scholarly journals Trophic network structure emerges through antagonistic coevolution in temporally varying environments

2011 ◽  
Vol 279 (1727) ◽  
pp. 299-308 ◽  
Author(s):  
Timothée Poisot ◽  
Peter H. Thrall ◽  
Michael E. Hochberg
Keyword(s):  
Network Structure ◽  
Environmental Variability ◽  
Empirical Studies ◽  
Single Species ◽  
Theoretical Work ◽  
Bipartite Network ◽  
Ecological Specialization ◽  
Natural Systems ◽  
Trophic Network ◽  
Varying Environments

Understanding the mechanisms underlying ecological specialization is central to our understanding of community ecology and evolution. Although theoretical work has investigated how variable environments may affect specialization in single species, little is known about how such variation impacts bipartite network structure in antagonistically coevolving systems. Here, we develop and analyse a general model of victim–enemy coevolution that explicitly includes resource and population dynamics. We investigate how temporal environmental heterogeneity affects the evolution of specialization and associated community structure. Environmental productivity influences victim investment in resistance, which will shape patterns of specialization through its regulating effect on enemy investment in infectivity. We also investigate the epidemiological consequences of environmental variability and show that enemy population density is maximized for intermediate lengths of productive seasons, which corresponds to situations where enemies can evolve higher infectivity than victims can evolve defence. We discuss our results in the light of empirical studies, and further highlight ways in which our model applies to a range of natural systems.

A performative network theory of attitudes

2020 ◽  
Author(s):  
Michael Quayle
Keyword(s):  
Attitude Change ◽  
Network Structure ◽  
Network Theory ◽  
Social Group ◽  
Group Structure ◽  
Social Identities ◽  
Bipartite Network ◽  
Identity Change ◽  
Multilayer Network ◽  
Dynamic Phenomena

In this paper I propose a network theory of attitudes where attitude agreements and disagreements forge a multilayer network structure that simultaneously binds people into groups (via attitudes) and attitudes into clusters (via people who share them). This theory proposes that people have a range of possible attitudes (like cards in a hand) but these only become meaningful when expressed (like a card played). Attitudes are expressed with sensitivity to their potential audiences and are socially performative: when we express attitudes, or respond to those expressed by others, we tell people who we are, what groups we might belong to and what to think of us. Agreement and disagreement can be modelled as a bipartite network that provides a psychological basis for perceived ingroup similarity and outgroup difference and, more abstractly, group identity. Opinion-based groups and group-related opinions are therefore co-emergent dynamic phenomena. Dynamic fixing occurs when particular attitudes become associated with specific social identities. The theory provides a framework for understanding identity ecosystems in which social group structure and attitudes are co-constituted. The theory describes how attitude change is also identity change. This has broad relevance across disciplines and applications concerned with social influence and attitude change.

scholarly journals Habitat choice meets thermal specialization: Competition with specialists may drive suboptimal habitat preferences in generalists

2018 ◽  
Vol 115 (47) ◽  
pp. 11988-11993 ◽  
Author(s):  
Staffan Jacob ◽  
Estelle Laurent ◽  
Bart Haegeman ◽  
Romain Bertrand ◽  
Jérôme G. Prunier ◽  
...  
Keyword(s):  
Environmental Changes ◽  
Environmental Variability ◽  
Habitat Preferences ◽  
Habitat Choice ◽  
Current Theory ◽  
Ecological Specialization ◽  
Metapopulation Model ◽  
Niche Specialization ◽  
Random Dispersal ◽  
Limited Dispersal

Limited dispersal is classically considered as a prerequisite for ecological specialization to evolve, such that generalists are expected to show greater dispersal propensity compared with specialists. However, when individuals choose habitats that maximize their performance instead of dispersing randomly, theory predicts dispersal with habitat choice to evolve in specialists, while generalists should disperse more randomly. We tested whether habitat choice is associated with thermal niche specialization using microcosms of the ciliate Tetrahymena thermophila, a species that performs active dispersal. We found that thermal specialists preferred optimal habitats as predicted by theory, a link that should make specialists more likely to track suitable conditions under environmental changes than expected under the random dispersal assumption. Surprisingly, generalists also performed habitat choice but with a preference for suboptimal habitats. Since this result challenges current theory, we developed a metapopulation model to understand under which circumstances such a preference for suboptimal habitats should evolve. We showed that competition between generalists and specialists may favor a preference for niche margins in generalists under environmental variability. Our results demonstrate that the behavioral dimension of dispersal—here, habitat choice—fundamentally alters our predictions of how dispersal evolve with niche specialization, making dispersal behaviors crucial for ecological forecasting facing environmental changes.

Workhorse Models

2015 ◽  
Author(s):  
Pol Antràs
Keyword(s):  
International Trade ◽  
Intellectual History ◽  
Empirical Studies ◽  
Theoretical Work ◽  
Central Unit ◽  
Unit Of Analysis ◽  
Basic Understanding ◽  
History Of ◽  
Key Features ◽  
The Rich

This chapter provides a succinct account of the rich intellectual history of the field of international trade and offers an overview of its modern workhorse models. This field has experienced a true revolution in recent years. Firms rather than countries or industries are now the central unit of analysis. The workhorse trade models used by most researchers both in theoretical work as well as in guiding empirical studies were published in the 2000s. While these benchmark frameworks ignore contractual aspects, they constitute the backbone of the models developed later in this volume, so the chapter provides a basic understanding of their key features.

Continual representation learning for evolving biomedical bipartite networks

2021 ◽  
Author(s):  
Kishlay Jha ◽  
Guangxu Xun ◽  
Aidong Zhang
Keyword(s):  
Network Structure ◽  
Learning Strategy ◽  
Structure Learning ◽  
Fundamental Problem ◽  
Representation Learning ◽  
Research Area ◽  
Bipartite Network ◽  
Bipartite Networks ◽  
Straightforward Application ◽  
Low Dimensional

Abstract Motivation Many real-world biomedical interactions such as ‘gene-disease’, ‘disease-symptom’ and ‘drug-target’ are modeled as a bipartite network structure. Learning meaningful representations for such networks is a fundamental problem in the research area of Network Representation Learning (NRL). NRL approaches aim to translate the network structure into low-dimensional vector representations that are useful to a variety of biomedical applications. Despite significant advances, the existing approaches still have certain limitations. First, a majority of these approaches do not model the unique topological properties of bipartite networks. Consequently, their straightforward application to the bipartite graphs yields unsatisfactory results. Second, the existing approaches typically learn representations from static networks. This is limiting for the biomedical bipartite networks that evolve at a rapid pace, and thus necessitate the development of approaches that can update the representations in an online fashion. Results In this research, we propose a novel representation learning approach that accurately preserves the intricate bipartite structure, and efficiently updates the node representations. Specifically, we design a customized autoencoder that captures the proximity relationship between nodes participating in the bipartite bicliques (2 × 2 sub-graph), while preserving both the global and local structures. Moreover, the proposed structure-preserving technique is carefully interleaved with the central tenets of continual machine learning to design an incremental learning strategy that updates the node representations in an online manner. Taken together, the proposed approach produces meaningful representations with high fidelity and computational efficiency. Extensive experiments conducted on several biomedical bipartite networks validate the effectiveness and rationality of the proposed approach.

scholarly journals Health system resilience: a literature review of empirical research

2020 ◽  
Vol 35 (8) ◽  
pp. 1084-1109
Author(s):  
Louise Biddle ◽  
Katharina Wahedi ◽  
Kayvan Bozorgmehr
Keyword(s):  
Health System ◽  
Mixed Methods Research ◽  
Quantitative Research ◽  
Empirical Studies ◽  
Disease Outbreaks ◽  
Building Blocks ◽  
Theoretical Work ◽  
Empirical Literature ◽  
Quantitative And Qualitative Research ◽  
System Resilience

Abstract The concept of health system resilience has gained popularity in the global health discourse, featuring in UN policies, academic articles and conferences. While substantial effort has gone into the conceptualization of health system resilience, there has been no review of how the concept has been operationalized in empirical studies. We conducted an empirical review in three databases using systematic methods. Findings were synthesized using descriptive quantitative analysis and by mapping aims, findings, underlying concepts and measurement approaches according to the resilience definition by Blanchet et al. We identified 71 empirical studies on health system resilience from 2008 to 2019, with an increase in literature in recent years (62% of studies published since 2017). Most studies addressed a specific crisis or challenge (82%), most notably infectious disease outbreaks (20%), natural disasters (15%) and climate change (11%). A large proportion of studies focused on service delivery (48%), while other health system building blocks were side-lined. The studies differed in terms of their disciplinary tradition and conceptual background, which was reflected in the variety of concepts and measurement approaches used. Despite extensive theoretical work on the domains which constitute health system resilience, we found that most of the empirical literature only addressed particular aspects related to absorptive and adaptive capacities, with legitimacy of institutions and transformative resilience seldom addressed. Qualitative and mixed methods research captured a broader range of resilience domains than quantitative research. The review shows that the way in which resilience is currently applied in the empirical literature does not match its theoretical foundations. In order to do justice to the complexities of the resilience concept, knowledge from both quantitative and qualitative research traditions should be integrated in a comprehensive assessment framework. Only then will the theoretical ‘resilience idea’ be able to prove its usefulness for the research community.

scholarly journals Całościowe ujęcie krajobrazu, wybrane podejścia i problemy badawcze = The holistic conceptualisation of the landscape, selected approaches and research problems

2019 ◽  
Vol 91 (3) ◽  
pp. 325-347
Author(s):  
Bożena Degórska ◽  
Marek Degórski
Keyword(s):  
Cultural Landscape ◽  
Landscape Connectivity ◽  
Theoretical Work ◽  
Current Approach ◽  
Added Value ◽  
Anthropogenic Pressure ◽  
Cultural Patterns ◽  
Natural Systems ◽  
Holistic Approaches ◽  
Research Problems

The aim of this theoretical work is to systemize and synthesize selected issues related to the approach to landscape. Presented here are: 1) selected holistic approaches to the cultural landscape, with particular attention paid to the added value of the current approach; 2) the rationale behind the devastated landscape being assigned to a separate category, rather than considered under the “cultural landscape” heading – and the essence of the associated typological separateness, as a logical inference from the interaction of the anthropogenic and natural systems in the formation of landscape properties, which emphasises the disappearance of cultural patterns as a devastated landscape is created; 3) an outline of research themes pertaining to landscape connectivity and permeability, as well as inter-penetration, with parallel depiction of substantive premises underpinning a somewhat different treatment of these properties. Given the progressive withdrawal of the term natural landscape, and also taking account of the category of cultural landscape and the level of anthropogenic pressure, the authors propose the division of the landscape into 3 categories: primary, cultural and devastated. This denotes an intentional separation and distinguishing of the devastated landscape, with the addition of this category justified in terms of the disappearance of cultural patterns that the formation of such a landscape entails.

scholarly journals Integrating Economic dynamics into Ecological Networks: The case of fishery sustainability

2019 ◽  
Author(s):  
Paul Glaum ◽  
Valentin Cocco ◽  
Fernanda S. Valdovinos
Keyword(s):  
Network Theory ◽  
Management Strategies ◽  
Single Species ◽  
Fishing Effort ◽  
Ecological Networks ◽  
Ecological Network ◽  
Ecological Dynamics ◽  
Natural Systems ◽  
Insight Into

Summary/AbstractUnderstanding and sustainably managing anthropogenic impact on ecosystems requires studying the integrated economic -ecological dynamics driving coupled human-natural systems. Here, we expand ecological network theory to study fishery sustainability by incorporating economic drivers into food-web models to evaluate the dynamics of thousands of single-species fisheries across hundreds of generated food-webs and two management strategies. Analysis reveals harvesting high population biomass species can initially support fishery persistence, but threatens long term economic and ecological sustainability by indirectly inducing extinction cascades in non-harvested species. This dynamic is exacerbated in open access fisheries where profit driven growth in fishing effort increases perturbation strength. Results demonstrate the unique insight into both ecological dynamics and sustainability garnered from considering economically dynamic fishing effort in the network.One Sentence SummaryIntegrating economic drivers into ecological networks reveal non-linear drivers of sustainability in fisheries.

scholarly journals Linked supergenes underlie split sex ratio and social organization in an ant

2021 ◽  
Author(s):  
German Lagunas-Robles ◽  
Jessica Purcell ◽  
Alan Brelsford
Keyword(s):  
Sex Ratio ◽  
Sex Allocation ◽  
Empirical Studies ◽  
Population Level ◽  
Theoretical Work ◽  
Female Offspring ◽  
Genomic Region ◽  
Genomic Conflict ◽  
Theoretical Predictions ◽  
Formica Podzolica

AbstractSexually reproducing organisms usually invest equally in male and female offspring. Deviations from this pattern have led researchers to new discoveries in the study of parent-offspring conflict, genomic conflict, and cooperation. Some social insect species exhibit the unusual population-level pattern of split sex ratio, wherein some colonies specialize in the production of future queens and others specialize in the production of males. Theoretical work focused on the relatedness asymmetries emerging from haplodiploid inheritance, whereby queens are equally related to daughters and sons, but their daughter workers are more closely related to sisters than to brothers, led to a series of testable predictions and spawned many empirical studies of this phenomenon. However, not all empirical systems follow predicted patterns, so questions remain about how split sex ratio emerges. Here, we sequence the genomes of 138 Formica glacialis workers from 34 male-producing and 34 gyne-producing colonies to determine whether split sex ratio is under genetic control. We identify a supergene spanning 5.5 Mbp that is closely associated with sex allocation in this system. Strikingly, this supergene is adjacent to another supergene spanning 5 Mbp that is associated with variation in colony queen number. We identify a similar pattern in a second related species, Formica podzolica. The discovery that split sex ratio is determined, at least in part, by a supergene in two species opens a new line of research on the evolutionary drivers of split sex ratio.Significance StatementSome social insects exhibit split sex ratio, wherein some colonies produce future queens and others produce males. This phenomenon spawned many influential theoretical studies and empirical tests, both of which have advanced our understanding of parent-offspring conflicts and cooperation. However, some empirical systems did not follow theoretical predictions, indicating that researchers lack a comprehensive understanding of the drivers of split sex ratio. Here, we show that split sex ratio is associated with a large genomic region in two ant species. The discovery of a genetic basis for sex allocation in ants provides a novel explanation for this phenomenon, particularly in systems where empirical observations deviate from theoretical predictions.

scholarly journals Generalizing to generalize: when (and when not) to be compositional in task structure learning

2019 ◽  
Author(s):  
Nicholas T. Franklin ◽  
Michael J. Frank
Keyword(s):  
National Science Foundation ◽  
Structure Learning ◽  
Human Subjects ◽  
Empirical Studies ◽  
Theoretical Work ◽  
State Transitions ◽  
Task Structure ◽  
Learned Behavior ◽  
Learning Agent ◽  
Author Note

AbstractHumans routinely face novel environments in which they have to generalize in order toact adaptively. However, doing so involves the non-trivial challenge of deciding which aspects of a task domain to generalize. While it is sometimes appropriate to simply re-use a learned behavior, often adaptive generalization entails recombining distinct components of knowledge acquired across multiple contexts. Theoretical work has suggested a computational trade-off in which it can be more or less useful to learn and generalize aspects of task structure jointly or compositionally, depending on previous task statistics, but empirical studies are lacking. Here we develop a series of navigation tasks which manipulate the statistics of goal values (“what to do”) and state transitions (“how to do it”) across contexts, and assess whether human subjects generalize these task components separately or conjunctively. We find that human generalization is sensitive to the statistics of the previously experienced task domain, favoring compositional or conjunctive generalization when the task statistics are indicative of such structures, and a mixture of the two when they are more ambiguous. These results support the predictions of a normative “meta-generalization learning” agent that does not only generalize previous knowledge but also generalizes the statistical structure most likely to support generalization.Author NoteThis work was supported in part by the National Science Foundation Proposal 1460604 “How Prefrontal Cortex Augments Reinforcement Learning” to MJF. We thank Mark Ho for providing code used in the behavioral task. We thank Matt Nassar for helpful discussions. Correspondence should be addressed to Nicholas T. Franklin ([email protected]) or Michael J. Frank ([email protected]).

scholarly journals The network structure of cancer ecosystems

2017 ◽  
Author(s):  
Simón P. Castillo ◽  
Rolando Rebolledo ◽  
Matias Arim ◽  
Michael E. Hochberg ◽  
Pablo A. Marquet
Keyword(s):  
Cancer Progression ◽  
Network Structure ◽  
Propagule Pressure ◽  
Ecological Networks ◽  
Bipartite Network ◽  
Tumor Spread ◽  
Heterogeneous Distribution ◽  
Arterial Blood ◽  
Stem Cell Divisions ◽  
Cancer Network

Ever since Paget’s seed-and-soil and Ewing’s connectivity hypotheses to explain tumor metastasis (1,2), it has become clear that cancer progression can be envisaged as an ecological phenomenon. This connection has flourished during the past two decades (3–7), giving rise to important insights into the ecology and evolution of cancer progression, with therapeutic implications (8–10). Here, we take a metapopulation view of metastasis (i.e. the migration to and colonization of, habitat patches) and represent it as a bipartite network, distinguishing source patches, or organs that host a primary tumor, and acceptor patches, or organs colonized ultimately from the source through metastasis. Using 20,326, biomedical records obtained from literature, we show that: (i) the network structure of cancer ecosystems is non-random, exhibiting a nested subset pattern as has been found both in the distribution of species across islands and island-like habitats (11–13), and in the distribution of among species interactions across different ecological networks (14–16); (ii) similar to ecological networks, there is a heterogeneous distribution of degree (i.e., number of connections associated with a source or acceptor organ); (iii) there is a significant correlation between metastatic incidence (or the frequency with which tumor cells from a source organ colonize an acceptor one) and arterial blood supply, suggesting that more irrigated organs have a higher probability of developing metastasis or being invaded; (iv) there is a positive correlation between metastatic incidence and acceptor organ degree (or number of different tumor-bearing source organs that generate metastasis in a given acceptor organ), and a negative one between acceptor organ degree and number of stem cell divisions, implying that there are preferred sink organs for metastasis and that this could be related to average acceptor organ cell longevity; (v) there is a negative association between organ cell turnover and source organ degree, implying that organs with rapid cell turnovers tend to generate more metastasis, a process akin to the phenomenon of propagule pressure in ecology (17); and (vi) the cancer ecosystem network exhibits a modular structure in both source and acceptor patches, suggesting that some of them share more connections among themselves than with the rest of the network. We show that both niche-related processes occurring at the organ level as well as spatial connectivity and propagule pressure contribute to metastaticspread and result in a non-random cancer network, which exhibits a truncated power law degree distribution, clustering and a nested subset structure. The similarity between the cancer network and ecological networks highlights the importance of ecological approaches in increasing our understanding of patterns in cancer incidence and dynamics, which may lead to new strategies to control tumor spread within the human ecosystem.

Sign in / Sign up

Export Citation Format

Share Document