Tag: ecological networks

Stochastic Models and Experiments in Ecology and Biology 2020 Conference – Venice 21-24th September

SMEEB 2020 conference will be held in Venice, September 21-24, 2020, at the European Center of Living Technology (ECLT). 

 
 The aim of the workshop is to bring together scientists with different backgrounds (mathematics, biology, physics and computing) interested in microbial ecology and evolutionary biology (both theory and experiments). We will discuss important and recent research topics in these areas as well as methods and ideas. 
 
Topics will include stochastic population dynamics, quantitative and systemic biology, community ecology of microbes, statistical mechanics models in ecology, evolution in microbial communities, biodiversity coexistence and species interactions. The style of the workshop will purposely be informal to encourage discussions. 
 
Invited Speakers(*tbc): Otto X. Cordero, Eric Dykeman, Daniel Fisher, Nigel Goldenfeld*, Susan Holmes*, Terry Hwa, Eleni Katifori, David Nelson, Derek Tittensor, Amandine Veber. 
 
 The call of abstracts for contributed talks will close on May 24, 2020 (EasyChair submission link: https://easychair.org/conferences/?conf=smeeb2020 ). 
 

 Please bring this announcement to the attention of anyone who may be interested, especially students and post-docs who are not in this mailing list. There are 2 registration fee waivers for Ph.Ds / young Post-docs. Look in the website for all info. The attendance fee of the workshop will be 200 Euro, which includes coffee breaks and workshop material. However, owing to the current Covid-19 epidemic, the payment is not open at the moment. Once the workshop will eventually be confirmed, we will open the payment link and contact those who have pre-registered or submitted an abstract for the final registration.

Reconciling cooperation, biodiversity and stability in complex ecological communities

Empirical evidences show that ecosystems with high biodiversity can persist in time even in the presence of few types of resources and are more stable than low biodiverse communities. This evidence is contrasted by the conventional mathematical modeling, which predicts that the presence of many species and/or cooperative interactions are detrimental for ecological stability and persistence. Here we propose a modelling framework for population dynamics, which also include indirect cooperative interactions mediated by other species (e.g. habitat modification). We show that in the large system size limit, any number of species can coexist and stability increases as the number of species grows, if mediated cooperation is present, even in presence of exploitative or harmful interactions (e.g. antibiotics). Our theoretical approach thus shows that appropriate models of mediated cooperation naturally lead to a solution of the long-standing question about complexity-stability paradox and on how highly biodiverse communities can coexist.

Source: www.nature.com

Effects of network modularity on the spread of perturbation impact in experimental metapopulations

The networks that form natural, social, and technological systems are vulnerable to the spreading impacts of perturbations. Theory predicts that networks with a clustered or modular structure—where nodes within a module interact more frequently than they do with nodes in other modules—might contain a perturbation, preventing it from spreading to the entire network. Gilarranz et al. conducted experiments with networked populations of springtail ( Folsomia candida ) microarthropods to show that modularity limits the impact of a local extinction on neighboring nodes (see the Perspective by Sales-Pardo). In networks with high modularity, the perturbation was contained within the targeted module, and its impact did not spread to nodes beyond it. However, simulations revealed that modularity is beneficial to the network only when perturbations are present; otherwise, it hinders population growth.

Science , this issue p. [199][1]; see also p. [128][2]

[1]: /lookup/doi/10.1126/science.aal4122
[2]: /lookup/doi/10.1126/science.aan8075

Source: science.sciencemag.org

Looplessness in networks is linked to trophic coherence

Complex systems such as cells, brains, or ecosystems are made up of many interconnected elements, each one acting on its neighbors, and sometimes influencing its own state via feedback loops. Certain biological networks have surprisingly few such loops. Although this may be advantageous in various ways, it is not known how feedback is suppressed. We show that trophic coherence, a structural property of ecosystems, is key to the extent of feedback in these as well as in many other systems, including networks related to genes, neurons, metabolites, words, computers, and trading nations. We derive mathematical expressions that provide a benchmark against which to examine empirical data, and conclude that “looplessness” in nature is probably a consequence of trophic coherenc

Source: www.pnas.org

Feasibility and coexistence of large ecological communities

The role of species interactions in controlling the interplay between the stability of ecosystems and their biodiversity is still not well understood. The ability of ecological communities to recover after small perturbations of the species abundances (local asymptotic stability) has been well studied, whereas the likelihood of a community to persist when the conditions change (structural stability) has received much less attention. Our goal is to understand the effects of diversity, interaction strengths and ecological network structure on the volume of parameter space leading to feasible equilibria. We develop a geometrical framework to study the range of conditions necessary for feasible coexistence. We show that feasibility is determined by few quantities describing the interactions, yielding a nontrivial complexity–feasibility relationship. Analysing more than 100 empirical networks, we show that the range of coexistence conditions in mutualistic systems can be analytically predicted. Finally, we characterize the geometric shape of the feasibility domain, thereby identifying the direction of perturbations that are more likely to cause extinctions.

Source: www.nature.com