained and managed to retain about different environments that it is exposed to. By understanding the dynamics of information gain and loss in a static environment, we predict how that same evolutionary system would behave when the environment is fluctuating. Specifically, we anticipate a cross-over between the regime in which fluctuations improve the ability of the evolutionary system to capture environmental information and the regime in which the fluctuations inhibit it, governed by a cross-over in the timescales of information gain and decay."]]></description>
<dc:subject>to:NB evolutionary_biology information_theory re:do-institutions-evolve</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:cshalizi/b:3787235c775c/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:to:NB"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:evolutionary_biology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:information_theory"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:re:do-institutions-evolve"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://doi.org/10.1093/oso/9780195125689.001.0001">
    <title>Brains Through Time: A Natural History of Vertebrates - Oxford Scholarship</title>
    <dc:date>2021-01-16T06:14:35+00:00</dc:date>
    <link>https://doi.org/10.1093/oso/9780195125689.001.0001</link>
    <dc:creator>cshalizi</dc:creator><description><![CDATA["Much is conserved in vertebrate evolution, but significant changes in the nervous system occurred at the origin of vertebrates and in most of the major vertebrate lineages. This book examines these innovations and relates them to evolutionary changes in other organ systems, animal behavior, and ecological conditions at the time. The resulting perspective clarifies what makes the major vertebrate lineages unique and helps explain their varying degrees of ecological success. One of the book’s major conclusions is that vertebrate nervous systems are more diverse than commonly assumed, at least among neurobiologists. Examples of important innovations include not only the emergence of novel brain regions, such as the cerebellum and neocortex, but also major changes in neuronal circuitry and functional organization. A second major conclusion is that many of the apparent similarities in vertebrate nervous systems resulted from convergent evolution, rather than inheritance from a common ancestor. For example, brain size and complexity increased numerous times, in many vertebrate lineages. In conjunction with these changes, olfactory inputs to the telencephalic pallium were reduced in several different lineages, and this reduction was associated with the emergence of pallial regions that process non-olfactory sensory inputs. These conclusions cast doubt on the widely held assumption that all vertebrate nervous systems are built according to a single, common plan. Instead, the book encourages readers to view both species similarities and differences as fundamental to a comprehensive understanding of nervous systems."]]></description>
<dc:subject>to:NB books:noted evolutionary_biology neuroscience</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:cshalizi/b:806bc84161dc/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:to:NB"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:books:noted"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:evolutionary_biology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:neuroscience"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://arxiv.org/abs/2010.06025">
    <title>[2010.06025] The replicator equation in stochastic spatial evolutionary games</title>
    <dc:date>2021-01-14T15:53:19+00:00</dc:date>
    <link>https://arxiv.org/abs/2010.06025</link>
    <dc:creator>cshalizi</dc:creator><description><![CDATA["We study the multi-strategy stochastic evolutionary game with death-birth updating in expanding spatial populations of size N→∞. The model is a voter model perturbation. For typical populations, we require perturbation strengths satisfying 1/N≪w≪1. Under appropriate conditions on the space, the limiting density processes of strategy are proven to obey the replicator equation, and the normalized fluctuations converge to a Gaussian process with the Wright-Fisher covariance function in the limiting densities. As an application, we resolve in the positive a conjecture from the biological literature that the expected density processes approximate the replicator equation on many non-regular graphs."]]></description>
<dc:subject>to:NB evolutionary_biology replicator_dynamics macro_from_micro re:do-institutions-evolve stochastic_processes</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:cshalizi/b:304c6af14fe6/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:to:NB"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:evolutionary_biology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:replicator_dynamics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:macro_from_micro"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:re:do-institutions-evolve"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:stochastic_processes"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://www.cambridge.org/core/journals/evolutionary-human-sciences/article/fitnessmaximizers-employ-pessimistic-probability-weighting-for-decisions-under-risk/FCF743180A566332C8AF9F7E7406AB43">
    <title>Fitness-maximizers employ pessimistic probability weighting for decisions under risk | Evolutionary Human Sciences | Cambridge Core</title>
    <dc:date>2020-12-16T19:47:18+00:00</dc:date>
    <link>https://www.cambridge.org/core/journals/evolutionary-human-sciences/article/fitnessmaximizers-employ-pessimistic-probability-weighting-for-decisions-under-risk/FCF743180A566332C8AF9F7E7406AB43</link>
    <dc:creator>cshalizi</dc:creator><description><![CDATA["The standard theory of rationality posits that agents order preferences according to average utilities associated with different choices. Expected utility theory has repeatedly failed as a predictive theory, as reflected in a growing literature in behavioural economics. Evolutionary theorists have suggested that seemingly irrational behaviours in contemporary contexts may have once served important functions, but existing work linking fitness and choice has not adequately addressed the challenges of constructing an evolutionary theory of decision making. In particular, fitness itself is not a reasonable metric for decision making since its timescale exceeds the lifespan of the decision-maker. Consequently, organisms use proximate systems that work on appropriate timescales and are amenable to feedback and learning. We develop an evolutionary principal–agent model in which individuals utilize a set of proximal choice variables to account for the non-linear dependence of these variables on consumption. While this is insufficient to maximize fitness in the presence of environmental stochasticity, maximum fitness can be achieved by adopting pessimistic probability weightings compatible with the rank-dependent expected utility family of choice models. In particular, pessimistic probability weighting emerges naturally in an evolutionary framework because of extreme intolerance to zeros in multiplicative growth processes."

--- Kelly gambling FTW?

]]></description>
<dc:subject>to:NB decision-making decision_theory evolutionary_biology evolution_of_cognition</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:cshalizi/b:375d11c1ccb8/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:to:NB"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:decision-making"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:decision_theory"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:evolutionary_biology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:evolution_of_cognition"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://journals.aps.org/pre/abstract/10.1103/PhysRevE.102.062410">
    <title>Phys. Rev. E 102, 062410 (2020) - Taming the diffusion approximation through a controlling-factor WKB method</title>
    <dc:date>2020-12-12T15:50:07+00:00</dc:date>
    <link>https://journals.aps.org/pre/abstract/10.1103/PhysRevE.102.062410</link>
    <dc:creator>cshalizi</dc:creator><description><![CDATA["The diffusion approximation (DA) is widely used in the analysis of stochastic population dynamics, from population genetics to ecology and evolution. The DA is an uncontrolled approximation that assumes the smoothness of the calculated quantity over the relevant state space and fails when this property is not satisfied. This failure becomes severe in situations where the direction of selection switches sign. Here we employ the WKB (Wentzel-Kramers-Brillouin) large-deviations method, which requires only the logarithm of a given quantity to be smooth over its state space. Combining the WKB scheme with asymptotic matching techniques, we show how to derive the diffusion approximation in a controlled manner and how to produce better approximations, applicable for much wider regimes of parameters. We also introduce a scalable (independent of population size) WKB-based numerical technique. The method is applied to a central problem in population genetics and evolution, finding the chance of ultimate fixation in a zero-sum, two-types competition."]]></description>
<dc:subject>to:NB large_deviations convergence_of_stochastic_processes stochastic_differential_equations evolutionary_biology re:do-institutions-evolve to_read</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:cshalizi/b:d7936a2543e5/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:to:NB"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:large_deviations"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:convergence_of_stochastic_processes"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:stochastic_differential_equations"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:evolutionary_biology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:re:do-institutions-evolve"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:to_read"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://arxiv.org/abs/2007.00096">
    <title>[2007.00096] Simple conditions for convergence of sequential Monte Carlo genealogies with applications</title>
    <dc:date>2020-12-09T15:21:10+00:00</dc:date>
    <link>https://arxiv.org/abs/2007.00096</link>
    <dc:creator>cshalizi</dc:creator><description><![CDATA["We present simple conditions under which the limiting genealogical process associated with a class of interacting particle systems with non-neutral selection mechanisms, as the number of particles grows, is a time-rescaled Kingman coalescent. Sequential Monte Carlo algorithms are popular methods for approximating integrals in problems such as non-linear filtering and smoothing which employ this type of particle system. Their performance depends strongly on the properties of the induced genealogical process. We verify the conditions of our main result for standard sequential Monte Carlo algorithms with a broad class of low-variance resampling schemes, as well as for conditional sequential Monte Carlo with multinomial resampling."]]></description>
<dc:subject>to:NB particle_filters evolutionary_biology stochastic_processes</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:cshalizi/b:e303aa09560d/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:to:NB"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:particle_filters"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:evolutionary_biology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:stochastic_processes"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://arxiv.org/abs/2012.02734">
    <title>[2012.02734] Universal constraints on selection strength in lineage trees</title>
    <dc:date>2020-12-07T15:10:38+00:00</dc:date>
    <link>https://arxiv.org/abs/2012.02734</link>
    <dc:creator>cshalizi</dc:creator><description><![CDATA["We obtain general inequalities constraining the difference between the average of an arbitrary function of a phenotypic trait, which includes the fitness landscape of the trait itself, in the presence or in the absence of natural selection. These inequalities imply bounds on the strength of selection, which can be measured from the statistics of traits or divisions along lineages. The upper bound is related to recent generalizations of linear response relations in Stochastic Thermodynamics, and is reminiscent of the fundamental theorem of Natural selection of R. Fisher and of its generalization by Price. The lower bound follows from recent improvements on Jensen inequality and is typically less tight than the upper bound. We illustrate our results using numerical simulations of growing cell colonies and with experimental data of time-lapse microscopy experiments of bacteria cell colonies."]]></description>
<dc:subject>to:NB evolutionary_biology color_me_skeptical</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:cshalizi/b:b783d906fb20/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:to:NB"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:evolutionary_biology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:color_me_skeptical"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://www.quantamagazine.org/how-jurassic-plankton-stole-control-of-the-oceans-chemistry-20191001/">
    <title>How Jurassic Plankton Stole Control of the Ocean’s Chemistry | Quanta Magazine</title>
    <dc:date>2020-11-27T05:35:55+00:00</dc:date>
    <link>https://www.quantamagazine.org/how-jurassic-plankton-stole-control-of-the-oceans-chemistry-20191001/</link>
    <dc:creator>cshalizi</dc:creator><dc:subject>paleontology ecology evolutionary_biology climatology</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:cshalizi/b:e021dc96347d/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:paleontology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:ecology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:evolutionary_biology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:climatology"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://www.nature.com/articles/d41586-019-03061-x">
    <title>How evolution builds genes from scratch</title>
    <dc:date>2020-11-27T05:22:58+00:00</dc:date>
    <link>https://www.nature.com/articles/d41586-019-03061-x</link>
    <dc:creator>cshalizi</dc:creator><dc:subject>evolutionary_biology genetics</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:cshalizi/b:affc7ba3a9cc/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:evolutionary_biology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:genetics"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://www.tandfonline.com/doi/full/10.1080/01621459.2020.1799812">
    <title>Inferring Phenotypic Trait Evolution on Large Trees With Many Incomplete Measurements: Journal of the American Statistical Association: Vol 0, No 0</title>
    <dc:date>2020-11-20T15:32:51+00:00</dc:date>
    <link>https://www.tandfonline.com/doi/full/10.1080/01621459.2020.1799812</link>
    <dc:creator>cshalizi</dc:creator><description><![CDATA["Comparative biologists are often interested in inferring covariation between multiple biological traits sampled across numerous related taxa. To properly study these relationships, we must control for the shared evolutionary history of the taxa to avoid spurious inference. An additional challenge arises as obtaining a full suite of measurements becomes increasingly difficult with increasing taxa. This generally necessitates data imputation or integration, and existing control techniques typically scale poorly as the number of taxa increases. We propose an inference technique that integrates out missing measurements analytically and scales linearly with the number of taxa by using a post-order traversal algorithm under a multivariate Brownian diffusion (MBD) model to characterize trait evolution. We further exploit this technique to extend the MBD model to account for sampling error or nonheritable residual variance. We test these methods to examine mammalian life history traits, prokaryotic genomic and phenotypic traits, and HIV infection traits. We find computational efficiency increases that top two orders-of-magnitude over current best practices. While we focus on the utility of this algorithm in phylogenetic comparative methods, our approach generalizes to solve long-standing challenges in computing the likelihood for matrix-normal and multivariate normal distributions with missing data at scale. Supplementary materials for this article are available online."

]]></description>
<dc:subject>to:NB phylogenetics missing_data statistics evolutionary_biology</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:cshalizi/b:e56d48899371/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:to:NB"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:phylogenetics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:missing_data"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:evolutionary_biology"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://www.nature.com/articles/d41586-020-01021-4">
    <title>Evolutionary trees can’t reveal speciation and extinction rates</title>
    <dc:date>2020-07-15T15:05:41+00:00</dc:date>
    <link>https://www.nature.com/articles/d41586-020-01021-4</link>
    <dc:creator>cshalizi</dc:creator><dc:subject>to:NB track_down_references evolutionary_biology phylogenetics identifiability partial_identification</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:cshalizi/b:26d0857af259/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:to:NB"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:track_down_references"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:evolutionary_biology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:phylogenetics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:identifiability"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:partial_identification"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://www.nature.com/articles/280455a0">
    <title>Population biology of infectious diseases: Part II | Nature</title>
    <dc:date>2020-05-01T20:32:24+00:00</dc:date>
    <link>https://www.nature.com/articles/280455a0</link>
    <dc:creator>cshalizi</dc:creator><description><![CDATA["In the first part of this two-part article (Nature 280, 361–367), mathematical models of directly transmitted microparasitic infections were developed, taking explicit account of the dynamics of the host population. The discussion is now extended to both microparasites (viruses, bacteria and protozoa) and macroparasites (helminths and arthropods), transmitted either directly or indirectly via one or more intermediate hosts. Consideration is given to the relation between the ecology and evolution of the transmission processes and the overall dynamics, and to the mechanisms that can produce cyclic patterns, or multiple stable states, in the levels of infection in the host population."]]></description>
<dc:subject>ecology epidemiology epidemic_models evolutionary_biology may.robert_m. have_read in_NB</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:cshalizi/b:2f4161c8ed70/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:ecology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:epidemiology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:epidemic_models"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:evolutionary_biology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:may.robert_m."/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:have_read"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:in_NB"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://www.nature.com/articles/280361a0">
    <title>Population biology of infectious diseases: Part I | Nature</title>
    <dc:date>2020-05-01T20:17:53+00:00</dc:date>
    <link>https://www.nature.com/articles/280361a0</link>
    <dc:creator>cshalizi</dc:creator><description><![CDATA["If the host population is taken to be a dynamic variable (rather than constant, as conventionally assumed), a wider understanding of the population biology of infectious diseases emerges. In this first part of a two-part article, mathematical models are developed, shown to fit data from laboratory experiments, and used to explore the evolutionary relations among transmission parameters. In the second part of the article, to be published in next week's issue, the models are extended to include indirectly transmitted infections, and the general implications for infectious diseases are considered."]]></description>
<dc:subject>ecology epidemiology epidemic_models evolutionary_biology may.robert_m. have_read in_NB</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:cshalizi/b:1fee609fca07/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:ecology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:epidemiology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:epidemic_models"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:evolutionary_biology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:may.robert_m."/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:have_read"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:in_NB"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://link.springer.com/article/10.1007/s12064-020-00313-7">
    <title>The information theory of individuality | SpringerLink</title>
    <dc:date>2020-04-14T17:13:29+00:00</dc:date>
    <link>https://link.springer.com/article/10.1007/s12064-020-00313-7</link>
    <dc:creator>cshalizi</dc:creator><description><![CDATA["Despite the near universal assumption of individuality in biology, there is little agreement about what individuals are and few rigorous quantitative methods for their identification. Here, we propose that individuals are aggregates that preserve a measure of temporal integrity, i.e., “propagate” information from their past into their futures. We formalize this idea using information theory and graphical models. This mathematical formulation yields three principled and distinct forms of individuality—an organismal, a colonial, and a driven form—each of which varies in the degree of environmental dependence and inherited information. This approach can be thought of as a Gestalt approach to evolution where selection makes figure-ground (agent–environment) distinctions using suitable information-theoretic lenses. A benefit of the approach is that it expands the scope of allowable individuals to include adaptive aggregations in systems that are multi-scale, highly distributed, and do not necessarily have physical boundaries such as cell walls or clonal somatic tissue. Such individuals might be visible to selection but hard to detect by observers without suitable measurement principles. The information theory of individuality allows for the identification of individuals at all levels of organization from molecular to cultural and provides a basis for testing assumptions about the natural scales of a system and argues for the importance of uncertainty reduction through coarse-graining in adaptive systems."]]></description>
<dc:subject>theoretical_biology information_theory kith_and_kin ay.nihat to:NB evolutionary_biology biological_organization</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:cshalizi/b:183588b12063/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:theoretical_biology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:information_theory"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:kith_and_kin"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:ay.nihat"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:to:NB"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:evolutionary_biology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:biological_organization"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://www.mitpressjournals.org/doi/abs/10.1162/evco_a_00249">
    <title>A Revisit of Infinite Population Models for Evolutionary Algorithms on Continuous Optimization Problems | Evolutionary Computation | MIT Press Journals</title>
    <dc:date>2020-03-02T14:52:54+00:00</dc:date>
    <link>https://www.mitpressjournals.org/doi/abs/10.1162/evco_a_00249</link>
    <dc:creator>cshalizi</dc:creator><description><![CDATA["Infinite population models are important tools for studying population dynamics of evolutionary algorithms. They describe how the distributions of populations change between consecutive generations. In general, infinite population models are derived from Markov chains by exploiting symmetries between individuals in the population and analyzing the limit as the population size goes to infinity. In this article, we study the theoretical foundations of infinite population models of evolutionary algorithms on continuous optimization problems. First, we show that the convergence proofs in a widely cited study were in fact problematic and incomplete. We further show that the modeling assumption of exchangeability of individuals cannot yield the transition equation. Then, in order to analyze infinite population models, we build an analytical framework based on convergence in distribution of random elements which take values in the metric space of infinite sequences. The framework is concise and mathematically rigorous. It also provides an infrastructure for studying the convergence of the stacking of operators and of iterating the algorithm which previous studies failed to address. Finally, we use the framework to prove the convergence of infinite population models for the mutation operator and the 𝑘k-ary recombination operator. We show that these operators can provide accurate predictions for real population dynamics as the population size goes to infinity, provided that the initial population is identically and independently distributed."]]></description>
<dc:subject>to:NB evolutionary_biology genetic_algorithms stochastic_processes re:do-institutions-evolve</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:cshalizi/b:2d92f419cef7/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:to:NB"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:evolutionary_biology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:genetic_algorithms"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:stochastic_processes"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:re:do-institutions-evolve"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://www.jstor.org/stable/j.ctt7rkfj">
    <title>First Signals: The Evolution of Multicellular Development on JSTOR</title>
    <dc:date>2020-01-26T16:55:06+00:00</dc:date>
    <link>https://www.jstor.org/stable/j.ctt7rkfj</link>
    <dc:creator>cshalizi</dc:creator><dc:subject>books:noted downloaded developmental_biology evolutionary_biology biochemical_networks bonner.john_tyler in_NB</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:cshalizi/b:b02b7bb6a1f9/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:books:noted"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:downloaded"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:developmental_biology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:evolutionary_biology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:biochemical_networks"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:bonner.john_tyler"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:in_NB"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://arxiv.org/abs/1907.09551">
    <title>[1907.09551] Cell differentiation: what have we learned in 50 years?</title>
    <dc:date>2019-09-15T14:43:28+00:00</dc:date>
    <link>https://arxiv.org/abs/1907.09551</link>
    <dc:creator>cshalizi</dc:creator><description><![CDATA["I revisit two theories of cell differentiation in multicellular organisms published a half-century ago, Stuart Kauffman's global gene regulatory dynamics (GGRD) model and Roy Britten's and Eric Davidson's modular gene regulatory network (MGRN) model, in light of newer knowledge of mechanisms of gene regulation in the metazoans (animals). The two models continue to inform hypotheses and computational studies of differentiation of lineage-adjacent cell types. However, their shared notion (based on bacterial regulatory systems) of gene switches and networks built from them, have constrained progress in understanding the dynamics and evolution of differentiation. Recent work has described unique write-read-rewrite chromatin-based expression encoding in eukaryotes, as well metazoan-specific processes of gene activation and silencing in condensed-phase, enhancer-recruiting regulatory hubs, employing disordered proteins, including transcription factors, with context-dependent identities. These findings suggest an evolutionary scenario in which the origination of differentiation in animals, rather than depending exclusively on adaptive natural selection, emerged as a consequence of a type of multicellularity in which the novel metazoan gene regulatory apparatus was readily mobilized to amplify and exaggerate inherent cell functions of unicellular ancestors. The plausibility of this hypothesis is illustrated by the evolution of the developmental role of Grainyhead-like in the formation of epithelium."]]></description>
<dc:subject>developmental_biology evolutionary_biology gene_regulation biochemical_networks in_NB</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:cshalizi/b:cde25938d027/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:developmental_biology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:evolutionary_biology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:gene_regulation"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:biochemical_networks"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:in_NB"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://www.jstor.org/stable/j.ctt4cgcnc">
    <title>Robustness and Evolvability in Living Systems: on JSTOR</title>
    <dc:date>2019-08-24T15:23:55+00:00</dc:date>
    <link>https://www.jstor.org/stable/j.ctt4cgcnc</link>
    <dc:creator>cshalizi</dc:creator><dc:subject>books:noted evolutionary_biology developmental_biology in_NB downloaded</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:cshalizi/b:53f8bbd1e840/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:books:noted"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:evolutionary_biology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:developmental_biology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:in_NB"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:downloaded"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://www.jstor.org/stable/j.ctt7zvwtj">
    <title>The Evolution of Individuality on JSTOR</title>
    <dc:date>2019-08-23T02:09:06+00:00</dc:date>
    <link>https://www.jstor.org/stable/j.ctt7zvwtj</link>
    <dc:creator>cshalizi</dc:creator><dc:subject>books:noted developmental_biology evolutionary_biology downloaded in_NB</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:cshalizi/b:52a6ef1bea98/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:books:noted"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:developmental_biology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:evolutionary_biology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:downloaded"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:in_NB"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://arxiv.org/abs/1908.06241">
    <title>[1908.06241] Graphon-valued stochastic processes from population genetics</title>
    <dc:date>2019-08-20T14:49:50+00:00</dc:date>
    <link>https://arxiv.org/abs/1908.06241</link>
    <dc:creator>cshalizi</dc:creator><description><![CDATA["The goal of this paper is to develop a theory of graphon-valued stochastic processes, and to construct and analyse a natural class of such processes arising from population genetics. We consider finite populations where individuals change type according to Wright-Fisher resampling. At any time, each pair of individuals is linked by an edge with a probability that is given by a type-connection matrix, whose entries depend on the current empirical type distribution of the entire population via a fitness function. We show that, in the large-population-size limit and with an appropriate scaling of time, the evolution of the associated adjacency matrix converges to a random process in the space of graphons, driven by the type-connection matrix and the underlying Wright-Fisher diffusion on the multi-type simplex. In the limit as the number of types tends to infinity, the limiting process is driven by the type-connection kernel and the underlying Fleming-Viot diffusion."]]></description>
<dc:subject>to:NB evolutionary_biology graphons stochastic_processes den_hollander.frank</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:cshalizi/b:2644ad59a91c/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:to:NB"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:evolutionary_biology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:graphons"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:stochastic_processes"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:den_hollander.frank"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://arxiv.org/abs/1908.05996">
    <title>[1908.05996] Turbulent coherent structures and early life below the Kolmogorov scale</title>
    <dc:date>2019-08-19T13:19:21+00:00</dc:date>
    <link>https://arxiv.org/abs/1908.05996</link>
    <dc:creator>cshalizi</dc:creator><description><![CDATA["A great number of biological organisms live in aqueous environments. Major evolutionary transitions, including the emergence of life itself, likely occurred in such environments. While the chemical aspects of the role of water in biology are well-studied, the effects of water's physical characteristics on evolutionary events, such as the control of population structure via its rich transport properties, are less clear. Evolutionary transitions such as the emergence of the first cells and of multicellularity, require cooperation among groups of individuals. However, evolution of cooperation faces challenges in unstructured "well-mixed" populations, as parasites quickly overwhelm cooperators. Models that assume population structure to promote cooperation envision such structure to arise from spatial "lattice" models (e.g. surface bound individuals) or compartmentalization models, often realized as protocells. Here we study the effect of turbulent motions in spatial models, and propose that coherent structures, i.e. flow patterns which trap fluid and arise naturally in turbulent flows, may serve many of the properties associated with compartments--collocalization, division, and merging--and thought to play a key role in the origins of life and other evolutionary transitions. These results suggest that group selection models may be applicable with fewer physical and chemical constraints than previously thought, and apply much more widely in aqueous environments."]]></description>
<dc:subject>to:NB evolutionary_biology turbulence</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:cshalizi/b:1ed87aef52af/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:to:NB"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:evolutionary_biology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:turbulence"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://journals.aps.org/rmp/abstract/10.1103/RevModPhys.91.031001">
    <title>Rev. Mod. Phys. 91, 031001 (2019) - Colloquium: Proteins: The physics of amorphous evolving matter</title>
    <dc:date>2019-07-30T17:58:43+00:00</dc:date>
    <link>https://journals.aps.org/rmp/abstract/10.1103/RevModPhys.91.031001</link>
    <dc:creator>cshalizi</dc:creator><description><![CDATA["Protein is matter of dual nature. As a physical object, a protein molecule is a folded chain of amino acids with diverse biochemistry. But it is also a point along an evolutionary trajectory determined by the function performed by the protein within a hierarchy of interwoven interaction networks of the cell, the organism, and the population. A physical theory of proteins therefore needs to unify both aspects, the biophysical and the evolutionary. Specifically, it should provide a model of how the DNA gene is mapped into the functional phenotype of the protein. Several physical approaches to the protein problem are reviewed, focusing on a mechanical framework which treats proteins as evolvable condensed matter: Mutations introduce localized perturbations in the gene, which are translated to localized perturbations in the protein matter. A natural tool to examine how mutations shape the phenotype are Green’s functions. They map the evolutionary linkage among mutations in the gene (termed epistasis) to cooperative physical interactions among the amino acids in the protein. The mechanistic view can be applied to examine basic questions of protein evolution and design."

--- Ungated: https://arxiv.org/abs/1907.13371]]></description>
<dc:subject>to:NB biophysics evolutionary_biology eckmann.jean-pierre</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:cshalizi/b:934a0f6ae079/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:to:NB"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:biophysics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:evolutionary_biology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:eckmann.jean-pierre"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://science.sciencemag.org/content/365/6451/347?rss=1">
    <title>Cryptic genetic variation accelerates evolution by opening access to diverse adaptive peaks | Science</title>
    <dc:date>2019-07-30T17:36:51+00:00</dc:date>
    <link>https://science.sciencemag.org/content/365/6451/347?rss=1</link>
    <dc:creator>cshalizi</dc:creator><description><![CDATA["Cryptic genetic variation can facilitate adaptation in evolving populations. To elucidate the underlying genetic mechanisms, we used directed evolution in Escherichia coli to accumulate variation in populations of yellow fluorescent proteins and then evolved these proteins toward the new phenotype of green fluorescence. Populations with cryptic variation evolved adaptive genotypes with greater diversity and higher fitness than populations without cryptic variation, which converged on similar genotypes. Populations with cryptic variation accumulated neutral or deleterious mutations that break the constraints on the order in which adaptive mutations arise. In doing so, cryptic variation opens paths to adaptive genotypes, creates historical contingency, and reduces the predictability of evolution by allowing different replicate populations to climb different adaptive peaks and explore otherwise-inaccessible regions of an adaptive landscape."]]></description>
<dc:subject>to:NB evolutionary_biology wagner.andreas</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:cshalizi/b:8fdf026a125c/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:to:NB"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:evolutionary_biology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:wagner.andreas"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://global.oup.com/academic/product/evolutionary-genetics-9780198830917?cc=us&amp;lang=en#">
    <title>Evolutionary Genetics - Hardcover - Glenn-Peter Saetre; Mark Ravinet - Oxford University Press</title>
    <dc:date>2019-07-24T14:15:51+00:00</dc:date>
    <link>https://global.oup.com/academic/product/evolutionary-genetics-9780198830917?cc=us&amp;lang=en#</link>
    <dc:creator>cshalizi</dc:creator><description><![CDATA["With recent technological advances, vast quantities of genetic and genomic data are being generated at an ever-increasing pace. The explosion in access to data has transformed the field of evolutionary genetics. A thorough understanding of evolutionary principles is essential for making sense of this, but new skill sets are also needed to handle and analyze big data. This contemporary textbook covers all the major components of modern evolutionary genetics, carefully explaining fundamental processes such as mutation, natural selection, genetic drift, and speciation. It also draws on a rich literature of exciting and inspiring examples to demonstrate the diversity of evolutionary research, including an emphasis on how evolution and selection has shaped our own species. 
"Practical experience is essential for developing an understanding of how to use genetic and genomic data to analyze and interpret results in meaningful ways. In addition to the main text, a series of online tutorials using the R language serves as an introduction to programming, statistics, and analysis. Indeed the R environment stands out as an ideal all-purpose source platform to handle and analyze such data. The book and its online materials take full advantage of the authors' own experience in working in a post-genomic revolution world, and introduces readers to the plethora of molecular and analytical methods that have only recently become available. 
"Evolutionary Genetics is an advanced but accessible textbook aimed principally at students of various levels (from undergraduate to postgraduate) but also for researchers looking for an updated introduction to modern evolutionary biology and genetics. "]]></description>
<dc:subject>to:NB genetics evolutionary_biology statistics R books:noted</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:cshalizi/b:b2bc7d74e413/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:to:NB"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:genetics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:evolutionary_biology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:R"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:books:noted"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://arxiv.org/abs/1907.01681">
    <title>[1907.01681] Gradient flow formulations of discrete and continuous evolutionary models: a unifying perspective</title>
    <dc:date>2019-07-17T20:47:19+00:00</dc:date>
    <link>https://arxiv.org/abs/1907.01681</link>
    <dc:creator>cshalizi</dc:creator><description><![CDATA["We consider three classical models of biological evolution: (i) the Moran process, an example of a reducible Markov Chain; (ii) the Kimura Equation, a particular case of a degenerated Fokker-Planck Diffusion; (iii) the Replicator Equation, a paradigm in Evolutionary Game Theory. While these approaches are not completely equivalent, they are intimately connected, since (ii) is the diffusion approximation of (i), and (iii) is obtained from (ii) in an appropriate limit. It is well known that the Replicator Dynamics for two strategies is a gradient flow with respect to the celebrated Shahshahani distance. We reformulate the Moran process and the Kimura Equation as gradient flows and in the sequel we discuss conditions such that the associated gradient structures converge: (i) to (ii) and (ii) to (iii). This provides a geometric characterisation of these evolutionary processes and provides a reformulation of the above examples as time minimization of free energy functionals."]]></description>
<dc:subject>to:NB replicator_dynamics evolutionary_biology dynamical_systems</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:cshalizi/b:135eec376931/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:to:NB"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:replicator_dynamics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:evolutionary_biology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:dynamical_systems"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://www.annualreviews.org/doi/abs/10.1146/annurev-ecolsys-110617-062339">
    <title>Development and Evolutionary Constraints in Animals | Annual Review of Ecology, Evolution, and Systematics</title>
    <dc:date>2019-05-26T18:11:53+00:00</dc:date>
    <link>https://www.annualreviews.org/doi/abs/10.1146/annurev-ecolsys-110617-062339</link>
    <dc:creator>cshalizi</dc:creator><description><![CDATA["We review the evolutionary importance of developmental mechanisms in constraining evolutionary changes in animals—in other words, developmental constraints. We focus on hard constraints that can act on macroevolutionary timescales. In particular, we discuss the causes and evolutionary consequences of the ancient metazoan constraint that differentiated cells cannot divide and constraints against changes of phylotypic stages in vertebrates and other higher taxa. We conclude that in all cases these constraints are caused by complex and highly controlled global interactivity of development, the disturbance of which has grave consequences. Mutations that affect such global interactivity almost unavoidably have many deleterious pleiotropic effects, which will be strongly selected against and will lead to long-term evolutionary stasis. The discussed developmental constraints have pervasive consequences for evolution and critically restrict regeneration capacity and body plan evolution."]]></description>
<dc:subject>evolutionary_biology developmental_biology in_NB</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:cshalizi/b:794e3b32b1da/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:evolutionary_biology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:developmental_biology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:in_NB"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://www.annualreviews.org/doi/abs/10.1146/annurev-ecolsys-110617-062249">
    <title>Evaluating Model Performance in Evolutionary Biology | Annual Review of Ecology, Evolution, and Systematics</title>
    <dc:date>2019-05-26T18:10:58+00:00</dc:date>
    <link>https://www.annualreviews.org/doi/abs/10.1146/annurev-ecolsys-110617-062249</link>
    <dc:creator>cshalizi</dc:creator><description><![CDATA["Many fields of evolutionary biology now depend on stochastic mathematical models. These models are valuable for their ability to formalize predictions in the face of uncertainty and provide a quantitative framework for testing hypotheses. However, no mathematical model will fully capture biological complexity. Instead, these models attempt to capture the important features of biological systems using relatively simple mathematical principles. These simplifications can allow us to focus on differences that are meaningful, while ignoring those that are not. However, simplification also requires assumptions, and to the extent that these are wrong, so is our ability to predict or compare. Here, we discuss approaches for evaluating the performance of evolutionary models in light of their assumptions by comparing them against reality. We highlight general approaches, how they are applied, and remaining opportunities. Absolute tests of fit, even when not explicitly framed as such, are fundamental to progress in understanding evolution."]]></description>
<dc:subject>to:NB evolutionary_biology stochastic_models modeling model_checking statistics</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:cshalizi/b:cb030510dd10/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:to:NB"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:evolutionary_biology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:stochastic_models"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:modeling"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:model_checking"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:statistics"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://www.annualreviews.org/doi/abs/10.1146/annurev-ecolsys-110617-062231">
    <title>Dinosaur Macroevolution and Macroecology | Annual Review of Ecology, Evolution, and Systematics</title>
    <dc:date>2019-05-26T18:08:53+00:00</dc:date>
    <link>https://www.annualreviews.org/doi/abs/10.1146/annurev-ecolsys-110617-062231</link>
    <dc:creator>cshalizi</dc:creator><description><![CDATA["Dinosaurs were large-bodied land animals of the Mesozoic that gave rise to birds. They played a fundamental role in structuring Jurassic–Cretaceous ecosystems and had physiology, growth, and reproductive biology unlike those of extant animals. These features have made them targets of theoretical macroecology. Dinosaurs achieved substantial structural diversity, and their fossil record documents the evolutionary assembly of the avian body plan. Phylogeny-based research has allowed new insights into dinosaur macroevolution, including the adaptive landscape of their body size evolution, patterns of species diversification, and the origins of birds and bird-like traits. Nevertheless, much remains unknown due to incompleteness of the fossil record at both local and global scales. This presents major challenges at the frontier of paleobiological research regarding tests of macroecological hypotheses and the effects of dinosaur biology, ecology, and life history on their macroevolution."]]></description>
<dc:subject>to:NB evolutionary_biology dinosaurs ecology</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:cshalizi/b:783ee92cc64f/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:to:NB"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:evolutionary_biology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:dinosaurs"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:ecology"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://www.annualreviews.org/doi/abs/10.1146/annurev-ecolsys-110316-022830">
    <title>Variation and Evolution of Function-Valued Traits | Annual Review of Ecology, Evolution, and Systematics</title>
    <dc:date>2019-05-26T18:08:20+00:00</dc:date>
    <link>https://www.annualreviews.org/doi/abs/10.1146/annurev-ecolsys-110316-022830</link>
    <dc:creator>cshalizi</dc:creator><description><![CDATA["Function-valued traits—phenotypes whose expression depends on a continuous index (such as age, temperature, or space)—occur throughout biology and, like any trait, it is important to understand how they vary and evolve. Although methods for analyzing variation and evolution of function-valued traits are well developed, they have been underutilized by evolutionists, especially those who study natural populations. We seek to summarize advances in the study of function-valued traits and to make their analyses more approachable and accessible to biologists who could benefit greatly from their use. To that end, we explain how curve thinking benefits conceptual understanding and statistical analysis of functional data. We provide a detailed guide to the most flexible and statistically powerful methods and include worked examples (with R code) as supplemental material. We review ways to characterize variation in function-valued traits and analyze consequences for evolution, including constraint. We also discuss how selection on function-valued traits can be estimated and combined with estimates of heritable variation to project evolutionary dynamics."]]></description>
<dc:subject>to:NB evolutionary_biology functional_data_analysis statistics</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:cshalizi/b:315c8f0e4874/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:to:NB"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:evolutionary_biology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:functional_data_analysis"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:statistics"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://www.annualreviews.org/doi/abs/10.1146/annurev-ecolsys-110617-062358">
    <title>The Contemporary Evolution of Fitness | Annual Review of Ecology, Evolution, and Systematics</title>
    <dc:date>2019-05-26T18:07:49+00:00</dc:date>
    <link>https://www.annualreviews.org/doi/abs/10.1146/annurev-ecolsys-110617-062358</link>
    <dc:creator>cshalizi</dc:creator><description><![CDATA["The rate of evolution of population mean fitness informs how selection acting in contemporary populations can counteract environmental change and genetic degradation (mutation, gene flow, drift, recombination). This rate influences population increases (e.g., range expansion), population stability (e.g., cryptic eco-evolutionary dynamics), and population recovery (i.e., evolutionary rescue). We review approaches for estimating such rates, especially in wild populations. We then review empirical estimates derived from two approaches: mutation accumulation (MA) and additive genetic variance in fitness (IAw). MA studies inform how selection counters genetic degradation arising from deleterious mutations, typically generating estimates of <1% per generation. IAw studies provide an integrated prediction of proportional change per generation, nearly always generating estimates of <20% and, more typically, <10%. Overall, considerable, but not unlimited, evolutionary potential exists in populations facing detrimental environmental or genetic change. However, further studies with diverse methods and species are required for more robust and general insights."]]></description>
<dc:subject>to:NB evolutionary_biology statistics</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:cshalizi/b:f91b470fa830/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:to:NB"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:evolutionary_biology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:statistics"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://www.theatlantic.com/science/archive/2019/01/unprecedentedly-thorough-evolution-experiment/581521/">
    <title>An Unprecedentedly Thorough Evolution Experiment - The Atlantic</title>
    <dc:date>2019-02-01T17:33:15+00:00</dc:date>
    <link>https://www.theatlantic.com/science/archive/2019/01/unprecedentedly-thorough-evolution-experiment/581521/</link>
    <dc:creator>cshalizi</dc:creator><dc:subject>biology evolutionary_biology experimental_biology track_down_references</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:cshalizi/b:c6cf3fdced73/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:biology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:evolutionary_biology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:experimental_biology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:track_down_references"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://www.nature.com/articles/315400a0">
    <title>Neo-darwinian evolution implies punctuated equilibria | Nature [1985]</title>
    <dc:date>2018-08-02T15:49:28+00:00</dc:date>
    <link>https://www.nature.com/articles/315400a0</link>
    <dc:creator>cshalizi</dc:creator><description><![CDATA["The two central elements of neo-darwinian evolution are small random variations and natural selection. In Wright's view, these lead to random drift of mean population characters in a fixed, multiply peaked ‘adaptive landscape’, with long periods spent near fitness peaks. Using recent theoretical results5, we show here that transitions between peaks are rapid and unidirectional even though (indeed, because) random variations are small and transitions initially require movement against selection. Thus, punctuated equilibrium, the palaeontological pattern of rapid transitions between morphological equlibria, is a natural manifestation of the standard wrightian evolutionary theory and requires no special developmental, genetic or ecological mechanisms."]]></description>
<dc:subject>have_read evolutionary_biology large_deviations stochastic_processes re:do-institutions-evolve evolution in_NB</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:cshalizi/b:004768a3d928/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:have_read"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:evolutionary_biology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:large_deviations"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:stochastic_processes"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:re:do-institutions-evolve"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:evolution"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:in_NB"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://www.nature.com/articles/nature25965">
    <title>Altruism in a volatile world | Nature</title>
    <dc:date>2018-05-07T22:33:04+00:00</dc:date>
    <link>https://www.nature.com/articles/nature25965</link>
    <dc:creator>cshalizi</dc:creator><description><![CDATA["The evolution of altruism—costly self-sacrifice in the service of others—has puzzled biologists1 since The Origin of Species. For half a century, attempts to understand altruism have developed around the concept that altruists may help relatives to have extra offspring in order to spread shared genes2. This theory—known as inclusive fitness—is founded on a simple inequality termed Hamilton’s rule2. However, explanations of altruism have typically not considered the stochasticity of natural environments, which will not necessarily favour genotypes that produce the greatest average reproductive success3,4. Moreover, empirical data across many taxa reveal associations between altruism and environmental stochasticity5,6,7,8, a pattern not predicted by standard interpretations of Hamilton’s rule. Here we derive Hamilton’s rule with explicit stochasticity, leading to new predictions about the evolution of altruism. We show that altruists can increase the long-term success of their genotype by reducing the temporal variability in the number of offspring produced by their relatives. Consequently, costly altruism can evolve even if it has a net negative effect on the average reproductive success of related recipients. The selective pressure on volatility-suppressing altruism is proportional to the coefficient of variation in population fitness, and is therefore diminished by its own success. Our results formalize the hitherto elusive link between bet-hedging and altruism4,9,10,11, and reveal missing fitness effects in the evolution of animal societies."]]></description>
<dc:subject>to:NB evolutionary_biology evolutionary_game_theory evolution_of_cooperation</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:cshalizi/b:5a041adeb794/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:to:NB"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:evolutionary_biology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:evolutionary_game_theory"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:evolution_of_cooperation"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://www.nature.com/articles/s41586-018-0043-0">
    <title>Renewing Felsenstein’s phylogenetic bootstrap in the era of big data | Nature</title>
    <dc:date>2018-05-07T17:06:07+00:00</dc:date>
    <link>https://www.nature.com/articles/s41586-018-0043-0</link>
    <dc:creator>cshalizi</dc:creator><description><![CDATA["Felsenstein’s application of the bootstrap method to evolutionary trees is one of the most cited scientific papers of all time. The bootstrap method, which is based on resampling and replications, is used extensively to assess the robustness of phylogenetic inferences. However, increasing numbers of sequences are now available for a wide variety of species, and phylogenies based on hundreds or thousands of taxa are becoming routine. With phylogenies of this size Felsenstein’s bootstrap tends to yield very low supports, especially on deep branches. Here we propose a new version of the phylogenetic bootstrap in which the presence of inferred branches in replications is measured using a gradual ‘transfer’ distance rather than the binary presence or absence index used in Felsenstein’s original version. The resulting supports are higher and do not induce falsely supported branches. The application of our method to large mammal, HIV and simulated datasets reveals their phylogenetic signals, whereas Felsenstein’s bootstrap fails to do so."]]></description>
<dc:subject>to:NB statistics evolutionary_biology phylogenetics bootstrap</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:cshalizi/b:9d5bc113ba1d/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:to:NB"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:evolutionary_biology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:phylogenetics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:bootstrap"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://www.nature.com/articles/nature24273">
    <title>Indirect effects drive coevolution in mutualistic networks | Nature</title>
    <dc:date>2017-12-14T22:59:53+00:00</dc:date>
    <link>https://www.nature.com/articles/nature24273</link>
    <dc:creator>cshalizi</dc:creator><description><![CDATA["Ecological interactions have been acknowledged to play a key role in shaping biodiversity1,2. Yet a major challenge for evolutionary biology is to understand the role of ecological interactions in shaping trait evolution when progressing from pairs of interacting species to multispecies interaction networks2. Here we introduce an approach that integrates coevolutionary dynamics and network structure. Our results show that non-interacting species can be as important as directly interacting species in shaping coevolution within mutualistic assemblages. The contribution of indirect effects differs among types of mutualism. Indirect effects are more likely to predominate in nested, species-rich networks formed by multiple-partner mutualisms, such as pollination or seed dispersal by animals, than in small and modular networks formed by intimate mutualisms, such as those between host plants and their protective ants. Coevolutionary pathways of indirect effects favour ongoing trait evolution by promoting slow but continuous reorganization of the adaptive landscape of mutualistic partners under changing environments. Our results show that coevolution can be a major process shaping species traits throughout ecological networks. These findings expand our understanding of how evolution driven by interactions occurs through the interplay of selection pressures moving along multiple direct and indirect pathways."]]></description>
<dc:subject>to:NB evolutionary_biology ecology networks</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:cshalizi/b:38ea998e9ef9/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:to:NB"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:evolutionary_biology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:ecology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:networks"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://www.nature.com/articles/nature24287">
    <title>The dynamics of molecular evolution over 60,000 generations | Nature</title>
    <dc:date>2017-12-14T22:55:10+00:00</dc:date>
    <link>https://www.nature.com/articles/nature24287</link>
    <dc:creator>cshalizi</dc:creator><description><![CDATA["The outcomes of evolution are determined by a stochastic dynamical process that governs how mutations arise and spread through a population. However, it is difficult to observe these dynamics directly over long periods and across entire genomes. Here we analyse the dynamics of molecular evolution in twelve experimental populations of Escherichia coli, using whole-genome metagenomic sequencing at five hundred-generation intervals through sixty thousand generations. Although the rate of fitness gain declines over time, molecular evolution is characterized by signatures of rapid adaptation throughout the duration of the experiment, with multiple beneficial variants simultaneously competing for dominance in each population. Interactions between ecological and evolutionary processes play an important role, as long-term quasi-stable coexistence arises spontaneously in most populations, and evolution continues within each clade. We also present evidence that the targets of natural selection change over time, as epistasis and historical contingency alter the strength of selection on different genes. Together, these results show that long-term adaptation to a constant environment can be a more complex and dynamic process than is often assumed."]]></description>
<dc:subject>to:NB evolutionary_biology e_coli lenski.richard</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:cshalizi/b:2e29c7ee389c/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:to:NB"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:evolutionary_biology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:e_coli"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:lenski.richard"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://press.princeton.edu/titles/11175.html">
    <title>McPeek, M.A.: Evolutionary Community Ecology, Volume 58 (eBook and Hardcover).</title>
    <dc:date>2017-08-31T19:08:32+00:00</dc:date>
    <link>http://press.princeton.edu/titles/11175.html</link>
    <dc:creator>cshalizi</dc:creator><description><![CDATA["Evolutionary Community Ecology develops a unified framework for understanding the structure of ecological communities and the dynamics of natural selection that shape the evolution of the species inhabiting them. All species engage in interactions with many other species, and these interactions regulate their abundance, define their trajectories of natural selection, and shape their movement decisions. Mark McPeek synthesizes the ecological and evolutionary dynamics generated by species interactions that structure local biological communities and regional metacommunities.
"McPeek explores the ecological performance characteristics needed for invasibility and coexistence of species in complex networks of species interactions. This species interaction framework is then extended to examine the ecological dynamics of natural selection that drive coevolution of interacting species in these complex interaction networks. The models of natural selection resulting from species interactions are used to evaluate the ecological conditions that foster diversification at multiple trophic levels. Analyses show that diversification depends on the ecological context in which species interactions occur and the types of traits that define the mechanisms of those species interactions. Lastly, looking at the mechanisms of speciation that affect species richness and diversity at various spatial scales and the consequences of past climate change over the Quaternary period, McPeek considers how metacommunity structure is shaped at regional and biogeographic scales."

]]></description>
<dc:subject>to:NB books:noted evolutionary_biology ecology</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:cshalizi/b:1b06f326496d/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:to:NB"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:books:noted"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:evolutionary_biology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:ecology"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://www.pnas.org/content/114/30/7838.abstract">
    <title>A social insect perspective on the evolution of social learning mechanisms</title>
    <dc:date>2017-08-28T22:42:02+00:00</dc:date>
    <link>http://www.pnas.org/content/114/30/7838.abstract</link>
    <dc:creator>cshalizi</dc:creator><description><![CDATA["The social world offers a wealth of opportunities to learn from others, and across the animal kingdom individuals capitalize on those opportunities. Here, we explore the role of natural selection in shaping the processes that underlie social information use, using a suite of experiments on social insects as case studies. We illustrate how an associative framework can encompass complex, context-specific social learning in the insect world and beyond, and based on the hypothesis that evolution acts to modify the associative process, suggest potential pathways by which social information use could evolve to become more efficient and effective. Social insects are distant relatives of vertebrate social learners, but the research we describe highlights routes by which natural selection could coopt similar cognitive raw material across the animal kingdom."]]></description>
<dc:subject>to:NB cultural_evolution social_life_of_the_mind evolutionary_biology</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:cshalizi/b:ca5c2c4b9757/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:to:NB"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:cultural_evolution"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:social_life_of_the_mind"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:evolutionary_biology"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://www.nature.com/nature/journal/vaop/ncurrent/full/nature21723.html">
    <title>Evolutionary dynamics on any population structure : Nature : Nature Research</title>
    <dc:date>2017-04-01T17:37:43+00:00</dc:date>
    <link>http://www.nature.com/nature/journal/vaop/ncurrent/full/nature21723.html</link>
    <dc:creator>cshalizi</dc:creator><description><![CDATA["Evolution occurs in populations of reproducing individuals. The structure of a population can affect which traits evolve1, 2. Understanding evolutionary game dynamics in structured populations remains difficult. Mathematical results are known for special structures in which all individuals have the same number of neighbours3, 4, 5, 6, 7, 8. The general case, in which the number of neighbours can vary, has remained open. For arbitrary selection intensity, the problem is in a computational complexity class that suggests there is no efficient algorithm9. Whether a simple solution for weak selection exists has remained unanswered. Here we provide a solution for weak selection that applies to any graph or network. Our method relies on calculating the coalescence times10, 11 of random walks12. We evaluate large numbers of diverse population structures for their propensity to favour cooperation. We study how small changes in population structure—graph surgery—affect evolutionary outcomes. We find that cooperation flourishes most in societies that are based on strong pairwise ties."]]></description>
<dc:subject>to:NB evolutionary_biology evolutionary_game_theory evolution_of_cooperation network_data_analysis</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:cshalizi/b:2a9ea0dd81d9/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:to:NB"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:evolutionary_biology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:evolutionary_game_theory"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:evolution_of_cooperation"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:network_data_analysis"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://press.uchicago.edu/ucp/books/book/chicago/H/bo25568406">
    <title>How to Tame a Fox (and Build a Dog): Visionary Scientists and a Siberian Tale of Jump-Started Evolution, Dugatkin, Trut</title>
    <dc:date>2017-04-01T01:25:34+00:00</dc:date>
    <link>http://press.uchicago.edu/ucp/books/book/chicago/H/bo25568406</link>
    <dc:creator>cshalizi</dc:creator><description><![CDATA["Tucked away in Siberia, there are furry, four-legged creatures with wagging tails and floppy ears that are as docile and friendly as any lapdog. But, despite appearances, these are not dogs—they are foxes. They are the result of the most astonishing experiment in breeding ever undertaken—imagine speeding up thousands of years of evolution into a few decades. In 1959, biologists Dmitri Belyaev and Lyudmila Trut set out to do just that, by starting with a few dozen silver foxes from fox farms in the USSR and attempting to recreate the evolution of wolves into dogs in real time in order to witness the process of domestication. This is the extraordinary, untold story of this remarkable undertaking.
"Most accounts of the natural evolution of wolves place it over a span of about 15,000 years, but within a decade, Belyaev and Trut’s fox breeding experiments had resulted in puppy-like foxes with floppy ears, piebald spots, and curly tails. Along with these physical changes came genetic and behavioral changes, as well. The foxes were bred using selection criteria for tameness, and with each generation, they became increasingly interested in human companionship. Trut has been there the whole time, and has been the lead scientist on this work since Belyaev’s death in 1985, and with Lee Dugatkin, biologist and science writer, she tells the story of the adventure, science, politics, and love behind it all.  In How to Tame a Fox, Dugatkin and Trut take us inside this path-breaking experiment in the midst of the brutal winters of Siberia to reveal how scientific history is made and continues to be made today.
"To date, fifty-six generations of foxes have been domesticated, and we continue to learn significant lessons from them about the genetic and behavioral evolution of domesticated animals. How to Tame a Fox offers an incredible tale of scientists at work, while also celebrating the deep attachments that have brought humans and animals together throughout time."

--- Naturally, my mind immediately goes to my mad plan to domesticate snow leopards.]]></description>
<dc:subject>to:NB books:noted evolutionary_biology popular_science</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:cshalizi/b:866bfcb3bb53/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:to:NB"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:books:noted"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:evolutionary_biology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:popular_science"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://press.uchicago.edu/ucp/books/book/chicago/M/bo20952527">
    <title>Microbes from Hell, Forterre, Fagan</title>
    <dc:date>2016-11-05T14:35:58+00:00</dc:date>
    <link>http://press.uchicago.edu/ucp/books/book/chicago/M/bo20952527</link>
    <dc:creator>cshalizi</dc:creator><description><![CDATA["At the close of the 1970s, the two-domain classification scheme long used by most biologists—prokaryotes versus eukaryotes—was upended by the discovery of an entirely new group of organisms: archaea. Initially thought to be bacteria, these single-celled microbes—many of which were first found in seemingly unlivable habitats like the volcanic hot springs of Yellowstone National Park—were in fact so different at molecular and genetic levels as to constitute a separate, third domain beside bacteria and eukaryotes. Their discovery sparked a conceptual revolution in our understanding of the evolution of life, and Patrick Forterre was—and still is—at the vanguard of this revolution.
"In Microbes from Hell, one of the world’s leading experts on archaea and hyperthermophiles, or organisms that have evolved to flourish in extreme temperatures, offers a colorful, engaging account of this taxonomic upheaval. Blending tales of his own search for thermophiles with discussions of both the physiological challenges thermophiles face and the unique adaptations they have evolved to live in high-temperature environments, Forterre illuminates our developing understanding of the relationship between archaea and the rest of Earth’s organisms. From biotech applications to the latest discoveries in thermophile research, from microbiomes to the communities of organisms that dwell on deep-sea vents, Forterre’s exploration of life-forms that seem to thrive at the mouth of hell provides a glimpse into the early days of Earth, offering deep insight into what life may have looked like in the extreme environments of our planet’s dawn."]]></description>
<dc:subject>to:NB books:noted evolutionary_biology archaea</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:cshalizi/b:fae6b165b711/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:to:NB"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:books:noted"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:evolutionary_biology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:archaea"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://press.princeton.edu/titles/10914.html">
    <title>Vellend, M.: The Theory of Ecological Communities (MPB-57) (eBook and Hardcover).</title>
    <dc:date>2016-09-20T15:50:12+00:00</dc:date>
    <link>http://press.princeton.edu/titles/10914.html</link>
    <dc:creator>cshalizi</dc:creator><description><![CDATA["A plethora of different theories, models, and concepts make up the field of community ecology. Amid this vast body of work, is it possible to build one general theory of ecological communities? What other scientific areas might serve as a guiding framework? As it turns out, the core focus of community ecology—understanding patterns of diversity and composition of biological variants across space and time—is shared by evolutionary biology and its very coherent conceptual framework, population genetics theory. The Theory of Ecological Communities takes this as a starting point to pull together community ecology’s various perspectives into a more unified whole.
"Mark Vellend builds a theory of ecological communities based on four overarching processes: selection among species, drift, dispersal, and speciation. These are analogues of the four central processes in population genetics theory—selection within species, drift, gene flow, and mutation—and together they subsume almost all of the many dozens of more specific models built to describe the dynamics of communities of interacting species. The result is a theory that allows the effects of many low-level processes, such as competition, facilitation, predation, disturbance, stress, succession, colonization, and local extinction to be understood as the underpinnings of high-level processes with widely applicable consequences for ecological communities."]]></description>
<dc:subject>to:NB books:noted ecology evolutionary_biology</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:cshalizi/b:d17dde0b38a1/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:to:NB"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:books:noted"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:ecology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:evolutionary_biology"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://www.pnas.org/content/113/34/9492.abstract.html">
    <title>Constraint, natural selection, and the evolution of human body form</title>
    <dc:date>2016-08-24T16:11:14+00:00</dc:date>
    <link>http://www.pnas.org/content/113/34/9492.abstract.html</link>
    <dc:creator>cshalizi</dc:creator><description><![CDATA["Variation in body form among human groups is structured by a blend of natural selection driven by local climatic conditions and random genetic drift. However, attempts to test ecogeographic hypotheses have not distinguished between adaptive traits (i.e., those that evolved as a result of selection) and those that evolved as a correlated response to selection on other traits (i.e., nonadaptive traits), complicating our understanding of the relationship between climate and morphological distinctions among populations. Here, we use evolutionary quantitative methods to test if traits previously identified as supporting ecogeographic hypotheses were actually adaptive by estimating the force of selection on individual traits needed to drive among-group differentiation. Our results show that not all associations between trait means and latitude were caused by selection acting directly on each individual trait. Although radial and tibial length and biiliac and femoral head breadth show signs of responses to directional selection matching ecogeographic hypotheses, the femur was subject to little or no directional selection despite having shorter values by latitude. Additionally, in contradiction to ecogeographic hypotheses, the humerus was under directional selection for longer values by latitude. Responses to directional selection in the tibia and radius induced a nonadaptive correlated response in the humerus that overwhelmed its own trait-specific response to selection. This result emphasizes that mean differences between groups are not good indicators of which traits are adaptations in the absence of information about covariation among characteristics."

--- Not obvious to me how they can pick out the constraints here (maybe assuming equal within-gro
up covariances, and assuming they reflect constraints?), but presumably that's addressed in the paper.]]></description>
<dc:subject>to:NB human_evolution evolutionary_biology</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:cshalizi/b:38a323ad3de7/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:to:NB"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:human_evolution"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:evolutionary_biology"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://press.princeton.edu/titles/4549.html">
    <title>Brandon, R.N.: Adaptation and Environment (eBook, Paperback and Hardcover).</title>
    <dc:date>2016-06-22T16:25:31+00:00</dc:date>
    <link>http://press.princeton.edu/titles/4549.html</link>
    <dc:creator>cshalizi</dc:creator><description><![CDATA["By focusing on the crucial role of environment in the process of adaptation, Robert Brandon clarifies definitions and principles so as to help make the argument of evolution by natural selection empirically testable. He proposes that natural selection is the process of differential reproduction resulting from differential adaptedness to a common selective environment."]]></description>
<dc:subject>to:NB books:noted adaptation evolutionary_biology philosophy_of_science</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:cshalizi/b:80d39fddfc29/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:to:NB"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:books:noted"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:adaptation"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:evolutionary_biology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:cshalizi/t:philosophy_of_science"/>
</rdf:Bag></taxo:topics>
</item>
</rdf:RDF>