Subterranean glacial spillways: an example from the karst of South Wales, UK

Many karst areas in the UK have been glaciated one or more times during the last 0.5 Ma, yet there are few documented examples of caves in these regions being affected by glacial processes other than erosion. The karst of South Wales is one area where sub or pro-glacial modification of pre-existing caves is thought to occur. Evidence from the Ogof Draenen cave system suggests that caves can sometimes act as subterranean glacial ‘underspill’ channels for melt-water. This cave, one of the longest in Britain with a surveyed length of over 70 km, underlies the interfluve between two glaciated valleys. Sediment fills and speleo-morphological observations indicate that melt-water from a high level glacier in the Afon Lwyd valley (>340m asl) filled part of the cave and over-spilled into the neighbouring Usk valley, temporarily reversing non-glacial groundwater flow directions in the cave. It is suggested that this may have occurred during a Middle Pleistocene glaciation

Extremism propagation in social networks with hubs

One aspect of opinion change that has been of academic interest is the impact of people with extreme opinions (extremists) on opinion dynamics. An agent-based model has been used to study the role of small-world social network topologies on general opinion change in the presence of extremists. It has been found that opinion convergence to a single extreme occurs only when the average number of network connections for each individual is extremely high. Here, we extend the model to examine the effect of positively skewed degree distributions, in addition to small-world structures, on the types of opinion convergence that occur in the presence of extremists. We also examine what happens when extremist opinions are located on the well-connected nodes (hubs) created by the positively skewed distribution. We find that a positively skewed network topology encourages opinion convergence on a single extreme under a wider range of conditions than topologies whose degree distributions were not skewed. The importance of social position for social influence is highlighted by the result that, when positive extremists are placed on hubs, all population convergence is to the positive extreme even when there are twice as many negative extremists. Thus, our results have shown the importance of considering a positively skewed degree distribution, and in particular network hubs and social position, when examining extremist transmission

Behavioral Differences Between Two Recently Sympatric Paper Wasps, the Native \u3ci\u3ePolistes Fuscatus\u3c/i\u3e and the Invasive \u3ci\u3ePolistes Dominulus\u3c/i\u3e

Polistes dominulus (Christ), an old world paper wasp, was introduced into the eastern United States in the 1970s and has been rapidly spreading westward. Recently, it has displaced the native Polistes fuscatus (F.) in at least some areas of Michigan. In order to understand why P. dominulus has been so successful, several behavioral attributes were compared between P. dominulus and P. fuscatus at a Michigan field site that contained colonies of both species nest- ing semi-naturally in plywood nestboxes. Preworker colonies of P. dominulus had a significantly greater tendency to store nectar (and had significantly higher proportions of cells with nectar) than preworker colonies of P. fuscatus. This finding may explain the higher survivorship of P. dominulus foundresses reported in a previous study. P. dominulus also had a significantly greater tendency to build vertical nests and had significantly more pedicels per comb and per cell than P. fuscatus. These findings suggest that compared to P. fuscatus, P. dominulus may have more flexibility in the positioning of its combs and, because of a possibly stronger attachment of the comb to a substrate, may be less susceptible to bird predation. The higher winter survivorship reported for P. fuscatus over P. dominulus in a previous study does not appear to be due to differences in the proportions of gynes stranded on their nests late in the fall. Finally, behavioral evidence from videography was consistent with previous reports that P. dominulus is not replacing P. fuscatus through direct agonistic interactions

Long-Term Impact of Leucaena-Based Grazing Systems on Soil Acidity

Soil acidification and land degradation issues are assuming increasing importance in Australia and challenging the concept of sustainablity of current land management systems. In this study the impact of a 22 year old Leucaena leucocephala / Urochloa mosambicensis (Leucaena) pasture production system on soil acidification and selected soil chemical properties was compared to an adjacent Urochloa mosambicensis (Sabi) area. Significant acidification and cation depletion was observed to 70 cm under the Leucaena when compared to the Sabi system. The net acidification rate for the Leucaena system was estimated to be 2.73 kmol H+ ha-1 yr-1 of which 0.17 kmol H+ ha-1 yr-1 was estimated to have originated from animal product removal. These preliminary results bring into question the long-term sustainability of these legume based production systems

Solving the division of labour problem using stigmergy and evolved heterogeneity (abstract)

Evolving cooperative teams is a research area with applications in the fields of robotics and software agents. Progress on this problem could also help us to understand the evolution of cooperation in natural systems such as the social insects. The overarching question is how cooperative teams should be represented in order to promote efficient evolutionary search. More specifically, what should serve as our basic unit of selection— the individual or the team? —and how can the division-of-labour problem be solved? In order to answer these questions we have taken a benchmark problem from the genetic programming (GP) literature, the artificial ant problem, and extended it so that teams of ants must cooperate to complete the task. In this model, the ants are centrally placed in a bounded grid with each square containing food. The goal of the team is to harvest all the food in the environment in as few moves as possible. In the initial version of the problem, the members of the team are all clones, each having exactly the same GP controller program. Many solutions will have poor performance as the team members will all behave in the same way, and will therefore fail to cover the grid efficiently. To perform better, the ants must evolve to take advantage of stigmergic interactions to break the symmetry of the problem and clear the world of food efficiently. This division of labour through stigmergy is indeed what is seen to evolve during the simulations. A further extension is made by assigning each member of the team an identity tag, and adding the ability to execute different subtrees of the cloned controller based on this tag. When these operations are allowed, higher fitnesses are achieved than with the purely stigmergic situation above. During evolution, selection acts at the team level. We can therefore view the members of the team as being equivalent to cells in a multicellular organism. The identity branching operation is analogous to cell differentiation within this abstract organism. Using this scheme, the degree of differentiation is not specified a-priori and is controllable through evolution. This allows the full continuum from purely homogeneous teams to entirely heterogeneous teams to be expressed. There is also the potential to use this method as a way of measuring the degree to which a task demands heterogeneous solutions. The relative importance of stigmergy and innate heterogeneity in achieving the necessary division of labour were compared with a third experimental manipulation. The ability to influence each other stigmergically was removed by placing each ant in it’s own world and tallying the pieces of food consumed by the team as a whole. In this scenario, the most efficient way to tackle the problem is for the team to evolve complete heterogeneity. We conclude that the division-of-labour problem in the evolution of cooperative teams can be solved by both stigmergic communication and innate heterogeneity. Furthermore, the technique of allowing the level of heterogeneity of the team to be open to selection shows promise for future work

What can artificial life offer ecology? (abstract)

Artificial life is the simulation and synthesis of living systems, and ALife models show how interactions between simple entities give rise to complex effects. Ecology is the study of the distribution and abundance of organisms, and ecological modelling involves fitting a linear model to a large data set and using that model to identify key causal factors at work in a complex ecosystem. We are interested in whether the individualbased modelling approach of ALife can be usefully employed in ecology. ALife models are “opaque thought experiments” (Di Paolo et al., 2000, Proc. ALife VII, p.497). They show that a phenomenon can arise from a given set of assumptions in cases where the implication is not clear from intuition alone: e.g., that spatial structure in a population can lead to altruistic behaviour. This type of modelling can be useful to ecology by showing the plausibility of a novel concept or process, which in turn suggests new natural experiments and new forms of data to collect. However, we argue that ALife models can go beyond this “proof of concept” role and serve as a direct account of data in the same way that statistical models do. We focus on a typical problem from ecology: the effect of clearing powerline corridors through a forest on the local wildlife populations (Clarke et al., 2006,Wildlife Research, 33, p.615). The real data set in this case is complex and, of course, we don’t know the true effects that underlie it. We therefore generated a fictional data set that reflects aspects of the original problem while allowing complete control over the simulated environment. The idea is to construct a test case for looking at the relative success of different modelling approaches. We know the true picture because we generated the data, but which modelling approach will get closer to the truth? The fitting of generalized linear models as is conventional in ecology, or the use of individual-based simulations as in ALife? Statistical models are fitted using some variant of the method of maximum likelihood: given the data, which of the models in the family we’re considering (e.g., a linear regression) makes the observed data most plausible? When dealing with simulations, however, it is difficult to establish that one model is a better fit to data than another. Simulations have many parameters, it may be difficult to determine a level of granularity at which the simulation output is supposed to “match” the data, and there will be no analytically tractable likelihood function. These problems are solved by the method of indirect inference (Gouri´eroux et al., 1993, J. Applied Econometrics, 8, p.S85) in which an auxiliary model is fitted to both the real data and to the output from competing simulation models. The best simulation model is the one producing the closest match to the data in terms of fitted parameter values in the auxiliary model. Using indirect inference with our fictional data set we demonstrate that ALife simulation models can be fitted to realistic ecological data, that they can out-compete standard statistical approaches, and that they can thus be used in ecology for more than just conceptual exploration

Type II critical phenomena of neutron star collapse

We investigate spherically-symmetric, general relativistic systems of collapsing perfect fluid distributions. We consider neutron star models that are driven to collapse by the addition of an initially "in-going" velocity profile to the nominally static star solution. The neutron star models we use are Tolman-Oppenheimer-Volkoff solutions with an initially isentropic, gamma-law equation of state. The initial values of 1) the amplitude of the velocity profile, and 2) the central density of the star, span a parameter space, and we focus only on that region that gives rise to Type II critical behavior, wherein black holes of arbitrarily small mass can be formed. In contrast to previously published work, we find that--for a specific value of the adiabatic index (Gamma = 2)--the observed Type II critical solution has approximately the same scaling exponent as that calculated for an ultrarelativistic fluid of the same index. Further, we find that the critical solution computed using the ideal-gas equations of state asymptotes to the ultrarelativistic critical solution.Comment: 24 pages, 22 figures, RevTeX 4, submitted to Phys. Rev.