Planarian (Platyhelminthes, Tricladida) Diversity and Molecular Markers: A New View of an Old Group

Planarians are a group of free-living platyhelminths (triclads) best-known largely due to long-standing regeneration and pattern formation research. However, the group"s diversity and evolutionary history has been mostly overlooked. A few taxonomists have focused on certain groups, resulting in the description of many species and the establishment of higher-level groups within the Tricladida. However, the scarcity of morphological features precludes inference of phylogenetic relationships among these taxa. The incorporation of molecular markers to study their diversity and phylogenetic relationships has facilitated disentangling many conundrums related to planarians and even allowed their use as phylogeographic model organisms. Here, we present some case examples ranging from delimiting species in an integrative style, and barcoding them, to analysing their evolutionary history on a lower scale to infer processes affecting biodiversity origin, or on a higher scale to understand the genus level or even higher relationships. In many cases, these studies have allowed proposing better classifications and resulted in taxonomical changes. We also explain shortcomings resulting in a lack of resolution or power to apply the most up-to-date data analyses. Next-generation sequencing methodologies may help improve this situation and accelerate their use as model organisms

Earth as a Hybrid Planet - The Anthropocene in an Evolutionary Astrobiological Context

We develop a classification scheme for the evolutionary state of planets based on the non-equilibrium thermodynamics of their coupled systems, including the presence of a biosphere and the possibility of what we call an agency-dominated biosphere (i.e. an energy-intensive technological species). The premise is that Earths entry into the Anthropocene represents what might be from an astrobiological perspective a predictable planetary transition. We explore this problem from the perspective of the solar system and exoplanet studies. Our classification discriminates planets by the forms of free energy generation driven from stellar forcing. We then explore how timescales for global evolutionary processes on Earth might be synchronized with ecological transformations driven by increases in energy harvesting and its consequences (which might have reached a turning point with global urbanization). Finally, we describe quantitatively the classification scheme based on the maintenance of chemical disequilibrium in the past and current Earth systems and on other worlds in the solar system. In this perspective, the beginning of the Anthropocene can be seen as the onset of the hybridization of the planet - a transitional stage from one class of planetary systems interaction to another. For Earth, this stage occurs as the effects of human civilization yield not just new evolutionary pressures, but new selected directions for novel planetary ecosystem functions and their capacity to generate disequilibrium and enhance planetary dissipation.Comment: Accepted for publication in the journal Anthropocen

Influence of initial distributions on robust cooperation in evolutionary Prisoner's Dilemma

We study the evolutionary Prisoner's Dilemma game on scale-free networks for different initial distributions. We consider three types of initial distributions for cooperators and defectors: initially random distribution with different frequencies of defectors; intentional organization with defectors initially occupying the most connected nodes with different fractions of defectors; intentional assignment for cooperators occupying the most connected nodes with different proportions of defectors at the beginning. It is shown that initial configurations for cooperators and defectors can influence the stationary level of cooperation and the evolution speed of cooperation. Organizations with the vertices with highest connectivity representing individuals cooperators could exhibit the most robust cooperation and drive evolutionary process to converge fastest to the high steady cooperation in the three situations of initial distributions. Otherwise, we determine the critical initial frequencies of defectors above which the extinction of cooperators occurs for the respective initial distributions, and find that the presence of network loops and clusters for cooperators can favor the emergence of cooperation.Comment: Submitted to EP

Symbiosis through exploitation and the merger of lineages in evolution

A model for the coevolution of two species in facultative symbiosis is used to investigate conditions under which species merge to form a single reproductive unit. Two traits evolve in each species, the first affecting loss of resources from an individual to its partner, and the second affecting vertical transmission of the symbiosis from one generation to the next. Initial conditions are set so that the symbiosis involves exploitation of one partner by the other and vertical transmission is very rare. It is shown that, even in the face of continuing exploitation, a stable symbiotic unit can evolve with maximum vertical transmission of the partners. Such evolution requires that eventually deaths should exceed births for both species in the free-living state, a condition which can be met if the victim, in the course of developing its defences, builds up sufficiently large costs in the free-living state. This result expands the set of initial conditions from which separate lineages can be expected to merge into symbiotic units

The world of strategies with memory

As part of a generalized ”prisoners’ dilemma”, is considered that the evolution of a population with a full set of behavioral strategies limited only by the depth of memory. Each subsequent generation of the population successively loses the most disadvantageous strategies of behavior of the previous generation. It is shown that an increase in memory in a population is evolutionarily beneficial. The winners of evolutionary selection invariably refer to agents with maximum memory. The concept of strategy complexity is introduced. It is shown that strategies that win in natural selection have maximum or near maximum complexity. Despite the fact that at a separate stage of evolution, according to the payout matrix, the individual gain, while refusing to cooperate, exceeded the gain obtained while cooperating. The winning strategies always belonged to the so-called respectable strategies that are clearly prone to cooperation

Evolutionary improvement of programs

Most applications of genetic programming (GP) involve the creation of an entirely new function, program or expression to solve a specific problem. In this paper, we propose a new approach that applies GP to improve existing software by optimizing its non-functional properties such as execution time, memory usage, or power consumption. In general, satisfying non-functional requirements is a difficult task and often achieved in part by optimizing compilers. However, modern compilers are in general not always able to produce semantically equivalent alternatives that optimize non-functional properties, even if such alternatives are known to exist: this is usually due to the limited local nature of such optimizations. In this paper, we discuss how best to combine and extend the existing evolutionary methods of GP, multiobjective optimization, and coevolution in order to improve existing software. Given as input the implementation of a function, we attempt to evolve a semantically equivalent version, in this case optimized to reduce execution time subject to a given probability distribution of inputs. We demonstrate that our framework is able to produce non-obvious optimizations that compilers are not yet able to generate on eight example functions. We employ a coevolved population of test cases to encourage the preservation of the function's semantics. We exploit the original program both through seeding of the population in order to focus the search, and as an oracle for testing purposes. As well as discussing the issues that arise when attempting to improve software, we employ rigorous experimental method to provide interesting and practical insights to suggest how to address these issues

A New Foundation for the Propensity Interpretation of Fitness

The propensity interpretation of fitness (PIF) is commonly taken to be subject to a set of simple counterexamples. We argue that three of the most important of these are not counterexamples to the PIF itself, but only to the traditional mathematical model of this propensity: fitness as expected number of offspring. They fail to demonstrate that a new mathematical model of the PIF could not succeed where this older model fails. We then propose a new formalization of the PIF that avoids these (and other) counterexamples. By producing a counterexample-free model of the PIF, we call into question one of the primary motivations for adopting the statisticalist interpretation of fitness. In addition, this new model has the benefit of being more closely allied with contemporary mathematical biology than the traditional model of the PIF