scholarly journals Directionality and community-level selection

2018 ◽  
Author(s):  
Guy Bunin
Keyword(s):  
Community Dynamics ◽  
Evolutionary Dynamics ◽  
Spatial Dimension ◽  
Complex Interaction ◽  
Community Level ◽  
Interaction Networks ◽  
Ecological Community ◽  
Middle Ground ◽  
Stable States ◽  
Composition Changes

Many ecological community dynamics display some degree of directionality, known as succession patterns. But complex interaction networks frequently tend to non-directional dynamics such as chaos, unless additional structures or mechanisms impose some form of, often fragile or shot-lived, directionality. We exhibit here a novel property of emergent long-lasting directionality in competitive communities, which relies on very minimal assumptions. We model communities where each species has a few strong competitive interactions, and many weak ones. We find that, at high enough diversity, the dynamics become directional, meaning that the community state can be characterized by a function that increases in time, which we call "maturity". In the presence of noise, the community composition changes toward increasingly stable and productive states. This scenario occupies a middle ground between deterministic succession and purely random species associations: there are many overlapping stable states, with stochastic transitions, that are nevertheless biased in a particular direction. When a spatial dimension is added in the form of a meta-community, higher-maturity community states are able to expand in space, replacing others by (exact or approximate) copies of themselves. This leads to community-level selection, with the same maturity function acting as fitness. Classic concepts from evolutionary dynamics provide a powerful analogy to understand this strictly ecological, community-level phenomenon of emergent directionality.

scholarly journals Many-Objective Optimization for Anomaly Detection on Multi-Layer Complex Interaction Networks

2021 ◽  
Vol 11 (9) ◽  
pp. 4005
Author(s):  
Asep Maulana ◽  
Martin Atzmueller
Keyword(s):  
Anomaly Detection ◽  
Complex Networks ◽  
Pareto Front ◽  
Scoring Function ◽  
Cyber Physical Systems ◽  
Complex Interaction ◽  
Interaction Networks ◽  
Physical Systems ◽  
Human Interactions ◽  
Different Levels

Anomaly detection in complex networks is an important and challenging task in many application domains. Examples include analysis and sensemaking in human interactions, e.g., in (social) interaction networks, as well as the analysis of the behavior of complex technical and cyber-physical systems such as suspicious transactions/behavior in financial or routing networks; here, behavior and/or interactions typically also occur on different levels and layers. In this paper, we focus on detecting anomalies in such complex networks. In particular, we focus on multi-layer complex networks, where we consider the problem of finding sets of anomalous nodes for group anomaly detection. Our presented method is based on centrality-based many-objective optimization on multi-layer networks. Starting from the Pareto Front obtained via many-objective optimization, we rank anomaly candidates using the centrality information on all layers. This ranking is formalized via a scoring function, which estimates relative deviations of the node centralities, considering the density of the network and its respective layers. In a human-centered approach, anomalous sets of nodes can then be identified. A key feature of this approach is its interpretability and explainability, since we can directly assess anomalous nodes in the context of the network topology. We evaluate the proposed method using different datasets, including both synthetic as well as real-world network data. Our results demonstrate the efficacy of the presented approach.

scholarly journals The importance of species interactions in eco-evolutionary community dynamics under climate change

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Anna Åkesson ◽  
Alva Curtsdotter ◽  
Anna Eklöf ◽  
Bo Ebenman ◽  
Jon Norberg ◽  
...  
Keyword(s):  
Climate Change ◽  
Species Interactions ◽  
Community Dynamics ◽  
Evolutionary Dynamics ◽  
Negative Impact ◽  
Trophic Levels ◽  
Temperature Dependent ◽  
Modeling Framework ◽  
Impact Of Climate Change ◽  
The Impact

AbstractEco-evolutionary dynamics are essential in shaping the biological response of communities to ongoing climate change. Here we develop a spatially explicit eco-evolutionary framework which features more detailed species interactions, integrating evolution and dispersal. We include species interactions within and between trophic levels, and additionally, we incorporate the feature that species’ interspecific competition might change due to increasing temperatures and affect the impact of climate change on ecological communities. Our modeling framework captures previously reported ecological responses to climate change, and also reveals two key results. First, interactions between trophic levels as well as temperature-dependent competition within a trophic level mitigate the negative impact of climate change on biodiversity, emphasizing the importance of understanding biotic interactions in shaping climate change impact. Second, our trait-based perspective reveals a strong positive relationship between the within-community variation in preferred temperatures and the capacity to respond to climate change. Temperature-dependent competition consistently results both in higher trait variation and more responsive communities to altered climatic conditions. Our study demonstrates the importance of species interactions in an eco-evolutionary setting, further expanding our knowledge of the interplay between ecological and evolutionary processes.

Effects of Community Versus Single Strain Inoculants on the Biocontrol of Salmonella and Microbial Community Dynamics in Alfalfa Sprouts†

2005 ◽  
Vol 68 (1) ◽  
pp. 40-48 ◽  
Author(s):  
ANABELLE MATOS ◽  
JAY L. GARLAND
Keyword(s):  
Microbial Community ◽  
Microbial Communities ◽  
Community Dynamics ◽  
Community Level ◽  
Microbial Consortia ◽  
Single Strain ◽  
Acridine Orange Staining ◽  
Physiological Profiles ◽  
Alfalfa Sprouts ◽  
Alfalfa Seeds

Potential biological control inoculants, Pseudomonas fluorescens 2-79 and microbial communities derived from market sprouts or laboratory-grown alfalfa sprouts, were introduced into alfalfa seeds with and without a Salmonella inoculum. We examined their ability to inhibit the growth of this foodborne pathogen and assess the relative effects of the inoculants on the alfalfa microbial community structure and function. Alfalfa seeds contaminated with a Salmonella cocktail were soaked for 2 h in bacterial suspensions from each inoculant tested. Inoculated alfalfa seeds were grown for 7 days and sampled during days 1, 3, and 7. At each sampling, alfalfa sprouts were sonicated for 7 min to recover microflora from the surface, and the resulting suspensions were diluted and plated on selective and nonselective media. Total bacterial counts were obtained using acridine orange staining, and the percentage culturability was calculated. Phenotypic potential of sprout-associated microbial communities inoculated with biocontrol treatments was assessed using community-level physiological profiles based on patterns of use of 95 separate carbon sources in Biolog plates. Community-level physiological profiles were also determined using oxygen-sensitive fluorophore in BD microtiter plates to examine functional patterns in these communities. No significant differences in total and mesophilic aerobe microbial cell density or microbial richness resulting from the introduction of inoculants on alfalfa seeds with and without Salmonella were observed. P. fluorescens 2-79 exhibited the greatest reduction in the growth of Salmonella early during alfalfa growth (4.22 log at day 1), while the market sprout inoculum had the reverse effect, resulting in a maximum log reduction (5.48) of Salmonella on day 7. Community-level physiological profiles analyses revealed that market sprout communities peaked higher and faster compared with the other inoculants tested. These results suggest that different modes of actions of single versus microbial consortia biocontrol treatments may be involved.

Ribosomally synthesized peptides, foreground players in microbial interactions: recent developments and unanswered questions

2021 ◽  
Author(s):  
Sylvie Rebuffat
Keyword(s):  
Current Knowledge ◽  
Complex Interaction ◽  
Microbial Interactions ◽  
Interaction Networks ◽  
Recent Developments

This review unveils current knowledge on the complex interaction networks involving ribosomally synthesized peptides, either modified or not, being at play in microbial interactions and symbioses.

scholarly journals Evolution to alternative levels of stable diversity leaves areas of niche space unexplored

2021 ◽  
Author(s):  
Ilan N. Rubin ◽  
Iaroslav Ispolatov ◽  
Michael Doebeli
Keyword(s):  
Evolutionary Dynamics ◽  
Natural Populations ◽  
Metastable States ◽  
Community Diversity ◽  
Limited Resources ◽  
Niche Space ◽  
Stable States ◽  
Low Diversity ◽  
Population Sizes ◽  
Adaptive Radiations

AbstractOne of the oldest and most persistent questions in ecology and evolution is whether natural communities tend to evolve toward saturation and maximal diversity. Robert MacArthur’s classical theory of niche packing and the theory of adaptive radiations both imply that populations will diversify and fully partition any available niche space. However, the saturation of natural populations is still very much an open area of debate and investigation. Additionally, recent evolutionary theory suggests the existence of alternative evolutionary stable states (ESSs), which implies that some stable communities may not be fully saturated. Using models with classical Lokta-Volterra ecological dynamics and three formulations of evolutionary dynamics (a model using adaptive dynamics, an individual-based model, and a partial differential equation model), we show that following an adaptive radiation, communities can often get stuck in low diversity states when limited by mutations of small phenotypic effect. These low diversity metastable states can also be maintained by limited resources and finite population sizes. When small mutations and finite populations are considered together, it is clear that despite the presence of higher-diversity stable states, natural populations are likely not fully saturating their environment and leaving potential niche space unfilled. Additionally, within-species variation can further reduce community diversity from levels predicted by models that assume species-level homogeneity.Author summaryUnderstanding if and when communities evolve to saturate their local environments is imperative to our understanding of natural populations. Using computer simulations of classical evolutionary models, we study whether adaptive radiations tend to lead toward saturated communities in which no new species can invade or remain trapped in alternative, lower diversity stable states. We show that with asymmetric competition and small effect mutations, evolutionary Red Queen dynamics can trap communities in low diversity metastable states. Moreover, limited resources not only reduces community population sizes, but also reduces community diversity, denying the formation of saturated communities and stabilizing low diversity, non-stationary evolutionary dynamics. Our results are directly relevant to the longstanding questions important to both ecological empiricists and theoreticians on the species packing and saturation of natural environments. Also, by showing the ease evolution can trap communities in low diversity metastable stats, we demonstrate the potential harm in relying solely on ESSs to answer questions of biodiversity.

scholarly journals Graph theory and stability analysis of protein complex interaction networks

2016 ◽  
Vol 10 (2) ◽  
pp. 64-75 ◽  
Author(s):  
Chien-Hung Huang ◽  
Teng-Hung Chen ◽  
Ka-Lok Ng
Keyword(s):  
Graph Theory ◽  
Stability Analysis ◽  
Protein Complex ◽  
Complex Interaction ◽  
Interaction Networks

Effects of Targeted Grazing and Prescribed Burning on Community and Seed Dynamics of a Downy Brome (Bromus tectorum)–Dominated Landscape

2012 ◽  
Vol 5 (2) ◽  
pp. 259-269 ◽  
Author(s):  
Joel M. Diamond ◽  
Christopher A. Call ◽  
Nora Devoe
Keyword(s):  
Species Composition ◽  
Seed Bank ◽  
Community Dynamics ◽  
Prescribed Burning ◽  
Bromus Tectorum ◽  
Downy Brome ◽  
Stable States ◽  
Targeted Grazing ◽  
Northern Nevada ◽  
Seed Dynamics

AbstractDowny brome (Bromus tectorum L.)—dominated communities can remain as stable states for long periods, even with frequent disturbance by grazing and fire. The objective of this study was to determine the effectiveness of using targeted cattle grazing and late-season prescribed burning, alone and in combination, to reduce B. tectorum seed bank input and seed bank density and thus alter aboveground community dynamics (species composition) on a B. tectorum–dominated landscape in northern Nevada. Cattle removed 80 to 90% of standing biomass in grazed plots in May of 2005 and 2006 when B. tectorum was in the boot (phenological) stage. Grazed and ungrazed plots were burned in October 2005 and 2006. The combined grazing–burning treatment was more effective than either treatment alone in reducing B. tectorum seed input and seed bank density, and in shifting species composition from a community dominated by B. tectorum to one composed of a suite of species, with B. tectorum as a component rather than a dominant. This study provides a meso-scale precursor for landscape-scale adaptive management using grazing and burning methodologies.

scholarly journals LifeWebs: A (global) database of bipartite ecological interaction networks

2021 ◽  
Vol 5 ◽  
Author(s):  
Philip Butterill ◽  
Leonardo Jorge ◽  
Shuang Xing ◽  
Tom Fayle
Keyword(s):  
Interaction Network ◽  
Community Level ◽  
Interaction Networks ◽  
Sampling Effort ◽  
Ecological Communities ◽  
Bipartite Networks ◽  
Data Types ◽  
User Friendliness ◽  
Global Database ◽  
Machine Readable

The structure and dynamics of ecological interactions are nowadays recognized as a crucial challenge to comprehend the assembly, functioning and maintenance of ecological communities, their processes and the services they provide. Nevertheless, while standards and databases for information on species occurrences, traits and phylogenies have been established, interaction networks have lagged behind on the development of these standards. Here, we discuss the challenges and our experiences in developing a global database of bipartite interaction networks. LifeWebs*1 is an effort to compile community-level interaction networks from both published and unpublished sources. We focus on bipartite networks that comprise one specific type of interaction between two groups of species (e.g., plants and herbivores, hosts and parasites, mammals and their microbiota), which are usually presented in a co-occurrence matrix format. However, with LifeWebs, we attempt to go beyond simple matrices by integrating relevant metadata from the studies, especially sampling effort, explicit species information (traits and taxonomy/phylogeny), and environmental/geographic information on the communities. Specifically, we explore 1) the unique aspects of community-level interaction networks when compared to data on single inter-specific interactions, occurrence data, and other biodiversity data and how to integrate these different data types. 2) The trade-off between user friendliness in data input/output vs. machine-readable formats, especially important when data contributors need to provide large amounts of data usually compiled in a non-machine-readable format. 3) How to have a single framework that is general enough to include disparate interaction types while retaining all the meaningful information. We envision LifeWebs to be in a good position to test a general standard for interaction network data, with a large variety of already compiled networks that encompass different types of interactions. We provide a framework for integration with other types of data, and formalization of the data necessary to represent networks into established biodiversity standards.

scholarly journals Emergence of evolutionary stable communities through eco-evolutionary tunneling

2018 ◽  
Author(s):  
Seyfullah Enes Kotil ◽  
Kalin Vetsigian
Keyword(s):  
Evolutionary Dynamics ◽  
Adaptive Dynamics ◽  
Evolutionary Game ◽  
Evolutionary Process ◽  
Short Time Scale ◽  
Stable States ◽  
Ecological Dynamics ◽  
Adaptive Diversification ◽  
Branching Points ◽  
Short Time

AbstractEcological and evolutionary dynamics of communities are inexorably intertwined. The ecological state determines the fate of newly arising mutants, and mutations that increase in frequency can reshape the ecological dynamics. Evolutionary game theory and its extensions within adaptive dynamics (AD) have been the mathematical frameworks for understanding this interplay, leading to notions such as Evolutionary Stable States (ESS) in which no mutations are favored, and evolutionary branching points near which the population diversifies. A central assumption behind these theoretical treatments has been that mutations are rare so that the ecological dynamics has time to equilibrate after every mutation. A fundamental question is whether qualitatively new phenomena can arise when mutations are frequent. Here we describe an adaptive diversification process that robustly leads to complex ESS, despite the fact that such communities are unreachable through a step-by-step evolutionary process. Rather, the system as a whole tunnels between collective states over a short time scale. The tunneling rate is a sharply increasing function of the rate with which mutations arise in the population. This makes the emergence of ESS communities virtually impossible in small populations, but generic in large ones. Moreover, communities emerging through this process can spatially spread as single replication units that outcompete other communities. Overall, this work provides a qualitatively new mechanism for adaptive diversification and shows that complex structures can generically evolve even when no step-by-step evolutionary path exists.

Sign in / Sign up

Export Citation Format

Share Document