On the volunteer’s dilemma I: Continuous-time decision

It is assumed that there is a group of unrelated individuals taken at random from a large population which is exposed to the same time-continuous threat of dying. Accumulated loss of each player increases as the game goes on until at least one participant volunteers to take some extra risk on its own. The risk is taken by a volunteer in order to stop the threat may or may not depend on the time of volunteering. This situation can be modeled as an n-player War of Attrition, which ends when one of the players volunteers. We called this sort of generalization, "The (n-player) volunteer dilemma". Indeed, a two-player volunteer dilemma is equivalent to the original War of Attrition. It was further assumed that both the risk for the volunteer and the intensity of the risk of waiting are time dependent according to some integrable function, this instead of being constants as assumed in the original War of Attrition model of Maynard Smith. Necessary and sufficient conditions for a strategy to be a Nash strategy are given. This strategy is characterized by a time-intensity of volunteering. In the stationary case the Nash strategy is proven to be ESS

Linkage and Physical Mapping of Sex Region on LG23 of Nile Tilapia (Oreochromis niloticus)

Evidence supports that sex determination (SD) in tilapia is controlled by major genetic factors that may interact with minor genetic as well as environmental factors, thus implying that SD should be analyzed as a quantitative trait. Quantitative trait loci (QTL) for SD in Oreochromis niloticus were previously detected on linkage groups (LG) 1 and 23. Twenty-one short single repeats (SSR) of >12 TGs and one single nucleotide polymorphism were identified using the unpublished tilapia genome sequence on LG23. All markers showed two segregating alleles in a mapping family that was obtained by a cross between O. niloticus male (XY) and sex-reversed female (ΔXY) yielding 29 females (XX) and 61 males (XY and YY). Interval mapping analysis mapped the QTL peak between SSR markers ARO172 and ARO177 with a maximum F value of 78.7 (P < 7.6 × 10−14). Twelve adjacent markers found in this region were homozygous in females and either homozygous for the alternative allele or heterozygous in males. This segment was defined as the sex region (SR). The SR encompasses 1.5 Mbp on a single tilapia scaffold (no. 101) harboring 51 annotated genes. Among 10 candidate genes for SD that were tested for gene expression, anti-Müllerian hormone (Amh), which is located in the center of the SR, showed the highest overexpression in male vs. female embryos at 3 to 7 days postfertilization

Random Topologies and the emergence of cooperation: the role of short-cuts

We study in detail the role of short-cuts in promoting the emergence of cooperation in a network of agents playing the Prisoner's Dilemma Game (PDG). We introduce a model whose topology interpolates between the one-dimensional euclidean lattice (a ring) and the complete graph by changing the value of one parameter (the probability p to add a link between two nodes not already connected in the euclidean configuration). We show that there is a region of values of p in which cooperation is largely enhanced, whilst for smaller values of p only a few cooperators are present in the final state, and for p \rightarrow 1- cooperation is totally suppressed. We present analytical arguments that provide a very plausible interpretation of the simulation results, thus unveiling the mechanism by which short-cuts contribute to promote (or suppress) cooperation

Group selection models in prebiotic evolution

The evolution of enzyme production is studied analytically using ideas of the group selection theory for the evolution of altruistic behavior. In particular, we argue that the mathematical formulation of Wilson's structured deme model ({\it The Evolution of Populations and Communities}, Benjamin/Cumings, Menlo Park, 1980) is a mean-field approach in which the actual environment that a particular individual experiences is replaced by an {\it average} environment. That formalism is further developed so as to avoid the mean-field approximation and then applied to the problem of enzyme production in the prebiotic context, where the enzyme producer molecules play the altruists role while the molecules that benefit from the catalyst without paying its production cost play the non-altruists role. The effects of synergism (i.e., division of labor) as well as of mutations are also considered and the results of the equilibrium analysis are summarized in phase diagrams showing the regions of the space of parameters where the altruistic, non-altruistic and the coexistence regimes are stable. In general, those regions are delimitated by discontinuous transition lines which end at critical points.Comment: 22 pages, 10 figure

Dynamic instabilities induced by asymmetric influence: Prisoners' dilemma game on small-world networks

A two-dimensional small-world type network, subject to spatial prisoners' dilemma dynamics and containing an influential node defined as a special node with a finite density of directed random links to the other nodes in the network, is numerically investigated. It is shown that the degree of cooperation does not remain at a steady state level but displays a punctuated equilibrium type behavior manifested by the existence of sudden breakdowns of cooperation. The breakdown of cooperation is linked to an imitation of a successful selfish strategy of the influential node. It is also found that while the breakdown of cooperation occurs suddenly, the recovery of it requires longer time. This recovery time may, depending on the degree of steady state cooperation, either increase or decrease with an increasing number of long range connections.Comment: 5 pages, 6 figure

Traffic Instabilities in Self-Organized Pedestrian Crowds

In human crowds as well as in many animal societies, local interactions among individuals often give rise to self-organized collective organizations that offer functional benefits to the group. For instance, flows of pedestrians moving in opposite directions spontaneously segregate into lanes of uniform walking directions. This phenomenon is often referred to as a smart collective pattern, as it increases the traffic efficiency with no need of external control. However, the functional benefits of this emergent organization have never been experimentally measured, and the underlying behavioral mechanisms are poorly understood. In this work, we have studied this phenomenon under controlled laboratory conditions. We found that the traffic segregation exhibits structural instabilities characterized by the alternation of organized and disorganized states, where the lifetime of well-organized clusters of pedestrians follow a stretched exponential relaxation process. Further analysis show that the inter-pedestrian variability of comfortable walking speeds is a key variable at the origin of the observed traffic perturbations. We show that the collective benefit of the emerging pattern is maximized when all pedestrians walk at the average speed of the group. In practice, however, local interactions between slow- and fast-walking pedestrians trigger global breakdowns of organization, which reduce the collective and the individual payoff provided by the traffic segregation. This work is a step ahead toward the understanding of traffic self-organization in crowds, which turns out to be modulated by complex behavioral mechanisms that do not always maximize the group's benefits. The quantitative understanding of crowd behaviors opens the way for designing bottom-up management strategies bound to promote the emergence of efficient collective behaviors in crowds.Comment: Article published in PLoS Computational biology. Freely available here: http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.100244

Towards developmental modelling of tree root systems

Knowledge of belowground structures and processes is essential for understanding and predicting ecosystem functioning, and consequently in the development of adaptive strategies to safeguard production from trees and woody plants into the future. In the past, research has mainly been concentrated on growth models for the prediction of agronomic or forest production. Newly emerging scientific challenges, e.g. climate change and sustainable development, call for new integrated predictive methods where root systems development will become a key element for understanding global biological systems. The types of input data available from the various branches of woody root research, including biomass allocation, architecture, biomechanics, water and nutrient supply, are discussed with a view to the possibility of incorporating them into a more generic developmental model. We discuss here the main focus of root system modelling to date, including a description of simple allometric biomass models, and biomechanical stress models, and then build in complexity through static growth models towards architecture models. The next progressive and logical step in developing an inclusive developmental model that integrates these modelling approaches is discussed.Knowledge of belowground structures and processes is essential for understanding and predicting ecosystem functioning, and consequently in the development of adaptive strategies to safeguard production from trees and woody plants into the future. In the past, research has mainly been concentrated on growth models for the prediction of agronomic or forest production. Newly emerging scientific challenges, e.g. climate change and sustainable development, call for new integrated predictive methods where root systems development will become a key element for understanding global biological systems. The types of input data available from the various branches of woody root research, including biomass allocation, architecture, biomechanics, water and nutrient supply, are discussed with a view to the possibility of incorporating them into a more generic developmental model. We discuss here the main focus of root system modelling to date, including a description of simple allometric biomass models, and biomechanical stress models, and then build in complexity through static growth models towards architecture models. The next progressive and logical step in developing an inclusive developmental model that integrates these modelling approaches is discussed.Knowledge of belowground structures and processes is essential for understanding and predicting ecosystem functioning, and consequently in the development of adaptive strategies to safeguard production from trees and woody plants into the future. In the past, research has mainly been concentrated on growth models for the prediction of agronomic or forest production. Newly emerging scientific challenges, e.g. climate change and sustainable development, call for new integrated predictive methods where root systems development will become a key element for understanding global biological systems. The types of input data available from the various branches of woody root research, including biomass allocation, architecture, biomechanics, water and nutrient supply, are discussed with a view to the possibility of incorporating them into a more generic developmental model. We discuss here the main focus of root system modelling to date, including a description of simple allometric biomass models, and biomechanical stress models, and then build in complexity through static growth models towards architecture models. The next progressive and logical step in developing an inclusive developmental model that integrates these modelling approaches is discussed.Peer reviewe

Mesoscopic structure conditions the emergence of cooperation on social networks

We study the evolutionary Prisoner's Dilemma on two social networks obtained from actual relational data. We find very different cooperation levels on each of them that can not be easily understood in terms of global statistical properties of both networks. We claim that the result can be understood at the mesoscopic scale, by studying the community structure of the networks. We explain the dependence of the cooperation level on the temptation parameter in terms of the internal structure of the communities and their interconnections. We then test our results on community-structured, specifically designed artificial networks, finding perfect agreement with the observations in the real networks. Our results support the conclusion that studies of evolutionary games on model networks and their interpretation in terms of global properties may not be sufficient to study specific, real social systems. In addition, the community perspective may be helpful to interpret the origin and behavior of existing networks as well as to design structures that show resilient cooperative behavior.Comment: Largely improved version, includes an artificial network model that fully confirms the explanation of the results in terms of inter- and intra-community structur

Cooperation and Contagion in Web-Based, Networked Public Goods Experiments

A longstanding idea in the literature on human cooperation is that cooperation should be reinforced when conditional cooperators are more likely to interact. In the context of social networks, this idea implies that cooperation should fare better in highly clustered networks such as cliques than in networks with low clustering such as random networks. To test this hypothesis, we conducted a series of web-based experiments, in which 24 individuals played a local public goods game arranged on one of five network topologies that varied between disconnected cliques and a random regular graph. In contrast with previous theoretical work, we found that network topology had no significant effect on average contributions. This result implies either that individuals are not conditional cooperators, or else that cooperation does not benefit from positive reinforcement between connected neighbors. We then tested both of these possibilities in two subsequent series of experiments in which artificial seed players were introduced, making either full or zero contributions. First, we found that although players did generally behave like conditional cooperators, they were as likely to decrease their contributions in response to low contributing neighbors as they were to increase their contributions in response to high contributing neighbors. Second, we found that positive effects of cooperation were contagious only to direct neighbors in the network. In total we report on 113 human subjects experiments, highlighting the speed, flexibility, and cost-effectiveness of web-based experiments over those conducted in physical labs