Adaptive dynamics; an asymptotic point of view

2010 ◽  
Vol 278 (1704) ◽  
pp. 449-457 ◽  
Author(s):  
S. Boudsocq ◽  
S. Barot ◽  
N. Loeuille

Although plant strategies for acquiring nutrients have been widely studied from a functional point of view, their evolution is still not well understood. In this study, we investigate the evolutionary dynamics of these strategies and determine how they influence ecosystem properties. To do so, we use a simple nutrient-limited ecosystem model in which plant ability to take up nutrients is subject to adaptive dynamics. We postulate the existence of a trade-off between this ability and mortality. We show that contrasting strategies are possible as evolutionary outcomes, depending on the shape of the trade-off and, when nitrogen is considered as the limiting nutrient, on the intensity of symbiotic fixation. Our model enables us to bridge these evolutionary outcomes to classical ecological theories such as Hardin's tragedy of the commons and Tilman's rule of R *. Evolution does not systematically maximize plant biomass or primary productivity. On the other hand, each evolutionary outcome leads to a decrease in the availability of the limiting mineral nutrient, supporting the work of Tilman on competition between plants for a single resource. Our model shows that evolution can be used to link different classical ecological results and that adaptation may influence ecosystem properties in contrasted ways.


1984 ◽  
Vol 16 (03) ◽  
pp. 585-602
Author(s):  
Shigeru Mase

We consider the statistical estimation problem of potential functions of Gibbs models on the plane lattice. We assume that the area on which a random point pattern is observed is sufficiently large and take an asymptotic point of view. The main result is to show the locally asymptotic normality of the Gibbs model under certain conditions. From this result we can show the optimality of the maximum likelihood estimator employing known results about locally asymptotic normal families, though a practical computation of the maximum likelihood estimator presents difficulties. An estimation procedure based on the method of moments is also proposed.


2019 ◽  
Vol 33 (1) ◽  
pp. 83-106
Author(s):  
Manuel Baumgartner ◽  
Peter Spichtinger

2016 ◽  
Vol 23 (02) ◽  
pp. 1650011 ◽  
Author(s):  
Luigi Accardi ◽  
Andrei Khrennikov ◽  
Masanori Ohya ◽  
Yoshiharu Tanaka ◽  
Ichiro Yamato

Recently a novel quantum information formalism — quantum adaptive dynamics — was developed and applied to modelling of information processing by bio-systems including cognitive phenomena: from molecular biology (glucose-lactose metabolism for E.coli bacteria, epigenetic evolution) to cognition, psychology. From the foundational point of view quantum adaptive dynamics describes mutual adapting of the information states of two interacting systems (physical or biological) as well as adapting of co-observations performed by the systems. In this paper we apply this formalism to model unconscious inference: the process of transition from sensation to perception. The paper combines theory and experiment. Statistical data collected in an experimental study on recognition of a particular ambiguous figure, the Schröder stairs, support the viability of the quantum(-like) model of unconscious inference including modelling of biases generated by rotation-contexts. From the probabilistic point of view, we study (for concrete experimental data) the problem of contextuality of probability, its dependence on experimental contexts. Mathematically contextuality leads to non-Komogorovness: probability distributions generated by various rotation contexts cannot be treated in the Kolmogorovian framework. At the same time they can be embedded in a “big Kolmogorov space” as conditional probabilities. However, such a Kolmogorov space has too complex structure and the operational quantum formalism in the form of quantum adaptive dynamics simplifies the modelling essentially.


Mathematics ◽  
2019 ◽  
Vol 7 (10) ◽  
pp. 924 ◽  
Author(s):  
Alberto Lastra ◽  
Stéphane Malek

The analytic solutions of a family of singularly perturbed q-difference-differential equations in the complex domain are constructed and studied from an asymptotic point of view with respect to the perturbation parameter. Two types of holomorphic solutions, the so-called inner and outer solutions, are considered. Each of them holds a particular asymptotic relation with the formal ones in terms of asymptotic expansions in the perturbation parameter. The growth rate in the asymptotics leans on the - 1 -branch of Lambert W function, which turns out to be crucial.


1984 ◽  
Vol 16 (3) ◽  
pp. 585-602 ◽  
Author(s):  
Shigeru Mase

We consider the statistical estimation problem of potential functions of Gibbs models on the plane lattice. We assume that the area on which a random point pattern is observed is sufficiently large and take an asymptotic point of view. The main result is to show the locally asymptotic normality of the Gibbs model under certain conditions. From this result we can show the optimality of the maximum likelihood estimator employing known results about locally asymptotic normal families, though a practical computation of the maximum likelihood estimator presents difficulties. An estimation procedure based on the method of moments is also proposed.


2014 ◽  
Vol 47 (3) ◽  
pp. 4376-4381 ◽  
Author(s):  
Ghjuvan Micaelu Grimaud ◽  
Francis Mairet ◽  
Olivier Bernard

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