Showing papers by "Santa Fe Institute published in 2010"
TL;DR: It is shown that all opinions in a large society converge to the truth if and only if the influence of the most influential agent vanishes as the society grows.
Abstract: We study learning in a setting where agents receive independent noisy signals about the true value of a variable and then communi cate in a network. They naively update beliefs by repeatedly taking weighted averages of neighbors' opinions. We show that all opinions in a large society converge to the truth if and only if the influence of the most influential agent vanishes as the society grows. We also identify obstructions to this, including prominent groups, and pro vide structural conditions on the network ensuring efficient learn ing. Whether agents converge to the truth is unrelated to how quickly consensus is approached. (JEL D83, D85, Z13)
1,044 citations
TL;DR: It is shown that the modularity function Q exhibits extreme degeneracies: it typically admits an exponential number of distinct high-scoring solutions and typically lacks a clear global maximum, implying that the output of any modularity maximization procedure should be interpreted cautiously in scientific contexts.
Abstract: Although widely used in practice, the behavior and accuracy of the popular module identification technique called modularity maximization is not well understood in practical contexts. Here, we present a broad characterization of its performance in such situations. First, we revisit and clarify the resolution limit phenomenon for modularity maximization. Second, we show that the modularity function Q exhibits extreme degeneracies: it typically admits an exponential number of distinct high-scoring solutions and typically lacks a clear global maximum. Third, we derive the limiting behavior of the maximum modularity Q(max) for one model of infinitely modular networks, showing that it depends strongly both on the size of the network and on the number of modules it contains. Finally, using three real-world metabolic networks as examples, we show that the degenerate solutions can fundamentally disagree on many, but not all, partition properties such as the composition of the largest modules and the distribution of module sizes. These results imply that the output of any modularity maximization procedure should be interpreted cautiously in scientific contexts. They also explain why many heuristics are often successful at finding high-scoring partitions in practice and why different heuristics can disagree on the modular structure of the same network. We conclude by discussing avenues for mitigating some of these behaviors, such as combining information from many degenerate solutions or using generative models.
982 citations
TL;DR: Analyzing the motion of approximately 1500 pedestrian groups under natural condition shows that social interactions among group members generate typical group walking patterns that influence crowd dynamics, demonstrating that crowd dynamics is not only determined by physical constraints induced by other pedestrians and the environment, but also significantly by communicative, social interaction among individuals.
Abstract: Human crowd motion is mainly driven by self-organized processes based on local interactions among pedestrians. While most studies of crowd behaviour consider only interactions among isolated individuals, it turns out that up to 70% of people in a crowd are actually moving in groups, such as friends, couples, or families walking together. These groups constitute medium-scale aggregated structures and their impact on crowd dynamics is still largely unknown. In this work, we analyze the motion of approximately 1500 pedestrian groups under natural condition, and show that social interactions among group members generate typical group walking patterns that influence crowd dynamics. At low density, group members tend to walk side by side, forming a line perpendicular to the walking direction. As the density increases, however, the linear walking formation is bent forward, turning it into a V-like pattern. These spatial patterns can be well described by a model based on social communication between group members. We show that the V-like walking pattern facilitates social interactions within the group, but reduces the flow because of its "non-aerodynamic" shape. Therefore, when crowd density increases, the group organization results from a trade-off between walking faster and facilitating social exchange. These insights demonstrate that crowd dynamics is not only determined by physical constraints induced by other pedestrians and the environment, but also significantly by communicative, social interactions among individuals.
950 citations
TL;DR: It is found that the diversity of individuals’ relationships is strongly correlated with the economic development of communities and the relation between the structure of social networks and access to socioeconomic opportunity is investigated.
Abstract: Social networks form the backbone of social and economic life. Until recently, however, data have not been available to study the social impact of a national network structure. To that end, we combined the most complete record of a national communication network with national census data on the socioeconomic well-being of communities. These data make possible a population-level investigation of the relation between the structure of social networks and access to socioeconomic opportunity. We find that the diversity of individuals' relationships is strongly correlated with the economic development of communities.
722 citations
TL;DR: Emerging knowledge of how plant nutrients respond to environmental variables and are connected to size, the effects of global change factors can be better understood.
Abstract: Biological stoichiometry theory considers the balance of multiple chemical elements in living systems, whereas metabolic scaling theory considers how size affects metabolic properties from cells to ecosystems. We review recent developments integrating biological stoichiometry and metabolic scaling theories in the context of plant ecology and global change. Although vascular plants exhibit wide variation in foliar carbon:nitrogen:phosphorus ratios, they exhibit a higher degree of 'stoichiometric homeostasis' than previously appreciated. Thus, terrestrial carbon:nitrogen:phosphorus stoichiometry will reflect the effects of adjustment to local growth conditions as well as species' replacements. Plant stoichiometry exhibits size scaling, as foliar nutrient concentration decreases with increasing plant size, especially for phosphorus. Thus, small plants have lower nitrogen:phosphorus ratios. Furthermore, foliar nutrient concentration is reflected in other tissues (root, reproductive, support), permitting the development of empirical models of production that scale from tissue to whole-plant levels. Plant stoichiometry exhibits large-scale macroecological patterns, including stronger latitudinal trends and environmental correlations for phosphorus concentration (relative to nitrogen) and a positive correlation between nutrient concentrations and geographic range size. Given this emerging knowledge of how plant nutrients respond to environmental variables and are connected to size, the effects of global change factors (such as carbon dioxide, temperature, nitrogen deposition) can be better understood.
688 citations
TL;DR: It is shown that bootstrap resampling accompanied by significance clustering provides a solution to the problem of distinguishing meaningful structural changes from random fluctuations and is realized de Solla Price's vision of mapping change in science.
Abstract: Change is a fundamental ingredient of interaction patterns in biology, technology, the economy, and science itself: Interactions within and between organisms change; transportation patterns by air, land, and sea all change; the global financial flow changes; and the frontiers of scientific research change. Networks and clustering methods have become important tools to comprehend instances of these large-scale structures, but without methods to distinguish between real trends and noisy data, these approaches are not useful for studying how networks change. Only if we can assign significance to the partitioning of single networks can we distinguish meaningful structural changes from random fluctuations. Here we show that bootstrap resampling accompanied by significance clustering provides a solution to this problem. To connect changing structures with the changing function of networks, we highlight and summarize the significant structural changes with alluvial diagrams and realize de Solla Price's vision of mapping change in science: studying the citation pattern between about 7000 scientific journals over the past decade, we find that neuroscience has transformed from an interdisciplinary specialty to a mature and stand-alone discipline.
582 citations
TL;DR: It is shown that punishment can proliferate when rare, and when it does, it enhances group-average payoffs, and captures a further aspect of reality missing from both models and experiments.
Abstract: Because mutually beneficial cooperation may unravel unless most members of a group contribute, people often gang up on free-riders, punishing them when this is cost-effective in sustaining cooperation. In contrast, current models of the evolution of cooperation assume that punishment is uncoordinated and unconditional. These models have difficulty explaining the evolutionary emergence of punishment because rare unconditional punishers bear substantial costs and hence are eliminated. Moreover, in human behavioral experiments in which punishment is uncoordinated, the sum of costs to punishers and their targets often exceeds the benefits of the increased cooperation that results from the punishment of free-riders. As a result, cooperation sustained by punishment may actually reduce the average payoffs of group members in comparison with groups in which punishment of free-riders is not an option. Here, we present a model of coordinated punishment that is calibrated for ancestral human conditions and captures a further aspect of reality missing from both models and experiments: The total cost of punishing a free-rider declines as the number of punishers increases. We show that punishment can proliferate when rare, and when it does, it enhances group-average payoffs.
546 citations
TL;DR: It is found that local urban dynamics display long-term memory, so cities under or outperforming their size expectation maintain such (dis)advantage for decades.
Abstract: With urban population increasing dramatically worldwide, cities are playing an increasingly critical role in human societies and the sustainability of the planet. An obstacle to effective policy is the lack of meaningful urban metrics based on a quantitative understanding of cities. Typically, linear per capita indicators are used to characterize and rank cities. However, these implicitly ignore the fundamental role of nonlinear agglomeration integral to the life history of cities. As such, per capita indicators conflate general nonlinear effects, common to all cities, with local dynamics, specific to each city, failing to provide direct measures of the impact of local events and policy. Agglomeration nonlinearities are explicitly manifested by the superlinear power law scaling of most urban socioeconomic indicators with population size, all with similar exponents (*1.15). As a result larger cities are disproportionally the centers of innovation, wealth and crime, all to approximately the same degree. We use these general urban laws to develop new urban metrics that disentangle dynamics at different scales and provide true measures of local urban performance. New rankings of cities and a novel and simpler perspective on urban systems emerge. We find that local urban dynamics display long-term memory, so cities under or outperforming their size expectation maintain such (dis)advantage for decades. Spatiotemporal correlation analyses reveal a novel functional taxonomy of U.S. metropolitan areas that is generally not organized geographically but based instead on common local economic models, innovation strategies and patterns of crime.
483 citations
TL;DR: It is shown that mosaic HIV-1 Gag, Pol and Env antigens expressed by recombinant, replication-incompetent adenovirus serotype 26 vectors markedly augmented both the breadth and depth without compromising the magnitude of antigen-specific T lymphocyte responses in rhesus monkeys.
Abstract: The worldwide diversity of HIV-1 presents an unprecedented challenge for vaccine development. Antigens derived from natural HIV-1 sequences have elicited only a limited breadth of cellular immune responses in nonhuman primate studies and clinical trials to date. Polyvalent 'mosaic' antigens, in contrast, are designed to optimize cellular immunologic coverage of global HIV-1 sequence diversity. Here we show that mosaic HIV-1 Gag, Pol and Env antigens expressed by recombinant, replication-incompetent adenovirus serotype 26 vectors markedly augmented both the breadth and depth without compromising the magnitude of antigen-specific T lymphocyte responses as compared with consensus or natural sequence HIV-1 antigens in rhesus monkeys. Polyvalent mosaic antigens therefore represent a promising strategy to expand cellular immunologic vaccine coverage for genetically diverse pathogens such as HIV-1.
397 citations
TL;DR: The scalings of metabolic rate, population growth rate, and production efficiency with body size have changed across the evolutionary transitions, showing Kleiber’s 3/4 power scaling law does not apply universally across organisms.
Abstract: The diversification of life involved enormous increases in size and complexity. The evolutionary transitions from prokaryotes to unicellular eukaryotes to metazoans were accompanied by major innovations in metabolic design. Here we show that the scalings of metabolic rate, population growth rate, and production efficiency with body size have changed across the evolutionary transitions. Metabolic rate scales with body mass superlinearly in prokaryotes, linearly in protists, and sublinearly in metazoans, so Kleiber's 3/4 power scaling law does not apply universally across organisms. The scaling of maximum population growth rate shifts from positive in prokaryotes to negative in protists and metazoans, and the efficiency of production declines across these groups. Major changes in metabolic processes during the early evolution of life overcame existing constraints, exploited new opportunities, and imposed new constraints.
350 citations
TL;DR: Punishing strategies can spread in both cases, but based on largely different mechanisms, which depend on the cooperativeness (or not) of punishers.
Abstract: We study the evolution of cooperation in spatial public goods games where, besides the classical strategies of cooperation (C) and defection (D), we consider punishing cooperators (PC) or punishing defectors (PD) as an additional strategy. Using a minimalist modeling approach, our goal is to separately clarify and identify the consequences of the two punishing strategies. Since punishment is costly, punishing strategies lose the evolutionary competition in case of well-mixed interactions. When spatial interactions are taken into account, however, the outcome can be strikingly different, and cooperation may spread. The underlying mechanism depends on the character of the punishment strategy. In the case of cooperating punishers, increasing the fine results in a rising cooperation level. In contrast, in the presence of the PD strategy, the phase diagram exhibits a reentrant transition as the fine is increased. Accordingly, the level of cooperation shows a non-monotonous dependence on the fine. Remarkably, punishing strategies can spread in both cases, but based on largely different mechanisms, which depend on the cooperativeness (or not) of punishers.
TL;DR: Breadth of neutralization was correlated with viral load, but not with CD4 count, history of past antiretroviral use, age, gender, race/ethnicity, or route of exposure.
Abstract: Induction of antibodies that neutralize a broad range of human immunodeficiency virus type 1 (HIV-1) isolates is a major goal of vaccine development. To study natural examples of broad neutralization, we analyzed sera from 103 HIV-1-infected subjects. Among progressor patients, 20% of sera neutralized more than 75% of a panel of 20 diverse viral isolates. Little activity was observed in sera from long-term nonprogressors (elite controllers). Breadth of neutralization was correlated with viral load, but not with CD4 count, history of past antiretroviral use, age, gender, race/ethnicity, or route of exposure. Clustering analysis of sera by a novel method identified a statistically robust subgrouping of sera that demonstrated broad and potent neutralization activity.
University of Alabama at Birmingham1, Los Alamos National Laboratory2, University of Massachusetts Amherst3, Santa Fe Institute4, University of North Carolina at Chapel Hill5, Duke University6, Rockefeller University7, Aaron Diamond AIDS Research Center8, Science Applications International Corporation9
TL;DR: Higher multiplicity of HIV-1 infection in MSM compared with HSX is consistent with the demonstrably higher epidemiological risk of virus acquisition in MSM and could indicate a greater challenge for HIV- 1 vaccines than previously recognized.
Abstract: Elucidating virus-host interactions responsible for HIV-1 transmission is important for advancing HIV-1 prevention strategies. To this end, single genome amplification (SGA) and sequencing of HIV-1 within the context of a model of random virus evolution has made possible for the first time an unambiguous identification of transmitted/founder viruses and a precise estimation of their numbers. Here, we applied this approach to HIV-1 env analyses in a cohort of acutely infected men who have sex with men (MSM) and found that a high proportion (10 of 28; 36%) had been productively infected by more than one virus. In subjects with multivariant transmission, the minimum number of transmitted viruses ranged from 2 to 10 with viral recombination leading to rapid and extensive genetic shuffling among virus lineages. A combined analysis of these results, together with recently published findings based on identical SGA methods in largely heterosexual (HSX) cohorts, revealed a significantly higher frequency of multivariant transmission in MSM than in HSX [19 of 50 subjects (38%) versus 34 of 175 subjects (19%); Fisher’s exact p=0.008]. To further evaluate the SGA strategy for identifying transmitted/founder viruses, we analyzed 239 overlapping 59 and 39 half genome or env-only sequences from plasma viral RNA (vRNA) and blood mononuclear cell DNA in an MSM subject who had a particularly well-documented virus exposure history 3–6 days before symptom onset and 14–17 days before peak plasma viremia (47,600,000 vRNA molecules/ml). All 239 sequences coalesced to a single transmitted/founder virus genome in a time frame consistent with the clinical history, and a molecular clone of this genome encoded replication competent virus in accord with model predictions. Higher multiplicity of HIV-1 infection in MSM compared with HSX is consistent with the demonstrably higher epidemiological risk of virus acquisition in MSM and could indicate a greater challenge for HIV-1 vaccines than previously recognized.
TL;DR: Traces of immune escape were observed in the earliest samples, suggesting that immune pressure is present and effective earlier than previously reported; quantifying the loss rate of the founder virus suggests a direct role for CD8 T-lymphocyte responses in viral containment after peak viremia.
Abstract: We used ultra-deep sequencing to obtain tens of thousands of HIV-1 sequences from regions targeted by CD8+ T lymphocytes from longitudinal samples from three acutely infected subjects, and modeled viral evolution during the critical first weeks of infection. Previous studies suggested that a single virus established productive infection, but these conclusions were tempered because of limited sampling; now, we have greatly increased our confidence in this observation through modeling the observed earliest sample diversity based on vastly more extensive sampling. Conventional sequencing of HIV-1 from acute/early infection has shown different patterns of escape at different epitopes; we investigated the earliest escapes in exquisite detail. Over 3–6 weeks, ultradeep sequencing revealed that the virus explored an extraordinary array of potential escape routes in the process of evading the earliest CD8 T-lymphocyte responses – using 454 sequencing, we identified over 50 variant forms of each targeted epitope during early immune escape, while only 2–7 variants were detected in the same samples via conventional sequencing. In contrast to the diversity seen within epitopes, non-epitope regions, including the Envelope V3 region, which was sequenced as a control in each subject, displayed very low levels of variation. In early infection, in the regions sequenced, the consensus forms did not have a fitness advantage large enough to trigger reversion to consensus amino acids in the absence of immune pressure. In one subject, a genetic bottleneck was observed, with extensive diversity at the second time point narrowing to two dominant escape forms by the third time point, all within two months of infection. Traces of immune escape were observed in the earliest samples, suggesting that immune pressure is present and effective earlier than previously reported; quantifying the loss rate of the founder virus suggests a direct role for CD8 T-lymphocyte responses in viral containment after peak viremia. Dramatic shifts in the frequencies of epitope variants during the first weeks of infection revealed a complex interplay between viral fitness and immune escape.
TL;DR: A data set consisting of practically all actions of all players over a period of 3 years from a MMOG played by 300,000 people is compiled, demonstrating the feasibility for establishing a ‘socio-economic laboratory’ which allows to operate at levels of precision approaching those of the natural sciences.
TL;DR: In this paper, the authors define and obtain hierarchical trees, correlation based trees and networks from a correlation matrix, and associate a hierarchically nested factor model to a hierarchical tree obtained from the correlation matrix.
Abstract: We discuss some methods to quantitatively investigate the properties of correlation matrices. Correlation matrices play an important role in portfolio optimization and in several other quantitative descriptions of asset price dynamics in financial markets. Here, we discuss how to define and obtain hierarchical trees, correlation based trees and networks from a correlation matrix. The hierarchical clustering and other procedures performed on the correlation matrix to detect statistically reliable aspects of it are seen as filtering procedures of the correlation matrix. We also discuss a method to associate a hierarchically nested factor model to a hierarchical tree obtained from a correlation matrix. The information retained in filtering procedures and its stability with respect to statistical fluctuations is quantified by using the Kullback–Leibler distance.
TL;DR: Increased breadth and depth of epitope recognition may contribute both to protection against infection by genetically diverse viruses and to the control of variant viruses that emerge as they mutate away from recognition by cytotoxic T lymphocytes.
Abstract: Vaccine design is challenging when the infectious agent is genetically diverse. Polyvalent 'mosaic' antigens might be used to address this challenge, and these two studies show promising results in monkeys infected with HIV-1.
TL;DR: Perceived risk of infection and precautionary behavior can be dynamic in time, and differ by demographic characteristics and geographical locations, which will likely influence the effectiveness of disease control measures.
Abstract: The trajectory of an infectious disease outbreak is affected by the behavior of individuals, and the behavior is often related to individuals' risk perception. We assessed temporal changes and geographical differences in risk perceptions and precautionary behaviors in response to H1N1 influenza. 1,290 US adults completed an online survey on risk perceptions, interests in pharmaceutical interventions (preventive intervention and curative intervention), and engagement in precautionary activities (information seeking activities and taking quarantine measures) in response to H1N1 influenza between April 28 and May 27 2009. Associations of risk perceptions and precautionary behaviors with respondents' sex, age, and household size were analyzed. Linear and quadratic time trends were assessed by regression analyses. Geographic differences in risk perception and precautionary behaviors were evaluated. Predictors of willingness to take pharmaceutical intervention were analyzed. Respondents from larger households reported stronger interest in taking medications and engaged in more precautionary activities, as would be normatively predicted. Perceived risk increased over time, whereas interest in pharmaceutical preventive interventions and the engagement in some precautionary activities decreased over time. Respondents who live in states with higher H1N1 incidence per population perceived a higher likelihood of influenza infection, but did not express greater interests in pharmaceutical interventions, nor did they engage in a higher degree of precautionary activities. Perceived likelihood of influenza infection, willingness to take medications and engagement in information seeking activities were higher for women than men. Perceived risk of infection and precautionary behavior can be dynamic in time, and differ by demographic characteristics and geographical locations. These patterns will likely influence the effectiveness of disease control measures.
TL;DR: A new model can explain cultural clustering in human societies by combining the integrative tendencies of social influence with the disintegrative effects of individualization, and is robust to “noise”—randomness is actually the central mechanism that sustains pluralism and clustering.
Abstract: One of the most intriguing dynamics in biological systems is the emergence of clustering, in the sense that individuals self-organize into separate agglomerations in physical or behavioral space. Several theories have been developed to explain clustering in, for instance, multi-cellular organisms, ant colonies, bee hives, flocks of birds, schools of fish, and animal herds. A persistent puzzle, however, is the clustering of opinions in human populations, particularly when opinions vary continuously, such as the degree to which citizens are in favor of or against a vaccination program. Existing continuous opinion formation models predict “monoculture” in the long run, unless subsets of the population are perfectly separated from each other. Yet, social diversity is a robust empirical phenomenon, although perfect separation is hardly possible in an increasingly connected world. Considering randomness has not overcome the theoretical shortcomings so far. Small perturbations of individual opinions trigger social influence cascades that inevitably lead to monoculture, while larger noise disrupts opinion clusters and results in rampant individualism without any social structure. Our solution to the puzzle builds on recent empirical research, combining the integrative tendencies of social influence with the disintegrative effects of individualization. A key element of the new computational model is an adaptive kind of noise. We conduct computer simulation experiments demonstrating that with this kind of noise a third phase besides individualism and monoculture becomes possible, characterized by the formation of metastable clusters with diversity between and consensus within clusters. When clusters are small, individualization tendencies are too weak to prohibit a fusion of clusters. When clusters grow too large, however, individualization increases in strength, which promotes their splitting. In summary, the new model can explain cultural clustering in human societies. Strikingly, model predictions are not only robust to “noise”—randomness is actually the central mechanism that sustains pluralism and clustering.
TL;DR: It is shown that modularity can increase in gene regulatory networks as a byproduct of specialization in gene activity, and how modularityCan facilitate co-option, the utilization of existing gene activity to build new gene activity patterns, a frequent feature of evolutionary innovations.
Abstract: Organismal development and many cell biological processes are organized in a modular fashion, where regulatory molecules form groups with many interactions within a group and few interactions between groups. Thus, the activity of elements within a module depends little on elements outside of it. Modularity facilitates the production of heritable variation and of evolutionary innovations. There is no consensus on how modularity might evolve, especially for modules in development. We show that modularity can increase in gene regulatory networks as a byproduct of specialization in gene activity. Such specialization occurs after gene regulatory networks are selected to produce new gene activity patterns that appear in a specific body structure or under a specific environmental condition. Modules that arise after specialization in gene activity comprise genes that show concerted changes in gene activities. This and other observations suggest that modularity evolves because it decreases interference between different groups of genes. Our work can explain the appearance and maintenance of modularity through a mechanism that is not contingent on environmental change. We also show how modularity can facilitate co-option, the utilization of existing gene activity to build new gene activity patterns, a frequent feature of evolutionary innovations.
TL;DR: An updated estimate of R is provided that takes into account the epidemic data from 29 May to 14 July, and the next-generation matrix predicts that only 17.5% of the population will experience infection by the end of the first pandemic wave.
Abstract: In many parts of the world, the exponential growth rate of infections during the initial epidemic phase has been used to make statistical inferences on the reproduction number, R, a summary measure of the transmission potential for the novel influenza A (H1N1) 2009. The growth rate at the initial stage of the epidemic in Japan led to estimates for R in the range 2.0 to 2.6, capturing the intensity of the initial outbreak among school-age children in May 2009. An updated estimate of R that takes into account the epidemic data from 29 May to 14 July is provided. An age-structured renewal process is employed to capture the age-dependent transmission dynamics, jointly estimating the reproduction number, the age-dependent susceptibility and the relative contribution of imported cases to secondary transmission. Pitfalls in estimating epidemic growth rates are identified and used for scrutinizing and re-assessing the results of our earlier estimate of R. Maximum likelihood estimates of R using the data from 29 May to 14 July ranged from 1.21 to 1.35. The next-generation matrix, based on our age-structured model, predicts that only 17.5% of the population will experience infection by the end of the first pandemic wave. Our earlier estimate of R did not fully capture the population-wide epidemic in quantifying the next-generation matrix from the estimated growth rate during the initial stage of the pandemic in Japan. In order to quantify R from the growth rate of cases, it is essential that the selected model captures the underlying transmission dynamics embedded in the data. Exploring additional epidemiological information will be useful for assessing the temporal dynamics. Although the simple concept of R is more easily grasped by the general public than that of the next-generation matrix, the matrix incorporating detailed information (e.g., age-specificity) is essential for reducing the levels of uncertainty in predictions and for assisting public health policymaking. Model-based prediction and policymaking are best described by sharing fundamental notions of heterogeneous risks of infection and death with non-experts to avoid potential confusion and/or possible misuse of modelling results.
TL;DR: A theory for plant network scaling that is based on optimal space filling by the vascular system along with trade-offs between hydraulic safety and efficiency is developed, suggesting that the evolutionary drivers that are proposed have been fundamental in determining how physiological processes scale within and across plant species.
Abstract: Plant vascular networks are central to botanical form, function, and diversity. Here, we develop a theory for plant network scaling that is based on optimal space filling by the vascular system along with trade-offs between hydraulic safety and efficiency. Including these evolutionary drivers leads to predictions for sap flow, the taper of the radii of xylem conduits from trunk to terminal twig, and how the frequency of xylem conduits varies with conduit radius. To test our predictions, we use comprehensive empirical measurements of maple, oak, and pine trees and complementary literature data that we obtained for a wide range of tree species. This robust intra- and interspecific assessment of our botanical network model indicates that the central tendency of observed scaling properties supports our predictions much better than the West, Brown, and Enquist (WBE) or pipe models. Consequently, our model is a more accurate description of vascular architecture than what is given by existing network models and should be used as a baseline to understand and to predict the scaling of individual plants to whole forests. In addition, our model is flexible enough to allow the quantification of species variation around rules for network design. These results suggest that the evolutionary drivers that we propose have been fundamental in determining how physiological processes scale within and across plant species.
TL;DR: In this paper, the structure of neutron stars in f(R) gravity theories with perturbative constraints was studied and the modified Toltnan-Oppenheimer-Volkov equations were solved for a polytropic equation of state.
Abstract: We study the structure of neutron stars in f(R) gravity theories with perturbative constraints. We derive the modified Toltnan-Oppenheimer-Volkov equations and solve them for a polytropic equation of state. We investigate the resulting modifications to the masses and radii of neutron stars and show that observations of surface phenomena alone cannot break the degeneracy between altering the theory of gravity versus choosing a different equation of state of neutron-star matter. On the other hand, observations of neutron-star cooling, which depends on the density of matter at the stellar interior, can place significant constraints on the parameters of the theory.
TL;DR: Sex-antagonistic alleles can become more strongly associated with pleiotropically dominant sex-determining factors, which may help to explain biases in the rates of transitions between male and female heterogamety.
Abstract: Many animal taxa show frequent and rapid transitions between male heterogamety (XY) and female heterogamety (ZW). We develop a model showing how these transitions can be driven by sex-antagonistic selection. Sex-antagonistic selection acting on loci linked to a new sex-determination mutation can cause it to invade, but when acting on loci linked to the ancestral sex-determination gene will inhibit an invasion. The strengths of the consequent indirect selection on the old and new sex-determination loci are mediated by the strengths of sex-antagonistic selection, linkage between the sex-antagonistic and sex-determination genes, and the amount of genetic variation. Sex-antagonistic loci that are tightly linked to a sex-determining gene have a vastly stronger influence on the balance of selection than more distant loci. As a result, changes in linkage, caused, for example, by an inversion that captures a sex-determination mutation and a gene under sex-antagonistic selection, can trigger transitions between XY and ZW systems. Sex-antagonistic alleles can become more strongly associated with pleiotropically dominant sex-determining factors, which may help to explain biases in the rates of transitions between male and female heterogamety. Deleterious recessive mutations completely linked to the ancestral Y chromosome can prevent invasion of a neo-W chromosome or result in a stable equilibrium at which XY and ZW systems segregate simultaneously at two linkage groups.
TL;DR: Current knowledge supports ATB as an essential ingredient for models of community dynamics, and future research that incorporates ATB will be well positioned to address questions important for basic ecological research and its applications.
Abstract: Ecology Letters (2010) 13: 1546–1559
Abstract
Species coexistence within ecosystems and the stability of patterns of temporal changes in population sizes are central topics in ecological theory. In the last decade, adaptive behaviour has been proposed as a mechanism of population stabilization. In particular, widely distributed adaptive trophic behaviour (ATB), the fitness-enhancing changes in individuals’ feeding-related traits due to variation in their trophic environment, may play a key role in modulating the dynamics of feeding relationships within natural communities. In this article, we review and synthesize models and results from theoretical research dealing with the consequences of ATB on the structure and dynamics of complex food webs. We discuss current approaches, point out limitations, and consider questions ripe for future research. In spite of some differences in the modelling and analytic approaches, there are points of convergence: (1) ATB promotes the complex structure of ecological networks, (2) ATB increases the stability of their dynamics, (3) ATB reverses May’s negative complexity–stability relationship, and (4) ATB provides resilience and resistance of networks against perturbations. Current knowledge supports ATB as an essential ingredient for models of community dynamics, and future research that incorporates ATB will be well positioned to address questions important for basic ecological research and its applications.
TL;DR: A four-phase colonization model is put forward in which Paleolithic migrations of hunter-gatherers shape the primary structure of current Indonesian Y chromosome diversity, and Neolithic incursions make only a minor impact on the paternal gene pool, despite the large cultural impact of the Austronesian expansion.
Abstract: The early history of island Southeast Asia is often characterized as the story of two major population dispersals: the initial Paleolithic colonization of Sahul approximately 45 ka ago and the much later Neolithic expansion of Austronesian-speaking farmers approximately 4 ka ago. Here, in the largest survey of Indonesian Y chromosomes to date, we present evidence for multiple genetic strata that likely arose through a series of distinct migratory processes. We genotype an extensive battery of Y chromosome markers, including 85 single-nucleotide polymorphisms/indels and 12 short tandem repeats, in a sample of 1,917 men from 32 communities located across Indonesia. We find that the paternal gene pool is sharply subdivided between western and eastern locations, with a boundary running between the islands of Bali and Flores. Analysis of molecular variance reveals one of the highest levels of between-group variance yet reported for human Y chromosome data (e.g., Phi(ST) = 0.47). Eastern Y chromosome haplogroups are closely related to Melanesian lineages (i.e., within the C, M, and S subclades) and likely reflect the initial wave of colonization of the region, whereas the majority of western Y chromosomes (i.e., O-M119*, O-P203, and O-M95*) are related to haplogroups that may have entered Indonesia during the Paleolithic from mainland Asia. In addition, two novel markers (P201 and P203) provide significantly enhanced phylogenetic resolution of two key haplogroups (O-M122 and O-M119) that are often associated with the Austronesian expansion. This more refined picture leads us to put forward a four-phase colonization model in which Paleolithic migrations of hunter-gatherers shape the primary structure of current Indonesian Y chromosome diversity, and Neolithic incursions make only a minor impact on the paternal gene pool, despite the large cultural impact of the Austronesian expansion.
TL;DR: The present crisis is the bottom of a recurring problem that I call the leverage cycle, in which leverage gradually rises too high then suddenly falls much too low as discussed by the authors, and the government must manage this leverage cycle in normal times by monitoring and regulating leverage to keep it from getting too high.
Abstract: The present crisis is the bottom of a recurring problem that I call the leverage cycle, in which leverage gradually rises too high then suddenly falls much too low. The government must manage the leverage cycle in normal times by monitoring and regulating leverage to keep it from getting too high. In the crisis stage the government must stem the scary bad news that brought on the crisis, which often will entail coordinated write downs of principal; it must restore sane leverage by going around the banks and lending at lower collateral rates (not lower interest rates), and when necessary it must inject optimistic capital into firms and markets than cannot be allowed to fail. Economists and the Fed have for too long focused on interest rates and ignored collateral.
TL;DR: This model predicts a constant rate of speciation, and provides a new interpretation of the Red Queen: the metaphor of species losing a race against a deteriorating environment is replaced by a view linking speciation to rare stochastic events that cause reproductive isolation.
Abstract: The Red Queen metaphor has species accumulating small changes to keep up with a continually changing environment, with speciation occurring at a constant rate This constant-rate claim is now tested against four competing models, using 101 phylogenies of animal, plant and fungal taxa The results provide a new interpretation of the Red Queen; a view linking speciation to rare stochastic events that cause reproductive isolation
TL;DR: It is argued that understanding the acquisition of any cultural form, whether linguistic or otherwise, during development, requires considering the corresponding question of how that cultural form arose through processes of cultural evolution, which helps resolve the "logical" problem of language acquisition.
13 Dec 2010
TL;DR: In this article, the authors present a statistical comparison of the general Rwandan population to the population of mobile phone owners in Rwanda and find that phone owners are considerably wealthier, better educated, and more predominantly male than the general population.
Abstract: We combine data from a field survey with transaction log data from a mobile phone operator to provide new insight into daily patterns of mobile phone use in Rwanda. The analysis is divided into three parts. First, we present a statistical comparison of the general Rwandan population to the population of mobile phone owners in Rwanda. We find that phone owners are considerably wealthier, better educated, and more predominantly male than the general population. Second, we analyze patterns of phone use and access, based on self-reported survey data. We note statistically significant differences by gender; for instance, women are more likely to use shared phones than men. Third, we perform a quantitative analysis of calling patterns and social network structure using mobile operator billing logs. By these measures, the differences between men and women are more modest, but we observe vast differences in utilization between the relatively rich and the relatively poor. Taken together, the evidence in this paper suggests that phones are disproportionately owned and used by the privileged strata of Rwandan society.