A Functional Naturalism

I provide two arguments against value-free naturalism. Both are based on considerations concerning biological teleology. Value-free naturalism is the thesis that both (1) everything is, at least in principle, under the purview of the sciences and (2) all scientific facts are purely non-evaluative. First, I advance a counterexample to any analysis on which natural selection is necessary to biological teleology. This should concern the value-free naturalist, since most value-free analyses of biological teleology appeal to natural selection. My counterexample is unique in that it is likely to actually occur. It concerns the creation of synthetic life. Recent developments in synthetic biology suggest scientists will eventually be able to develop synthetic life. Such life, however, would not have any of its traits naturally selected for. Second, I develop a simple argument that biological teleology is a scientific but value-laden notion. Consequently, value-free naturalism is false. I end with some concluding remarks on the implications for naturalism, the thesis that (1). Naturalism may be salvaged only if we reject (2). (2) is a dogma that unnecessarily constrains our conception of the sciences. Only a naturalism that recognizes value-laden notions as scientifically respectable can be true. Such a naturalism is a functional naturalism

Comparing the hierarchy of keywords in on-line news portals

The tagging of on-line content with informative keywords is a widespread phenomenon from scientific article repositories through blogs to on-line news portals. In most of the cases, the tags on a given item are free words chosen by the authors independently. Therefore, relations among keywords in a collection of news items is unknown. However, in most cases the topics and concepts described by these keywords are forming a latent hierarchy, with the more general topics and categories at the top, and more specialised ones at the bottom. Here we apply a recent, cooccurrence-based tag hierarchy extraction method to sets of keywords obtained from four different on-line news portals. The resulting hierarchies show substantial differences not just in the topics rendered as important (being at the top of the hierarchy) or of less interest (categorised low in the hierarchy), but also in the underlying network structure. This reveals discrepancies between the plausible keyword association frameworks in the studied news portals

Integrated information increases with fitness in the evolution of animats

One of the hallmarks of biological organisms is their ability to integrate disparate information sources to optimize their behavior in complex environments. How this capability can be quantified and related to the functional complexity of an organism remains a challenging problem, in particular since organismal functional complexity is not well-defined. We present here several candidate measures that quantify information and integration, and study their dependence on fitness as an artificial agent ("animat") evolves over thousands of generations to solve a navigation task in a simple, simulated environment. We compare the ability of these measures to predict high fitness with more conventional information-theoretic processing measures. As the animat adapts by increasing its "fit" to the world, information integration and processing increase commensurately along the evolutionary line of descent. We suggest that the correlation of fitness with information integration and with processing measures implies that high fitness requires both information processing as well as integration, but that information integration may be a better measure when the task requires memory. A correlation of measures of information integration (but also information processing) and fitness strongly suggests that these measures reflect the functional complexity of the animat, and that such measures can be used to quantify functional complexity even in the absence of fitness data.Comment: 27 pages, 8 figures, one supplementary figure. Three supplementary video files available on request. Version commensurate with published text in PLoS Comput. Bio

Science and economics in the management of an invasive species

Author Posting. © American Institute of Biological Sciences, 2006. This article is posted here by permission of American Institute of Biological Sciences for personal use, not for redistribution. The definitive version was published in BioScience 56 (2006): 931-935, doi: 10.1641/0006-3568(2006)56[931:SAEITM]2.0.CO;2Estimates of the economic impacts of nonnative nuisance ("invasive") species must rely on both a sound ecological understanding and the proper application of economic methods. Focusing on the example of the invasive European green crab (Carcinus maenas), we show that the crab's estimated economic impact—which has been used to help justify recent public policy—is based on data taken from the wrong geographic location. Furthermore, the predictions of ecological effects appear to rest on loose footing, and economic methods have been misapplied in constructing the estimate. Our purpose is to call attention to the need for the more careful application of science and economics in managing this pressing environmental issue.This work was supported by a research grant from the US Department of Commerce,National Oceanic and Atmospheric Administration, Project no. NA16RG1698

Degeneracy: a link between evolvability, robustness and complexity in biological systems

A full accounting of biological robustness remains elusive; both in terms of the mechanisms by which robustness is achieved and the forces that have caused robustness to grow over evolutionary time. Although its importance to topics such as ecosystem services and resilience is well recognized, the broader relationship between robustness and evolution is only starting to be fully appreciated. A renewed interest in this relationship has been prompted by evidence that mutational robustness can play a positive role in the discovery of adaptive innovations (evolvability) and evidence of an intimate relationship between robustness and complexity in biology. This paper offers a new perspective on the mechanics of evolution and the origins of complexity, robustness, and evolvability. Here we explore the hypothesis that degeneracy, a partial overlap in the functioning of multi-functional components, plays a central role in the evolution and robustness of complex forms. In support of this hypothesis, we present evidence that degeneracy is a fundamental source of robustness, it is intimately tied to multi-scaled complexity, and it establishes conditions that are necessary for system evolvability

‘O sibling, where art thou?’ – a review of avian sibling recognition with respect to the mammalian literature

Avian literature on sibling recognition is rare compared to that developed by mammalian researchers. We compare avian and mammalian research on sibling recognition to identify why avian work is rare, how approaches differ and what avian and mammalian researchers can learn from each other. Three factors: (1) biological differences between birds and mammals, (2) conceptual biases and (3) practical constraints, appear to influence our current understanding. Avian research focuses on colonial species because sibling recognition is considered adaptive where ‘mixing potential’ of dependent young is high; research on a wider range of species, breeding systems and ecological conditions is now needed. Studies of acoustic recognition cues dominate avian literature; other types of cues (e.g. visual, olfactory) deserve further attention. The effect of gender on avian sibling recognition has yet to be investigated; mammalian work shows that gender can have important influences. Most importantly, many researchers assume that birds recognise siblings through ‘direct familiarisation’ (commonly known as associative learning or familiarity); future experiments should also incorporate tests for ‘indirect familiarisation’ (commonly known as phenotype matching). If direct familiarisation proves crucial, avian research should investigate how periods of separation influence sibling discrimination. Mammalian researchers typically interpret sibling recognition in broad functional terms (nepotism, optimal outbreeding); some avian researchers more successfully identify specific and testable adaptive explanations, with greater relevance to natural contexts. We end by reporting exciting discoveries from recent studies of avian sibling recognition that inspire further interest in this topic

How large should whales be?

The evolution and distribution of species body sizes for terrestrial mammals is well-explained by a macroevolutionary tradeoff between short-term selective advantages and long-term extinction risks from increased species body size, unfolding above the 2g minimum size induced by thermoregulation in air. Here, we consider whether this same tradeoff, formalized as a constrained convection-reaction-diffusion system, can also explain the sizes of fully aquatic mammals, which have not previously been considered. By replacing the terrestrial minimum with a pelagic one, at roughly 7000g, the terrestrial mammal tradeoff model accurately predicts, with no tunable parameters, the observed body masses of all extant cetacean species, including the 175,000,000g Blue Whale. This strong agreement between theory and data suggests that a universal macroevolutionary tradeoff governs body size evolution for all mammals, regardless of their habitat. The dramatic sizes of cetaceans can thus be attributed mainly to the increased convective heat loss is water, which shifts the species size distribution upward and pushes its right tail into ranges inaccessible to terrestrial mammals. Under this macroevolutionary tradeoff, the largest expected species occurs where the rate at which smaller-bodied species move up into large-bodied niches approximately equals the rate at which extinction removes them.Comment: 7 pages, 3 figures, 2 data table

The Minimal Complexity of Adapting Agents Increases with Fitness

What is the relationship between the complexity and the fitness of evolved organisms, whether natural or artificial? It has been asserted, primarily based on empirical data, that the complexity of plants and animals increases as their fitness within a particular environment increases via evolution by natural selection. We simulate the evolution of the brains of simple organisms living in a planar maze that they have to traverse as rapidly as possible. Their connectome evolves over 10,000s of generations. We evaluate their circuit complexity, using four information-theoretical measures, including one that emphasizes the extent to which any network is an irreducible entity. We find that their minimal complexity increases with their fitness

The Geozoic Supereon

Geological time units are the lingua franca of earth sciences: they are a terminological convenience, a vernacular of any geological conversation, and a prerequisite of geo-scientific writing found throughout in earth science dictionaries and textbooks. Time units include terms formalized by stratigraphic committees as well as informal constructs erected ad hoc to communicate more efficiently. With these time terms we partition Earth’s history into utilitarian and intuitively understandable time segments that vary in length over seven orders of magnitude: from the 225-year-long Anthropocene (Crutzen and Stoermer, 2000) to the ,4-billion-year-long Precambrian (e.g., Hicks, 1885; Ball, 1906; formalized by De Villiers, 1969)

Astrobiological Complexity with Probabilistic Cellular Automata

Search for extraterrestrial life and intelligence constitutes one of the major endeavors in science, but has yet been quantitatively modeled only rarely and in a cursory and superficial fashion. We argue that probabilistic cellular automata (PCA) represent the best quantitative framework for modeling astrobiological history of the Milky Way and its Galactic Habitable Zone. The relevant astrobiological parameters are to be modeled as the elements of the input probability matrix for the PCA kernel. With the underlying simplicity of the cellular automata constructs, this approach enables a quick analysis of large and ambiguous input parameters' space. We perform a simple clustering analysis of typical astrobiological histories and discuss the relevant boundary conditions of practical importance for planning and guiding actual empirical astrobiological and SETI projects. In addition to showing how the present framework is adaptable to more complex situations and updated observational databases from current and near-future space missions, we demonstrate how numerical results could offer a cautious rationale for continuation of practical SETI searches.Comment: 37 pages, 11 figures, 2 tables; added journal reference belo