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Biology subjects

Froese, T.

Publications and source records attributed to Froese, T..

3 recordsLinked to original sources

Football as foraging? Movements by individual players and whole teams exhibit Levy walk dynamics

Many organisms, ranging from modern humans to extinct species, exhibit movement patterns that can be described by Levy walk dynamics. It has been demonstrated that such behavior enables optimal foraging when resource distribution is sparse. Here, we analyze a dataset of football player trajectories, recorded during the matches of the Japanese football league to elucidate the presence of statistical signatures of Levy walks; such as the heavy-tailed distribution of distances traveled between significant turns and the characteristic superdiffusive behavior. We conjecture that the competitive environment of a football game leads to movement dynamics reminiscent of that observed in hunter-gathering populations and more broadly in any biological organisms foraging for resources, whose exact distribution is unknown to them. Apart from analyzing individual players movements, we investigate the dynamics of the whole team by studying the movements of its center of mass (teams centroid). Remarkably, the trajectory of the centroid also exhibits Levy walk properties, marking the first instance of such type of motion observed at the group level. Our work concludes with a comparative analysis of different teams and some discussion on the relevance of our findings to sports science and science more generally.

systems biology↗

From autopoiesis to self-optimization: Toward an enactive model of biological regulation

The theory of autopoiesis has been influential in many areas of theoretical biology, especially in the fields of artificial life and origins of life. However, it has not managed to productively connect with mainstream biology, partly for theoretical reasons, but arguably mainly because deriving specific working hypotheses has been challenging. The theory has recently undergone significant conceptual development in the enactive approach to life and mind. Hidden complexity in the original conception of autopoiesis has been explicated in the service of other operationalizable concepts related to self-individuation: precariousness, adaptivity, and agency. Here we advance these developments by highlighting the interplay of these concepts with considerations from thermodynamics: reversibility, irreversibility, and path-dependence. We interpret this interplay in terms of the self-optimization model, and present modeling results that illustrate how these minimal conditions enable a system to re-organize itself such that it tends toward coordinated constraint satisfaction at the system level. Although the model is still very abstract, these results point in a direction where the enactive approach could productively connect with cell biology.

systems biology↗

The thermodynamics of reproduction constrain species ranking dynamics and diversity

Iniguez, Pineda, Gershenson, and Barabasi proposed that complex systems can be simplified and analyzed in terms of the dynamics of ordered lists. For social, economic, and infrastructural systems, they succeeded in modeling the dynamics of ranking with two mechanisms, namely displacement (i.e., shuffling of ranks among existing elements) and replacement of elements by new elements. A general pattern is that, for open systems with influx and outflux of elements, e.g., a list with a subset of elements, only the top of the list is stable; for closed systems, top and bottom are stable. This model was fitted to empirical data, resulting in a universal curve in which displacement and replacement parameters are inversely related, which implies that a single parameter could regulate both. Our aim is twofold: First, we demonstrate that the pattern generalizes to ranking of biological species, based on FishBase records of fish taxonomy and life history traits. Second, we propose a candidate for a unified mechanism, based on a recent model of the thermodynamics of self-replication.

evolutionary biology↗