Santa Fe Institute

About: Santa Fe Institute is a nonprofit organization based out in Santa Fe, New Mexico, United States. It is known for research contribution in the topics: Population & Context (language use). The organization has 558 authors who have published 4558 publications receiving 396015 citations. The organization is also known as: SFI.

Information measures, effective complexity, and total information

Abstract: This article defines the concept of an information measure and shows how common information measures such as entropy, Shannon information, and algorithmic information content can be combined to solve problems of characterization, inference, and learning for complex systems. Particularly useful quantities are the effective complexity, which is roughly the length of a compact description of the identified regularities of an entity, and total information, which is effective complexity plus an entropy term that measures the information required to describe the random aspects of the entity. Mathematical definitions are given for both quantities and some applications are discussed. In particular, it is pointed out that if one compares different sets of identified regularities of an entity, the ‘best’ set minimizes the total information, and then, subject to that constraint, minimizes the effective complexity; the resulting effective complexity is then in many respects independent of the observer. © 1996 John Wiley & Sons, Inc.

Transmission of Single HIV-1 Genomes and Dynamics of Early Immune Escape Revealed by Ultra-Deep Sequencing

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.

Emulation, Inequality, and Work Hours: Was Thorsten Veblen Right?

Abstract: We investigate the manner in which a desire to emulate the rich influences individuals allocation of time between labour and leisure, greater inequality inducing longer work hours as a result. Data on work hours in ten countries over the period 1963‐98 show that greater inequality is indeed associated longer work hours. These Veblen effects are large and the estimates are robust using country fixed effects and other specifications. Because consumption inequality is a public bad, a social welfare optimum cannot be implemented by a flat tax on consumption but may be accomplished by more complicated (progressive) consumption taxes. At the close of the nineteenth century, Thorsten Veblen proposed what he termed pecuniary emulation as the foundation of a theory of consumption. Spending, he maintained, is driven by relative status considerations, that is by the desire to be a particular type of person as much as bythedesire to enjoytheconsumer goodsper se. The Joneses, with whom one had to keep up, were not the neighbours but the rich; theirleveloflivingbecamethenever-attainableobjectiveinaconsumptionarmsrace among the less well-to-do. In The Theory of the Leisure Class, he wrote: The motive is emulation ‐ the stimulus of an invidious comparison ... especially in any community in which class distinctions are quite vague, all canons and reputability and decency and all standards of consumption are traced back by insensible gradations to the usages and thoughts of the highest social and pecuniary class, the wealthy leisure class. (1934, p. 81). While valued by some economists as capturing common-sense aspects of consumption as a form of status seeking, Veblen’s view of social preferences was soon eclipsed by the simpler and more tractable neoclassical theory of the consumer. Relegated to the underworld of economics, Veblen’s ideas have nonetheless resonated over the ensuing years in the writing of Duesenberry (1949), Leibenstein (1950) and Galbraith (1958) at the middle of the past century and Schor (1998)

Scaling from Traits to Ecosystems: Developing a General Trait Driver Theory via Integrating Trait-Based and Metabolic Scaling Theories

Abstract: Aim: More powerful tests of biodiversity theories need to move beyond species richness and explicitly focus on mechanisms generating diversity via trait composition The rise of trait-based ecology has led to an increased focus on the distribution and dynamics of traits across broad geographic and climatic gradients and how these distributions influence ecosystem function However, a general theory of trait-based ecology, that can apply across different scales (eg species that differ in size) and gradients (eg temperature), has yet to be formulated While research focused on metabolic and allometric scaling theory provides the basis for such a theory, it does not explicitly account for differences in traits within and across taxa, such as variation in the optimal temperature for growth Here we synthesize trait-based and metabolic scaling approaches into a framework that we term ‘Trait Driver Theory’ or TDT It shows that the shape and dynamics of trait and size distributions can be linked to fundamental drivers of community assembly and how the community will respond to future drivers To assess predictions and assumptions of TDT, we review several theoretical studies and recent empirical studies spanning local and biogeographic gradients Further, we analyze how the shift in trait distributions influences ecosystem processes across an elevational gradient and a 140-year-long ecological experiment We show that TDT provides a baseline for (i) recasting the predictions of ecological theories based on species richness in terms of the shape of trait distributions and (ii) integrating how specific traits, including body size, and functional diversity then ‘scale up’ to influence ecosystem functioning and the dynamics of species assemblages across climate gradients Further, TDT offers a novel framework to integrate trait, metabolic/allometric, and species-richness-based approaches to better predict functional biogeography and how assemblages of species have and may respond to climate change

Analysing ecological networks of species interactions.

Abstract: Network approaches to ecological questions have been increasingly used, particularly in recent decades. The abstraction of ecological systems - such as communities - through networks of interactions between their components indeed provides a way to summarize this information with single objects. The methodological framework derived from graph theory also provides numerous approaches and measures to analyze these objects and can offer new perspectives on established ecological theories as well as tools to address new challenges. However, prior to using these methods to test ecological hypotheses, it is necessary that we understand, adapt, and use them in ways that both allow us to deliver their full potential and account for their limitations. Here, we attempt to increase the accessibility of network approaches by providing a review of the tools that have been developed so far, with - what we believe to be - their appropriate uses and potential limitations. This is not an exhaustive review of all methods and metrics, but rather, an overview of tools that are robust, informative, and ecologically sound. After providing a brief presentation of species interaction networks and how to build them in order to summarize ecological information of different types, we then classify methods and metrics by the types of ecological questions that they can be used to answer from global to local scales, including methods for hypothesis testing and future perspectives. Specifically, we show how the organization of species interactions in a community yields different network structures (e.g., more or less dense, modular or nested), how different measures can be used to describe and quantify these emerging structures, and how to compare communities based on these differences in structures. Within networks, we illustrate metrics that can be used to describe and compare the functional and dynamic roles of species based on their position in the network and the organization of their interactions as well as associated new methods to test the significance of these results. Lastly, we describe potential fruitful avenues for new methodological developments to address novel ecological questions.