Month: November 2017

The architecture of mutualistic networks as an evolutionary spandrel

Mutualistic networks have been shown to involve complex patterns of interactions among animal and plant species, including a widespread presence of nestedness. The nested structure of these webs seems to be positively correlated with higher diversity and resilience. Moreover, these webs exhibit marked measurable structural patterns, including broad distributions of connectivity, strongly asymmetrical interactions and hierarchical organization. Hierarchical organization is an especially interesting property, since it is positively correlated with biodiversity and network resilience, thus suggesting potential selection processes favouring the observed web organization. However, here we show that all these structural quantitative patterns—and nestedness in particular—can be properly explained by means of a very simple dynamical model of speciation and divergence with no selection-driven coevolution of traits. The agreement between observed and modelled networks suggests that the patterns displayed by real mutualistic webs might actually represent evolutionary spandrels.

 

The architecture of mutualistic networks as an evolutionary spandrel
Sergi Valverde, Jordi Piñero, Bernat Corominas-Murtra, Jose Montoya, Lucas Joppa & Ricard Solé
Nature Ecology & Evolution (2017)
doi:10.1038/s41559-017-0383-4

Source: www.nature.com

Social Complex Contagion in Music Listenership: A Natural Experiment with 1.3 Million Participants

Can live music events generate complex contagion in music streaming? This paper finds evidence in the affirmative, but only for the most popular artists. We generate a novel dataset from Last.fm, a music tracking website, to analyse the listenership history of 1.3 million users over a two-month time horizon. We use daily play counts along with event attendance data to run a regression discontinuity analysis in order to show the causal impact of concert attendance on music listenership among attendees and their friends network. First, we show that attending a music artist’s live concert increases that artist’s listenership among the attendees of the concert by approximately 1 song per day per attendee (p-value<0.001). Moreover, we show that this effect is contagious and can spread to users who did not attend the event. However, the extent of contagion depends on the type of artist. We only observe contagious increases in listenership for well-established, popular artists (.06 more daily plays per friend of an attendee [p<0.001]), while the effect is absent for emerging stars. We also show that the contagion effect size increases monotonically with the number of friends who have attended the live event.

 

Social Complex Contagion in Music Listenership: A Natural Experiment with 1.3 Million Participants
John Ternovski, Taha Yasseri

Source: arxiv.org

Social network and temporal discounting

For reasons of social influence and social logistics, people in closed networks are expected to experience time compression: The more closed a person’s network, the steeper the person’s discount function, and the more narrow the expected time horizon within which the person deliberates events and behavior. Consistent with the hypothesis, data on managers at the top of three organizations show network closure associated with a social life compressed into daily contact with colleagues. Further, language in closed networks is predominantly about current activities, ignoring the future. Further still, discount functions employed by executive MBA students show more severe discounting by students in more closed networks. Inattention to the future can be argued to impair achievement, however, I find no evidence across the managers of daily contact diminishing the achievement associated with network advantage. I close with comments on replication and extrapolation to language more generally, within-person variation, and select cognitive patterns (closure bias, end of history, and felt status loss).

 

 

Social network and temporal discounting

RONALD S. BURT
Network Science, Volume 5 / Issue 4, November 2017, pp 411 – 440
doi: 10.1017/nws.2017.23

Source: www.cambridge.org

Algorithmic Cognition and the Computational Nature of the Mind

The idea that complexity or, its reverse, simplicity are essential concepts for cognitive psychology was already understood in the middle of the twentieth century (Mach 1914), and these concepts have remained salient ever since (Oizumi et al. 2014). As early as the 1990s, the algorithmic theory of information was referenced by some researchers in psychology, who recommended the use of algorithmic complexity as a universal normative measure of complexity. Nevertheless, the noncomputability of algorithmic complexity was deemed an insurmountable obstacle, and more often than not it merely served as a point of reference.
In recent years, we have been able to create and use more reliable estimates of algorithmic complexity using the coding theorem method (Gauvrit et al. 2014b, 2016). This has made it possible to deploy a precise and quantitative approximation of algorithmic complexity, with applications in many areas of psychology and the behavioral sciences – sometimes …

 

Algorithmic Cognition and the Computational Nature of the Mind

Hector Zenil , Nicolas Gauvrit

Living Reference Work Entry
Encyclopedia of Complexity and Systems Science
pp 1-9

Source: link.springer.com

Modelling the effects of phylogeny and body size on within-host pathogen replication and immune response

Understanding how quickly pathogens replicate and how quickly the immune system responds is important for predicting the epidemic spread of emerging pathogens. Host body size, through its correlation with metabolic rates, is theoretically predicted to impact pathogen replication rates and immune system response rates. Here, we use mathematical models of viral time courses from multiple species of birds infected by a generalist pathogen (West Nile Virus; WNV) to test more thoroughly how disease progression and immune response depend on mass and host phylogeny. We use hierarchical Bayesian models coupled with nonlinear dynamical models of disease dynamics to incorporate the hierarchical nature of host phylogeny. Our analysis suggests an important role for both host phylogeny and species mass in determining factors important for viral spread such as the basic reproductive number, WNV production rate, peak viraemia in blood and competency of a host to infect mosquitoes. Our model is based on a principled analysis and gives a quantitative prediction for key epidemiological determinants and how they vary with species mass and phylogeny. This leads to new hypotheses about the mechanisms that cause certain taxonomic groups to have higher viraemia. For example, our models suggest that higher viral burst sizes cause corvids to have higher levels of viraemia and that the cellular rate of virus production is lower in larger species. We derive a metric of competency of a host to infect disease vectors and thereby sustain the disease between hosts. This suggests that smaller passerine species are highly competent at spreading the disease compared with larger non-passerine species. Our models lend mechanistic insight into why some species (smaller passerine species) are pathogen reservoirs and some (larger non-passerine species) are potentially dead-end hosts for WNV. Our techniques give insights into the role of body mass and host phylogeny in the spread of WNV and potentially other zoonotic diseases. The major contribution of this work is a computational framework for infectious disease modelling at the within-host level that leverages data from multiple species. This is likely to be of interest to modellers of infectious diseases that jump species barriers and infect multiple species. Our method can be used to computationally determine the competency of a host to infect mosquitoes that will sustain WNV and other zoonotic diseases. We find that smaller passerine species are more competent in spreading the disease than larger non-passerine species. This suggests the role of host phylogeny as an important determinant of within-host pathogen replication. Ultimately, we view our work as an important step in linking within-host viral dynamics models to between-host models that determine spread of infectious disease between different hosts.

 

Modelling the effects of phylogeny and body size on within-host pathogen replication and immune response
Soumya Banerjee, Alan S. Perelson, Melanie Moses
Published 15 November 2017.DOI: 10.1098/rsif.2017.0479

Source: rsif.royalsocietypublishing.org