971 resultados para biological evolution
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In this paper a mathematical model based on mass transfer in plant tissues is developed. The model takes into account the diffusion and convection of each constituent within the tissue. The driving force for the convection is assumed to be the gradient of hydrostatic pressure. The mass balance equation for the transport of each constituent is established separately for intracellular and extracellular volumes but taking into account the mass exchange across the cell membrane between the intracellular and extracellular volumes. The mass transfer results in not only the change of intracellular and extracellular volumes but also the shrinkage of whole tissue. The model allows us to quantitatively simulate the time evolution of intracellular and extracellular volumes, which was observed in histological sections under the microscope. © 2005 Elsevier B.V. All rights reserved.
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Bayesian algorithms pose a limit to the performance learning algorithms can achieve. Natural selection should guide the evolution of information processing systems towards those limits. What can we learn from this evolution and what properties do the intermediate stages have? While this question is too general to permit any answer, progress can be made by restricting the class of information processing systems under study. We present analytical and numerical results for the evolution of on-line algorithms for learning from examples for neural network classifiers, which might include or not a hidden layer. The analytical results are obtained by solving a variational problem to determine the learning algorithm that leads to maximum generalization ability. Simulations using evolutionary programming, for programs that implement learning algorithms, confirm and expand the results. The principal result is not just that the evolution is towards a Bayesian limit. Indeed it is essentially reached. In addition we find that evolution is driven by the discovery of useful structures or combinations of variables and operators. In different runs the temporal order of the discovery of such combinations is unique. The main result is that combinations that signal the surprise brought by an example arise always before combinations that serve to gauge the performance of the learning algorithm. This latter structures can be used to implement annealing schedules. The temporal ordering can be understood analytically as well by doing the functional optimization in restricted functional spaces. We also show that there is data suggesting that the appearance of these traits also follows the same temporal ordering in biological systems. © 2006 American Institute of Physics.
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Leaf colour change is commonly observed in temperate deciduous forests in autumn. This is not simply a side effect of leaf senescence, and, in the past decade, several hypotheses have emerged to explain the evolution of autumn colours. Yet a lack of crosstalk between plant physiologists and evolutionary ecologists has resulted in slow progress, and so the adaptive value of this colour change remains a mystery. Here we provide an interdisciplinary summary of the current body of knowledge on autumn colours, and discuss unresolved issues and future avenues of research that might help reveal the evolutionary meaning of this spectacle of nature.
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Ocean acidification, the drop in seawater pH associated with the ongoing enrichment of marine waters with carbon dioxide from fossil fuel burning, may seriously impair marine calcifying organisms. Our present understanding of the sensitivity of marine life to ocean acidification is based primarily on short-term experiments, in which organisms are exposed to increased concentrations of CO2. However, phytoplankton species with short generation times, in particular, may be able to respond to environmental alterations through adaptive evolution. Here, we examine the ability of the world's single most important calcifying organism, the coccolithophore Emiliania huxleyi, to evolve in response to ocean acidification in two 500-generation selection experiments. Specifically, we exposed E. huxleyi populations founded by single or multiple clones to increased concentrations of CO2. Around 500 asexual generations later we assessed their fitness. Compared with populations kept at ambient CO2 partial pressure, those selected at increased partial pressure exhibited higher growth rates, in both the single- and multiclone experiment, when tested under ocean acidification conditions. Calcification was partly restored: rates were lower under increased CO2 conditions in all cultures, but were up to 50% higher in adapted compared with non-adapted cultures. We suggest that contemporary evolution could help to maintain the functionality of microbial processes at the base of marine food webs in the face of global change.
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The exponential growth of studies on the biological response to ocean acidification over the last few decades has generated a large amount of data. To facilitate data comparison, a data compilation hosted at the data publisher PANGAEA was initiated in 2008 and is updated on a regular basis (doi:10.1594/PANGAEA.149999). By January 2015, a total of 581 data sets (over 4 000 000 data points) from 539 papers had been archived. Here we present the developments of this data compilation five years since its first description by Nisumaa et al. (2010). Most of study sites from which data archived are still in the Northern Hemisphere and the number of archived data from studies from the Southern Hemisphere and polar oceans are still relatively low. Data from 60 studies that investigated the response of a mix of organisms or natural communities were all added after 2010, indicating a welcomed shift from the study of individual organisms to communities and ecosystems. The initial imbalance of considerably more data archived on calcification and primary production than on other processes has improved. There is also a clear tendency towards more data archived from multifactorial studies after 2010. For easier and more effective access to ocean acidification data, the ocean acidification community is strongly encouraged to contribute to the data archiving effort, and help develop standard vocabularies describing the variables and define best practices for archiving ocean acidification data.
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The effect of pCO2 on carbon acquisition and intracellular assimilation was investigated in the three bloom-forming diatom species, Eucampia zodiacus (Ehrenberg), Skeletonema costatum (Greville) Cleve, Thalassionema nitzschioides (Grunow) Mereschkowsky and the non-bloom-forming Thalassiosira pseudonana (Hust.) Hasle and Heimdal. In vivo activities of carbonic anhydrase (CA), photosynthetic O2 evolution, CO2 and HCO3? uptake rates were measured by membrane-inlet mass spectrometry (MIMS) in cells acclimated to pCO2 levels of 370 and 800 ?atm. To investigate whether the cells operate a C4-like pathway, activities of ribulose-1,5-bisphosphate carboxylase (RubisCO) and phosphoenolpyruvate carboxylase (PEPC) were measured at the mentioned pCO2 levels and a lower pCO2 level of 50 ?atm. In the bloom-forming species, extracellular CA activities strongly increased with decreasing CO2 supply while constantly low activities were obtained for T. pseudonana. Half-saturation concentrations (K1/2) for photosynthetic O2 evolution decreased with decreasing CO2 supply in the two bloom-forming species S. costatum and T. nitzschioides, but not in T. pseudonana and E. zodiacus. With the exception of S. costatum, maximum rates (Vmax) of photosynthesis remained constant in all investigated diatom species. Independent of the pCO2 level, PEPC activities were significantly lower than those for RubisCO, averaging generally less than 3%. All examined diatom species operate highly efficient CCMs under ambient and high pCO2, but differ strongly in the degree of regulation of individual components of the CCM such as Ci uptake kinetics and extracellular CA activities. The present data do not suggest C4 metabolism in the investigated species.
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Peer reviewed
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Acknowledgments We thank A. B. Duthie, S. Losdat, and M. E. Wolak for useful discussions and comments and the European Research Council for funding. We also thank the two reviewers, whose suggestions greatly improved the manuscript.
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Peer reviewed
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Acknowledgments We thank A. B. Duthie, S. Losdat, and M. E. Wolak for useful discussions and comments and the European Research Council for funding. We also thank the two reviewers, whose suggestions greatly improved the manuscript.
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Peer reviewed
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Peer reviewed