57,777 research outputs found

    LIFE HISTORY SWITCH POINT PLASTICY IN RESPONSE TO POND DRYING ALYERS METAMORPH ALLOMETRY AND JUMPING PERFORMANCE

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    Animals with complex life cycles can cope with environmental uncertainty by altering life history switch points through developmental plasticity. Pond drying is an important factor which may alter life history switch points in aquatic organisms. Many amphibians can plastically respond to changes in pond drying by emerging earlier, but few studies have examined the post-metamorphic consequences for performance. To investigate the potential carry-over effects of plasticity to pond drying, we studied the túngara frog, Physalaemus pustulosus, a tropical anuran that breeds in highly ephemeral habitats. We conducted a field study with three different water depth treatments in 60 L mesocosms and measured time and size at metamorphosis, hind limb length and jumping performance. We also conducted a complimentary laboratory study that manipulated resources and water depth. In the field experiment, metamorphs from dry-down treatments emerged earlier, but at a similar size to constant volume treatments. In the laboratory experiment, metamorphs from the low depth and dry-down treatments emerged both earlier and smaller. In both studies, frogs from dry-down treatments had relatively shorter hind limbs, which negatively impacted their jumping performance. Reductions in resources delayed and reduced size at metamorphosis, but had no effect on jumping performance. We demonstrate that conditions experienced early in ontogeny can transcend the metamorphic boundary by erasing the relationship between hind limb length and jumping performance

    Artificial and Natural Genetic Information Processing

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    Conventional methods of genetic engineering and more recent genome editing techniques focus on identifying genetic target sequences for manipulation. This is a result of historical concept of the gene which was also the main assumption of the ENCODE project designed to identify all functional elements in the human genome sequence. However, the theoretical core concept changed dramatically. The old concept of genetic sequences which can be assembled and manipulated like molecular bricks has problems in explaining the natural genome-editing competences of viruses and RNA consortia that are able to insert or delete, combine and recombine genetic sequences more precisely than random-like into cellular host organisms according to adaptational needs or even generate sequences de novo. Increasing knowledge about natural genome editing questions the traditional narrative of mutations (error replications) as essential for generating genetic diversity and genetic content arrangements in biological systems. This may have far-reaching consequences for our understanding of artificial genome editing

    From metagenomics to the metagenome: Conceptual change and the rhetoric of translational genomic research

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    As the international genomic research community moves from the tool-making efforts of the Human Genome Project into biomedical applications of those tools, new metaphors are being suggested as useful to understanding how our genes work – and for understanding who we are as biological organisms. In this essay we focus on the Human Microbiome Project as one such translational initiative. The HMP is a new ‘metagenomic’ research effort to sequence the genomes of human microbiological flora, in order to pursue the interesting hypothesis that our ‘microbiome’ plays a vital and interactive role with our human genome in normal human physiology. Rather than describing the human genome as the ‘blueprint’ for human nature, the promoters of the HMP stress the ways in which our primate lineage DNA is interdependent with the genomes of our microbiological flora. They argue that the human body should be understood as an ecosystem with multiple ecological niches and habitats in which a variety of cellular species collaborate and compete, and that human beings should be understood as ‘superorganisms’ that incorporate multiple symbiotic cell species into a single individual with very blurry boundaries. These metaphors carry interesting philosophical messages, but their inspiration is not entirely ideological. Instead, part of their cachet within genome science stems from the ways in which they are rooted in genomic research techniques, in what philosophers of science have called a ‘tools-to-theory’ heuristic. Their emergence within genome science illustrates the complexity of conceptual change in translational research, by showing how it reflects both aspirational and methodological influences

    Deriving mesoscopic models of collective behaviour for finite populations

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    Animal groups exhibit emergent properties that are a consequence of local interactions. Linking individual-level behaviour to coarse-grained descriptions of animal groups has been a question of fundamental interest. Here, we present two complementary approaches to deriving coarse-grained descriptions of collective behaviour at so-called mesoscopic scales, which account for the stochasticity arising from the finite sizes of animal groups. We construct stochastic differential equations (SDEs) for a coarse-grained variable that describes the order/consensus within a group. The first method of construction is based on van Kampen's system-size expansion of transition rates. The second method employs Gillespie's chemical Langevin equations. We apply these two methods to two microscopic models from the literature, in which organisms stochastically interact and choose between two directions/choices of foraging. These `binary-choice' models differ only in the types of interactions between individuals, with one assuming simple pair-wise interactions, and the other incorporating higher-order effects. In both cases, the derived mesoscopic SDEs have multiplicative, or state-dependent, noise. However, the different models demonstrate the contrasting effects of noise: increasing order in the pair-wise interaction model, whilst reducing order in the higher-order interaction model. Although both methods yield identical SDEs for such binary-choice, or one-dimensional, systems, the relative tractability of the chemical Langevin approach is beneficial in generalizations to higher-dimensions. In summary, this book chapter provides a pedagogical review of two complementary methods to construct mesoscopic descriptions from microscopic rules and demonstrates how resultant multiplicative noise can have counter-intuitive effects on shaping collective behaviour.Comment: Second version, 4 figures, 2 appendice

    Predation effects on mean time to extinction under demographic stochasticity

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    Methods for predicting the probability and timing of a species' extinction are typically based on a combination of theoretical models and empirical data, and focus on single species population dynamics. Of course, species also interact with each other, forming more or less complex networks of interactions. Models to assess extinction risk often lack explicit incorporation of these interspecific interactions. We study a birth and death process in which the death rate includes an effect from predation. This predation rate is included via a general nonlinear expression for the functional response of predation to prey density. We investigate the effects of the foraging parameters (e.g. attack rate and handling time) on the mean time to extinction. Mean time to extinction varies by orders of magnitude when we alter the foraging parameters, even when we exclude the effects of these parameters on the equilibrium population size. In particular we observe an exponential dependence of the mean time to extinction on handling time. These findings clearly show that accounting for the nature of interspecific interactions is likely to be critically important when estimating extinction risk.Comment: 11 pages, 4 figures; Typos removed. For further discussion about the paper go to http://purl.org/net/extinctio

    Understories: A Common Ground For Art And Science

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    Simple identification tools in FishBase

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    Simple identification tools for fish species were included in the FishBase information system from its inception. Early tools made use of the relational model and characters like fin ray meristics. Soon pictures and drawings were added as a further help, similar to a field guide. Later came the computerization of existing dichotomous keys, again in combination with pictures and other information, and the ability to restrict possible species by country, area, or taxonomic group. Today, www.FishBase.org offers four different ways to identify species. This paper describes these tools with their advantages and disadvantages, and suggests various options for further development. It explores the possibility of a holistic and integrated computeraided strategy

    Receptor uptake arrays for vitamin B12, siderophores and glycans shape bacterial communities

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    Molecular variants of vitamin B12, siderophores and glycans occur. To take up variant forms, bacteria may express an array of receptors. The gut microbe Bacteroides thetaiotaomicron has three different receptors to take up variants of vitamin B12 and 88 receptors to take up various glycans. The design of receptor arrays reflects key processes that shape cellular evolution. Competition may focus each species on a subset of the available nutrient diversity. Some gut bacteria can take up only a narrow range of carbohydrates, whereas species such as B.~thetaiotaomicron can digest many different complex glycans. Comparison of different nutrients, habitats, and genomes provide opportunity to test hypotheses about the breadth of receptor arrays. Another important process concerns fluctuations in nutrient availability. Such fluctuations enhance the value of cellular sensors, which gain information about environmental availability and adjust receptor deployment. Bacteria often adjust receptor expression in response to fluctuations of particular carbohydrate food sources. Some species may adjust expression of uptake receptors for specific siderophores. How do cells use sensor information to control the response to fluctuations? That question about regulatory wiring relates to problems that arise in control theory and artificial intelligence. Control theory clarifies how to analyze environmental fluctuations in relation to the design of sensors and response systems. Recent advances in deep learning studies of artificial intelligence focus on the architecture of regulatory wiring and the ways in which complex control networks represent and classify environmental states. I emphasize the similar design problems that arise in cellular evolution, control theory, and artificial intelligence. I connect those broad concepts to testable hypotheses for bacterial uptake of B12, siderophores and glycans.Comment: Added many new references, edited throughou
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