arXiv subjects

Silvia De Monte

Publications and source records attributed to Silvia De Monte.

8 recordsLinked to original sources

arXiv2025

Fluctuating growth rates link turnover and unevenness in species-rich communities

The maintenance of diversity, the `commonness of rarity', and compositional turnover are ubiquitous features of species-rich communities. Through a minimal model, we consider how these features reflect the interplay between environmental stochasticity, intra- and interspecific competition, and dispersal. We show that, even if species have the same time-average fitness, fluctuations tend to drive the community towards ever-growing unevenness and species extinctions, but self-limitation and/or dispersal allow species-rich states to be sustained. Species abundance--distributions vary systematically in a Buffering--Stabilization parameter plane that describes the relative strength of the underlying ecological processes, and cover different empirically relevant power-law and unimodal shapes. A model describing the effective dynamics of a focal species relates static abundance distributions with turnover dynamics, also when species have different mean fitness. The model suggests how community statistics and time series of individual species can inform on the relative importance of the ecological processes that structure diversity.

q-bio.PE↗

arXiv2024

Chaotic turnover of rare and abundant species in a strongly interacting model community

The composition of ecological communities varies not only between different locations but also in time. Understanding the fundamental processes that drive species towards rarity or abundance is crucial to assessing ecosystem resilience and adaptation to changing environmental conditions. In plankton communities in particular, large temporal fluctuations in species abundances have been associated with chaotic dynamics. On the other hand, microbial diversity is overwhelmingly sustained by a `rare biosphere' of species with very low abundances. We consider here the possibility that interactions within a species-rich community can relate both phenomena. We use a Lotka-Volterra model with weak immigration and strong, disordered, and mostly competitive interactions between hundreds of species to bridge single-species temporal fluctuations and abundance distribution patterns. We highlight a generic chaotic regime where a few species at a time achieve dominance, but are continuously overturned by the invasion of formerly rare species. We derive a focal-species model that captures the intermittent boom-and-bust dynamics that every species undergoes. Although species cannot be treated as effectively uncorrelated in their abundances, the community's effect on a focal species can nonetheless be described by a time-correlated noise characterized by a few effective parameters that can be estimated from time series. The model predicts a non-unitary exponent of the power-law abundance decay, which varies weakly with ecological parameters, consistent with observation in marine protist communities. The chaotic turnover regime is thus poised to capture relevant ecological features of species-rich microbial communities.

q-bio.PE↗

arXiv2023

Artificial selection of communities drives the emergence of structured interactions

Species-rich communities, such as the microbiota or microbial ecosystems, provide key functions for human health and climatic resilience. Increasing effort is being dedicated to design experimental protocols for selecting community-level functions of interest. These experiments typically involve selection acting on populations of communities, each of which is composed of multiple species. If numerical simulations started to explore the evolutionary dynamics of this complex, multi-scale system, a comprehensive theoretical understanding of the process of artificial selection of communities is still lacking. Here, we propose a general model for the evolutionary dynamics of communities composed of a large number of interacting species, described by disordered generalised Lotka-Volterra equations. Our analytical and numerical results reveal that selection for scalar community functions leads to the emergence, along an evolutionary trajectory, of a low-dimensional structure in an initially featureless interaction matrix. Such structure reflects the combination of the properties of the ancestral community and of the selective pressure. Our analysis determines how the speed of adaptation scales with the system parameters and the abundance distribution of the evolved communities. Artificial selection for larger total abundance is thus shown to drive increased levels of mutualism and interaction diversity. Inference of the interaction matrix is proposed as a method to assess the emergence of structured interactions from experimentally accessible measures.

q-bio.PE↗

arXiv2009

French Roadmap for complex Systems 2008-2009

This second issue of the French Complex Systems Roadmap is the outcome of the Entretiens de Cargese 2008, an interdisciplinary brainstorming session organized over one week in 2008, jointly by RNSC, ISC-PIF and IXXI. It capitalizes on the first roadmap and gathers contributions of more than 70 scientists from major French institutions. The aim of this roadmap is to foster the coordination of the complex systems community on focused topics and questions, as well as to present contributions and challenges in the complex systems sciences and complexity science to the public, political and industrial spheres.

nlin.AO↗

arXiv2004

Noise-induced macroscopic bifurcations in globally-coupled chaotic units

Large populations of globally-coupled identical maps subjected to independent additive noise are shown to undergo qualitative changes as the features of the stochastic process are varied. We show that for strong coupling, the collective dynamics can be described in terms of a few effective macroscopic degrees of freedom, whose deterministic equations of motion are systematically derived through an order parameter expansion.

cond-mat.stat-mech↗

arXiv2003

Coherent regimes of globally coupled dynamical systems

The paper presents a method by which the mean field dynamics of a population of dynamical systems with parameter diversity and global coupling can be described in terms of a few macroscopic degrees of freedom. The method applies to populations of any size and functional form in the region of coherence. It requires linear variation or a narrow distribution for the dispersed parameter. Although being an approximation, the method allows us to quantitatively study the collective regimes that arise as a result of diversity and coupling and to interpret the transitions among these regimes as bifurcations of the effective macroscopic degrees of freedom. To illustrate, the phenomenon of oscillator death and the route to full locking are examined for chaotic oscillators with time scale mismatch.

cond-mat.stat-mech↗

arXiv2003

Noise-induced macroscopic bifurcations in populations of globally coupled maps

Populations of globally coupled identical maps subject to additive, independent noise are studied in the regimes of strong coupling. Contrary to each noisy population element, the mean field dynamics undergoes qualitative changes when the noise strength is varied. In the limit of infinite population size, these macroscopic bifurcations can be accounted for by a deterministic system, where the mean-field, having the same dynamics of each uncoupled element, is coupled with other order parameters. Different approximation schemes are proposed for polynomial and exponential functions and their validity discussed for logistic and excitable maps.

cond-mat.stat-mech↗

arXiv2001

Dynamics of order parameters for a population of globally coupled oscillators

Using an expansion in order parameters, the equation of motion for the centroid of globally coupled oscillators with natural frequencies taken from a distribution is obtained for the case of high coupling, low dispersion of natural frequencies and any number of oscillators. To the first order, the system can be approximated by a set of four equations, where the centroid is coupled with a second macroscopic variable, which describes the dynamics of the oscillators around their average. This gives rise to collective effects that suggest experiments aimed at measuring the parameters of the population.

cond-mat.stat-mech↗