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Yeakel J.D.,Simon Fraser University | Moore J.W.,Simon Fraser University | Guimaraes P.R.,University of Sao Paulo | de Aguiar M.A.M.,University of Campinas | de Aguiar M.A.M.,New England Complex Systems Institute
Ecology Letters | Year: 2014

Spatial structure in landscapes impacts population stability. Two linked components of stability have large consequences for persistence: first, statistical stability as the lack of temporal fluctuations; second, synchronisation as an aspect of dynamic stability, which erodes metapopulation rescue effects. Here, we determine the influence of river network structure on the stability of riverine metapopulations. We introduce an approach that converts river networks to metapopulation networks, and analytically show how fluctuation magnitude is influenced by interaction structure. We show that river metapopulation complexity (in terms of branching prevalence) has nonlinear dampening effects on population fluctuations, and can also buffer against synchronisation. We conclude by showing that river transects generally increase synchronisation, while the spatial scale of interaction has nonlinear effects on synchronised dynamics. Our results indicate that this dual stability - conferred by fluctuation and synchronisation dampening - emerges from interaction structure in rivers, and this may strongly influence the persistence of river metapopulations. © 2013 John Wiley & Sons Ltd/CNRS.

Vilar L.,University of Lisbon | Araujo D.,University of Lisbon | Davids K.,University of Queensland | Bar-Yam Y.,New England Complex Systems Institute
Journal of Systems Science and Complexity | Year: 2013

Quantitative analysis is increasingly being used in team sports to better understand performance in these stylized, delineated, complex social systems. Here, the authors provide a first step toward understanding the pattern-forming dynamics that emerge from collective offensive and defensive behavior in team sports. The authors propose a novel method of analysis that captures how teams occupy sub-areas of the field as the ball changes location. The authors use this method to analyze a game of association football (soccer) based upon a hypothesis that local player numerical dominance is key to defensive stability and offensive opportunity. The authors find that the teams consistently allocated more players than their opponents in sub-areas of play closer to their own goal. This is consistent with a predominantly defensive strategy intended to prevent yielding even a single goal. The authors also find differences between the two teams' strategies: while both adopted the same distribution of defensive, midfield, and attacking players (a 4: 3: 3 system of play), one team was significantly more effective in maintaining both defensive and offensive numerical dominance for defensive stability and offensive opportunity. That team indeed won the match with an advantage of one goal (2 to 1) but the analysis shows the advantage in play was more pervasive than the single goal victory would indicate. The proposed focus on the local dynamics of team collective behavior is distinct from the traditional focus on individual player capability. It supports a broader view in which specific player abilities contribute within the context of the dynamics of multiplayer team coordination and coaching strategy. By applying this complex system analysis to association football, the authors can understand how players' and teams' strategies result in successful and unsuccessful relationships between teammates and opponents in the area of play. © 2013 Institute of Systems Science, Academy of Mathematics and Systems Science, CAS and Springer-Verlag Berlin Heidelberg.

Widener M.J.,University of Cincinnati | Metcalf S.S.,State University of New York at Buffalo | Bar-Yam Y.,New England Complex Systems Institute
Applied Geography | Year: 2013

Despite advances in medical technology and public health practices over the past few decades, there has been a steady increase in the prevalence of chronic diseases like type 2 diabetes among low-income urban residents in the US. For this population, maintaining a diet consisting of nutritious foods is complicated by a number of physical and social barriers. In cities, a coalescence of social, spatial, and economic factors influence the availability of healthy food in any given place. The urban food environment contextualizes the structural and individual-level norms that drive daily decision-making about what to eat. Understanding and acting on the processes that reduce these residents' access to healthy foods will make for a healthier urban landscape. This paper advances the discussion of food deserts by using an agent-based model to simulate the impact of various policy interventions on low-income households' consumption of fresh fruits and vegetables. Using a simulated population of low-income households in Buffalo, NY, initialized with demographic and geographic data from the US Census and the City of Buffalo, a baseline scenario is established. Four different scenarios are explored in contrast to the baseline, including increasing the frequency that households shop for groceries, increasing the probability convenience stores stock fresh produce, and implementing a mobile market distribution system. The paper concludes by analyzing the effectiveness of the varying strategies, and discussing policy implications. © 2013 Elsevier Ltd.

Herdagdelen A.,University of Trento | Herdagdelen A.,New England Complex Systems Institute | Baroni M.,University of Trento
Journal of the American Society for Information Science and Technology | Year: 2011

We extracted gender-specific actions from text corpora and Twitter, and compared them with stereotypical expectations of people. We used Open Mind Common Sense (OMCS), a common sense knowledge repository, to focus on actions that are pertinent to common sense and daily life of humans. We use the gender information of Twitter users and web-corpus-based pronoun/name gender heuristics to compute the gender bias of the actions. With high recall, we obtained a Spearman correlation of 0.47 between corpus-based predictions and a human gold standard, and an area under the ROC curve of 0.76 when predicting the polarity of the gold standard. We conclude that it is feasible to use natural text (and a Twitter-derived corpus in particular) in order to augment common sense repositories with the stereotypical gender expectations of actions. We also present a dataset of 441 common sense actions with human judges' ratings on whether the action is typically/slightly masculine/feminine (or neutral), and another larger dataset of 21,442 actions automatically rated by the methods we investigate in this study. © 2011 ASIS&T.

Hill S.A.,University of Toledo | Braha D.,New England Complex Systems Institute | Braha D.,University of Massachusetts Dartmouth
Physical Review E - Statistical, Nonlinear, and Soft Matter Physics | Year: 2010

The characterization of the "most connected" nodes in static or slowly evolving complex networks has helped in understanding and predicting the behavior of social, biological, and technological networked systems, including their robustness against failures, vulnerability to deliberate attacks, and diffusion properties. However, recent empirical research of large dynamic networks (characterized by irregular connections that evolve rapidly) has demonstrated that there is little continuity in degree centrality of nodes over time, even when their degree distributions follow a power law. This unexpected dynamic centrality suggests that the connections in these systems are not driven by preferential attachment or other known mechanisms. We present an approach to explain real-world dynamic networks and qualitatively reproduce these dynamic centrality phenomena. This approach is based on a dynamic preferential attachment mechanism, which exhibits a sharp transition from a base pure random walk scheme. © 2010 The American Physical Society.

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