Methodological guidelines for the design, implementation and assessment of Digital Action

This report aims to create the conditions for the co-creation of Digital Action between citizens, HE staff and students. It is intended as the basis for a set of methodological guidelines for the design, implementation and assessment of digital activities by High Education Institutions. All the information is based on existing guidelines and insights on the barriers and drivers of Digital Action

Species abundance patterns in an ecosystem simulation studied through Fisher's logseries

We have developed an individual-based evolving predator-prey ecosystem simulation that integrates, for the first time, a complex individual behaviour model, an evolutionary mechanism and a speciation process, at an acceptable computational cost. In this article, we analyse the species abundance patterns observed in the communities generated by our simulation, based on Fisher's logseries. We propose a rigorous methodology for testing abundance data against the logseries. We show that our simulation produces coherent results, in terms of relative species abundance, when compared to classical ecological patterns. Some preliminary results are also provided about how our simulation is supporting ecological field results

Balancing Robustness and Evolvability

Can a single unifying mathematical framework help to explain robustness - the ability of organisms to persist in the face of changing conditions - at all biological scales, from biochemical to ecological

Self-recognition and Ca2+-dependent carbohydrate–carbohydrate cell adhesion provide clues to the Cambrian explosion

Author Posting. © The Authors, 2009. This is the author's version of the work. It is posted here by permission of Oxford University Press for personal use, not for redistribution. The definitive version was published in Molecular Biology and Evolution 26 (2009): 2551-2561, doi:10.1093/molbev/msp170.The Cambrian explosion of life was a relatively short period ca. 540 million years ago that marked a generalized acceleration in the evolution of most animal phyla, but the trigger of this key biological event remains elusive. Sponges are the oldest extant Precambrian metazoan phylum and thus a valid model to study factors that could have unleashed the rise of multicellular animals. One such factor is the advent of self/non-self recognition systems, which would be evolutionarily beneficial to organisms to prevent germ cell parasitism or the introduction of deleterious mutations resulting from fusion with genetically different individuals. However, the molecules responsible for allorecognition probably evolved gradually before the Cambrian period, and some other (external) factor remains to be identified as the missing triggering event. Sponge cells associate through calcium-dependent, multivalent carbohydrate-carbohydrate interactions of the g200 glycan found on extracellular proteoglycans. Single molecule force spectroscopy analysis of g200-g200 binding indicates that calcium affects the lifetime (+Ca/-Ca: 680 s/3 s) and bond reaction length (+Ca/-Ca: 3.47 Å/2.27 Å). Calculation of mean g200 dissociation times in low and high calcium within the theoretical framework of a cooperative binding model indicates the non-linear and divergent characteristics leading to either disaggregated cells or stable multicellular assemblies, respectively. This fundamental phenomenon can explain a switch from weak to strong adhesion between primitive metazoan cells caused by the well documented rise in ocean calcium levels at the end of Precambrian time. We propose that stronger cell adhesion allowed the integrity of genetically uniform animals composed only of “self” cells, facilitating genetic constitutions to remain within the metazoan individual and be passed down inheritance lines. The Cambrian explosion might have been triggered by the coincidence in time of primitive animals endowed with self/non-self recognition, and of a surge in sea water calcium that increased the binding forces between their calcium-dependent cell adhesion molecules.D.A. and A.K. acknowledge financial support from the Collaborative Research Center SFB 613 from the Deutsche Forschungsgemeinschaft (DFG), and X.F.-B. acknowledges financial support from grants BIO2002-00128, BIO2005-01591, and CSD2006-00012 from the Ministerio de Ciencia y Tecnología, Spain, which included Fondo Europeo de Desarrollo Regional funds, and from grant 2005SGR-00037 from the Generalitat de Catalunya, Spain

Genetic information transfer promotes cooperation in bacteria

Many bacterial species are social, producing costly secreted “public good” molecules that enhance the growth of neighboring cells. The genes coding for these cooperative traits are often propagated via mobile genetic elements and can be virulence factors from a biomedical perspective. Here, we present an experimental framework that links genetic information exchange and the selection of cooperative traits. Using simulations and experiments based on a synthetic bacterial system to control public good secretion and plasmid conjugation, we demonstrate that horizontal gene transfer can favor cooperation. In a well-mixed environment, horizontal transfer brings a direct infectious advantage to any gene, regardless of its cooperation properties. However, in a structured population transfer selects specifically for cooperation by increasing the assortment among cooperative alleles. Conjugation allows cooperative alleles to overcome rarity thresholds and invade bacterial populations structured purely by stochastic dilution effects. Our results provide an explanation for the prevalence of cooperative genes on mobile elements, and suggest a previously unidentified benefit of horizontal gene transfer for bacteria

The effects of low-impact mutations in digital organisms

<p>Abstract</p> <p>Background</p> <p>Avida is a computer program that performs evolution experiments with digital organisms. Previous work has used the program to study the evolutionary origin of complex features, namely logic operations, but has consistently used extremely large mutational fitness effects. The present study uses Avida to better understand the role of low-impact mutations in evolution.</p> <p>Results</p> <p>When mutational fitness effects were approximately 0.075 or less, no new logic operations evolved, and those that had previously evolved were lost. When fitness effects were approximately 0.2, only half of the operations evolved, reflecting a threshold for selection breakdown. In contrast, when Avida's default fitness effects were used, all operations routinely evolved to high frequencies and fitness increased by an average of 20 million in only 10,000 generations.</p> <p>Conclusions</p> <p>Avidian organisms evolve new logic operations only when mutations producing them are assigned high-impact fitness effects. Furthermore, purifying selection cannot protect operations with low-impact benefits from mutational deterioration. These results suggest that selection breaks down for low-impact mutations below a certain fitness effect, the <it>selection threshold</it>. Experiments using biologically relevant parameter settings show the tendency for increasing genetic load to lead to loss of biological functionality. An understanding of such genetic deterioration is relevant to human disease, and may be applicable to the control of pathogens by use of lethal mutagenesis.</p

Natural Selection Fails to Optimize Mutation Rates for Long-Term Adaptation on Rugged Fitness Landscapes

The rate of mutation is central to evolution. Mutations are required for adaptation, yet most mutations with phenotypic effects are deleterious. As a consequence, the mutation rate that maximizes adaptation will be some intermediate value. Here, we used digital organisms to investigate the ability of natural selection to adjust and optimize mutation rates. We assessed the optimal mutation rate by empirically determining what mutation rate produced the highest rate of adaptation. Then, we allowed mutation rates to evolve, and we evaluated the proximity to the optimum. Although we chose conditions favorable for mutation rate optimization, the evolved rates were invariably far below the optimum across a wide range of experimental parameter settings. We hypothesized that the reason that mutation rates evolved to be suboptimal was the ruggedness of fitness landscapes. To test this hypothesis, we created a simplified landscape without any fitness valleys and found that, in such conditions, populations evolved near-optimal mutation rates. In contrast, when fitness valleys were added to this simple landscape, the ability of evolving populations to find the optimal mutation rate was lost. We conclude that rugged fitness landscapes can prevent the evolution of mutation rates that are optimal for long-term adaptation. This finding has important implications for applied evolutionary research in both biological and computational realms

Promoting scientific literacy in evolution through citizen science

Evolutionary understanding is central to biology. It is also an essential prerequisite to understanding and making informed decisions about societal issues such as climate change. Yet, evolution is generally poorly understood by civil society and many misconceptions exist. Citizen science, which has been increasing in popularity as a means to gather new data and promote scientific literacy, is one strategy through which people could learn about evolution. However, despite the potential for citizen science to promote evolution learning opportunities, very few projects implement them. In this paper, we make the case for incorporating evolution education into citizen science, define key learning goals, and suggest opportunities for designing and evaluating projects in order to promote scientific literacy in evolution