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Xian J, Zhang Z, Li Z, Yang D. Coupled Information-Epidemic Spreading Dynamics with Selective Mass Media. Entropy (Basel) 2023; 25:927. [PMID: 37372271 DOI: 10.3390/e25060927] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/24/2023] [Revised: 06/04/2023] [Accepted: 06/05/2023] [Indexed: 06/29/2023]
Abstract
As a pandemic emerges, information on epidemic prevention disseminates among the populace, and the propagation of that information interacts with the proliferation of the disease. Mass media serve a pivotal function in facilitating the dissemination of epidemic-related information. Investigating coupled information-epidemic dynamics, while accounting for the promotional effect of mass media in information dissemination, is of significant practical relevance. Nonetheless, in the extant research, scholars predominantly employ an assumption that mass media broadcast to all individuals equally within the network: this assumption overlooks the practical constraint imposed by the substantial social resources required to accomplish such comprehensive promotion. In response, this study introduces a coupled information-epidemic spreading model with mass media that can selectively target and disseminate information to a specific proportion of high-degree nodes. We employed a microscopic Markov chain methodology to scrutinize our model, and we examined the influence of the various model parameters on the dynamic process. The findings of this study reveal that mass media broadcasts directed towards high-degree nodes within the information spreading layer can substantially reduce the infection density of the epidemic, and raise the spreading threshold of the epidemic. Additionally, as the mass media broadcast proportion increases, the suppression effect on the disease becomes stronger. Moreover, with a constant broadcast proportion, the suppression effect of mass media promotion on epidemic spreading within the model is more pronounced in a multiplex network with a negative interlayer degree correlation, compared to scenarios with positive or absent interlayer degree correlation.
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Affiliation(s)
- Jiajun Xian
- Department of Computer Science, School of Engineering, Shantou University, Shantou 515063, China
| | - Zhihong Zhang
- Department of Computer Science, School of Engineering, Shantou University, Shantou 515063, China
| | - Zongyi Li
- Department of Computer Science, School of Engineering, Shantou University, Shantou 515063, China
| | - Dan Yang
- Department of Computer Science, School of Engineering, Shantou University, Shantou 515063, China
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2
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Felipe-Lucia MR, Guerrero AM, Alexander SM, Ashander J, Baggio JA, Barnes ML, Bodin Ö, Bonn A, Fortin MJ, Friedman RS, Gephart JA, Helmstedt KJ, Keyes AA, Kroetz K, Massol F, Pocock MJO, Sayles J, Thompson RM, Wood SA, Dee LE. Conceptualizing ecosystem services using social-ecological networks. Trends Ecol Evol 2021; 37:211-222. [PMID: 34969536 DOI: 10.1016/j.tree.2021.11.012] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2021] [Revised: 10/15/2021] [Accepted: 11/24/2021] [Indexed: 12/01/2022]
Abstract
Social-ecological networks (SENs) represent the complex relationships between ecological and social systems and are a useful tool for analyzing and managing ecosystem services. However, mainstreaming the application of SENs in ecosystem service research has been hindered by a lack of clarity about how to match research questions to ecosystem service conceptualizations in SEN (i.e., as nodes, links, attributes, or emergent properties). Building from different disciplines, we propose a typology to represent ecosystem service in SENs and identify opportunities and challenges of using SENs in ecosystem service research. Our typology provides guidance for this growing field to improve research design and increase the breadth of questions that can be addressed with SEN to understand human-nature interdependencies in a changing world.
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Affiliation(s)
- María R Felipe-Lucia
- Department Ecosystem Services, Helmholtz Centre for Environmental Research - UFZ, Permoserstraße 15, 04318 Leipzig, Germany; German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Puschstrasse 4, 04103 Leipzig, Germany.
| | - Angela M Guerrero
- Stockholm Resilience Centre, Kräftriket 2B, 10691 Stockholm, Sweden; Queensland University of Technology, Brisbane, QLD, 4000, Australia
| | - Steven M Alexander
- Environmental Change and Governance Group, University of Waterloo, 200 University Ave. W, Waterloo, ON N2L 3G1, Canada
| | - Jaime Ashander
- Resources for the Future, 1616 P St. NW, Washington, DC 20036, USA
| | - Jacopo A Baggio
- School of Politics, Security and International Affairs, National Center for Integrated Coastal Research, 4297 Andromeda Loop N, Orlando, FL 32816, USA
| | - Michele L Barnes
- ARC Centre of Excellence for Coral Reef Studies, James Cook University, Townsville, QLD, 4810, Australia
| | - Örjan Bodin
- Stockholm Resilience Centre, Kräftriket 2B, 10691 Stockholm, Sweden
| | - Aletta Bonn
- Department Ecosystem Services, Helmholtz Centre for Environmental Research - UFZ, Permoserstraße 15, 04318 Leipzig, Germany; German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Puschstrasse 4, 04103 Leipzig, Germany; Institute of Biodiversity, Friedrich Schiller University Jena, Dornburgerstraße 159, 07743 Jena, Germany
| | - Marie-Josée Fortin
- Department of Ecology and Evolutionary Biology, University of Toronto, 25 Willcocks Street, Toronto, ON M5S 3B2, Canada
| | - Rachel S Friedman
- Institute for Climate, Energy and Disaster Solutions, Australian National University College of Science, Building 141, Linnaeus Way, Acton, ACT, 2601, Australia
| | - Jessica A Gephart
- Department of Environmental Science, American University, 4400 Massachusetts Ave. NW, Washington, DC 20016, USA
| | - Kate J Helmstedt
- School of Mathematical Sciences, Queensland University of Technology, 2 George St., Brisbane, City, QLD, 4000, Australia
| | - Aislyn A Keyes
- Department of Ecology and Evolutionary Biology, University of Colorado, Boulder, Ramaley Biology, Boulder, CO 80302, USA
| | - Kailin Kroetz
- School of Sustainability, Arizona State University and Resources for the Future, PO Box 875502, Tempe, AZ 85287-5502, USA
| | - François Massol
- University of Lille, CNRS, Inserm, CHU Lille, Institut Pasteur de Lille, U1019, UMR 9017, Center for Infection and Immunity of Lille (CIIL), F-59000 Lille, France
| | | | - Jesse Sayles
- ORISE Postdoctoral Fellow Appointed with the US Environmental Protection Agency, Office of Research and Development, Center for Environmental Measurement and Modeling, Atlantic Coastal Environmental Sciences Division, 27 Tarzwell Dr., Narragansett, RI 02882, USA
| | - Ross M Thompson
- Centre for Applied Water Science, Institute for Applied Ecology, University of Canberra, ACT, 2617, Australia
| | - Spencer A Wood
- College of the Environment, University of Washington, Box 352100, Seattle, WA 98195, USA
| | - Laura E Dee
- School of Sustainability, Arizona State University and Resources for the Future, PO Box 875502, Tempe, AZ 85287-5502, USA
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3
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Kumar Verma U, Ambika G. Emergent Dynamics and Spatio Temporal Patterns on Multiplex Neuronal Networks. Front Comput Neurosci 2021; 15:774969. [PMID: 34924985 PMCID: PMC8674435 DOI: 10.3389/fncom.2021.774969] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2021] [Accepted: 11/01/2021] [Indexed: 11/16/2022] Open
Abstract
We present a study on the emergence of a variety of spatio temporal patterns among neurons that are connected in a multiplex framework, with neurons on two layers with different functional couplings. With the Hindmarsh-Rose model for the dynamics of single neurons, we analyze the possible patterns of dynamics in each layer separately and report emergent patterns of activity like in-phase synchronized oscillations and amplitude death (AD) for excitatory coupling and anti-phase mixed-mode oscillations (MMO) in multi-clusters with phase regularities when the connections are inhibitory. When they are multiplexed, with neurons of one layer coupled with excitatory synaptic coupling and neurons of the other layer coupled with inhibitory synaptic coupling, we observe the transfer or selection of interesting patterns of collective behavior between the layers. While the revival of oscillations occurs in the layer with excitatory coupling, the transition from anti-phase to in-phase and vice versa is observed in the other layer with inhibitory synaptic coupling. We also discuss how the selection of these spatio temporal patterns can be controlled by tuning the intralayer or interlayer coupling strengths or increasing the range of non-local coupling. With one layer having electrical coupling while the other synaptic coupling of excitatory(inhibitory)type, we find in-phase(anti-phase) synchronized patterns of activity among neurons in both layers.
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Affiliation(s)
| | - G. Ambika
- Department of Physics, Indian Institute of Science Education and Research Tirupati, Tirupati, India
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4
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Yu L, Xia M, An Q. A network embedding framework based on integrating multiplex network for drug combination prediction. Brief Bioinform 2021; 23:6367637. [PMID: 34505623 DOI: 10.1093/bib/bbab364] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2021] [Revised: 08/16/2021] [Accepted: 08/17/2021] [Indexed: 11/14/2022] Open
Abstract
Drug combination is a sensible strategy for disease treatment because it improves the treatment efficacy and reduces concomitant side effects. Due to the large number of possible combinations among candidate compounds, exhaustive screening is prohibitive. Currently, a large number of studies have focused on predicting potential drug combinations. However, these methods are not entirely satisfactory in terms of performance and scalability. In this paper, we proposed a Network Embedding frameWork in MultIplex Network (NEWMIN) to predict synthetic drug combinations. Based on a multiplex drug similarity network, we offered alternative methods to integrate useful information from different aspects and to decide the quantitative importance of each network. For drug combination prediction, we found seven novel drug combinations that have been validated by external sources among the top-ranked predictions of our model. To verify the feasibility of NEWMIN, we compared NEWMIN with other five methods, for which it showed better performance than other methods in terms of the area under the precision-recall curve and receiver operating characteristic curve.
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Affiliation(s)
- Liang Yu
- School of Computer Science and Technology, Xidian University, Xi'an 710071, P.R. China
| | - Mingfei Xia
- School of Computer Science and Technology, Xidian University, Xi'an 710071, P.R. China
| | - Qi An
- School of Computer Science and Technology, Xidian University, Xi'an 710071, P.R. China
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Chen N, Liu G, Guo M, Li Y, Yao Z, Hu B. Calcarine as a bridge between brain function and structure in irritable bowel syndrome: A multiplex network analysis. J Gastroenterol Hepatol 2021; 36:2408-2415. [PMID: 33354807 DOI: 10.1111/jgh.15382] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/12/2020] [Revised: 11/09/2020] [Accepted: 12/16/2020] [Indexed: 12/11/2022]
Abstract
BACKGROUND AND AIM Jointly analyzing structural and functional brain networks enables a better understanding of pathological underpinnings of irritable bowel syndrome (IBS). Multiplex network analysis provides a novel framework to study complex networks consisting of different types of connectivity patterns in multimodal data. METHODS In the present work, we integrated functional and structural networks to a multiplex network. Then, the multiplex metrics and the inner-layer/inter-layer hub nodes were investigated through 34 patients with IBS and 33 healthy controls. RESULTS Significantly differential multiplex degree in both left and right parts of calcarine was found, and meanwhile, IBS patients lost inner-layer hub properties in these regions. In addition, the left fusiform was no longer practicing as an inner-layer hub node, while the right median cingulate acted as a new inner-layer hub node in the IBS patients. Besides, the right calcarine, which lost its inner-layer hub identity, became a new inter-layer hub node, and the multiplex degree of the left hippocampus, which lost its inter-layer hub identity in IBS patients, was significantly positively correlated with the IBS Symptom Severity Score scores. CONCLUSIONS Inner-layer hub nodes of multiplex networks were preferentially vulnerable, and some inner-layer hub nodes would convert into inter-layer hub nodes in IBS patients. Besides, the inter-layer hub nodes might be influenced by IBS severity and therefore converted to general nodes.
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Affiliation(s)
- Nan Chen
- Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou University, Lanzhou, China
| | - Guangyao Liu
- Department of Magnetic Resonance, Lanzhou University Second Hospital, Lanzhou, China
| | - Man Guo
- Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou University, Lanzhou, China
| | - Yongchao Li
- Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou University, Lanzhou, China
| | - Zhijun Yao
- Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou University, Lanzhou, China
| | - Bin Hu
- Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou University, Lanzhou, China.,Joint Research Center for Cognitive Neurosensor Technology of Lanzhou University and Institute of Semiconductors, Chinese Academy of Sciences, Lanzhou, China.,CAS Center for Excellence in Brain Science and Intelligence Technology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, China.,Ministry of Education, Engineering Research Center of Open Source Software and Real-Time System (Lanzhou University), Lanzhou, China
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6
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Zmazek J, Klemen MS, Markovič R, Dolenšek J, Marhl M, Stožer A, Gosak M. Assessing Different Temporal Scales of Calcium Dynamics in Networks of Beta Cell Populations. Front Physiol 2021; 12:612233. [PMID: 33833686 PMCID: PMC8021717 DOI: 10.3389/fphys.2021.612233] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2020] [Accepted: 02/26/2021] [Indexed: 01/06/2023] Open
Abstract
Beta cells within the pancreatic islets of Langerhans respond to stimulation with coherent oscillations of membrane potential and intracellular calcium concentration that presumably drive the pulsatile exocytosis of insulin. Their rhythmic activity is multimodal, resulting from networked feedback interactions of various oscillatory subsystems, such as the glycolytic, mitochondrial, and electrical/calcium components. How these oscillatory modules interact and affect the collective cellular activity, which is a prerequisite for proper hormone release, is incompletely understood. In the present work, we combined advanced confocal Ca2+ imaging in fresh mouse pancreas tissue slices with time series analysis and network science approaches to unveil the glucose-dependent characteristics of different oscillatory components on both the intra- and inter-cellular level. Our results reveal an interrelationship between the metabolically driven low-frequency component and the electrically driven high-frequency component, with the latter exhibiting the highest bursting rates around the peaks of the slow component and the lowest around the nadirs. Moreover, the activity, as well as the average synchronicity of the fast component, considerably increased with increasing stimulatory glucose concentration, whereas the stimulation level did not affect any of these parameters in the slow component domain. Remarkably, in both dynamical components, the average correlation decreased similarly with intercellular distance, which implies that intercellular communication affects the synchronicity of both types of oscillations. To explore the intra-islet synchronization patterns in more detail, we constructed functional connectivity maps. The subsequent comparison of network characteristics of different oscillatory components showed more locally clustered and segregated networks of fast oscillatory activity, while the slow oscillations were more global, resulting in several long-range connections and a more cohesive structure. Besides the structural differences, we found a relatively weak relationship between the fast and slow network layer, which suggests that different synchronization mechanisms shape the collective cellular activity in islets, a finding which has to be kept in mind in future studies employing different oscillations for constructing networks.
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Affiliation(s)
- Jan Zmazek
- Faculty of Natural Sciences and Mathematics, University of Maribor, Maribor, Slovenia
| | | | - Rene Markovič
- Faculty of Natural Sciences and Mathematics, University of Maribor, Maribor, Slovenia
- Faculty of Electrical Engineering and Computer Science, University of Maribor, Maribor, Slovenia
| | - Jurij Dolenšek
- Faculty of Natural Sciences and Mathematics, University of Maribor, Maribor, Slovenia
- Faculty of Medicine, University of Maribor, Maribor, Slovenia
| | - Marko Marhl
- Faculty of Natural Sciences and Mathematics, University of Maribor, Maribor, Slovenia
- Faculty of Medicine, University of Maribor, Maribor, Slovenia
- Faculty of Education, University of Maribor, Maribor, Slovenia
| | - Andraž Stožer
- Faculty of Medicine, University of Maribor, Maribor, Slovenia
| | - Marko Gosak
- Faculty of Natural Sciences and Mathematics, University of Maribor, Maribor, Slovenia
- Faculty of Medicine, University of Maribor, Maribor, Slovenia
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7
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Tianyu Shi, Ting Long, Yaohui Pan, Wensi Zhang, Chao Dong, Qiuju Yin. Effects of asymptomatic infection on the dynamical interplay between behavior and disease transmission in multiplex networks. Physica A 2019; 536. [PMID: 32288109 DOI: 10.1016/j.physa.2019.04.266] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/15/2018] [Revised: 03/05/2019] [Indexed: 06/02/2023]
Abstract
Multiplex network theory is widely introduced to deepen the understanding of the dynamical interplay between self-protective behavior and epidemic spreading. Most of the existing studies assumed that all infected individuals can transmit disease- related information or can be perceived by their neighbors. However, owing to lack of distinct symptoms for patients in the initial stage of infection, the disease information cannot be transmitted in the population, which may lead to the wrong perception of infection risk and inappropriate behavior response. In this work, we divide infected individuals into Exposed-state (without obvious clinical symptoms) individuals and Infected-state (with evident clinical symptoms) individuals, both of whom can spread disease, but only Infected-state individuals can diffuse disease information. Then, in this work we establish UAU-SEIS (Unaware–Aware–Unaware–Susceptible–Exposed–Infected–Susceptible) model in multiplex networks and analyze the effect of asymptomatic infection and the isolation of Infected-state individuals on the density of infection and the epidemic threshold. Furthermore, we extend the UAU-SEIS model by taking the individual heterogeneity into consideration. Combined Markov chain approach and Monte-Carlo Simulations, we find that asymptomatic infection has an effect on the density of infected individuals and the epidemic threshold, and the extent of the effect is influenced by whether Infected-state individuals are isolated or treated. In addition, results show that the individual heterogeneity can lower the density of infected individuals, but cannot enhance the epidemic threshold. We study the impact of asymptomatic infection on the epidemic spread dynamics in multiplex networks. We assume infected can be isolation and non isolation, then compare the research results of these two cases. We take the individual heterogeneity into consideration and study whether it affect research results.
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8
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Huang Y, Dai H, Ke R. Principles of Effective and Robust Innate Immune Response to Viral Infections: A Multiplex Network Analysis. Front Immunol 2019; 10:1736. [PMID: 31396233 PMCID: PMC6667926 DOI: 10.3389/fimmu.2019.01736] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2018] [Accepted: 07/09/2019] [Indexed: 12/12/2022] Open
Abstract
The human innate immune response, particularly the type-I interferon (IFN) response, is highly robust and effective first line of defense against virus invasion. IFN molecules are produced and secreted from infected cells upon virus infection and recognition. They then act as signaling/communication molecules to activate an antiviral response in neighboring cells so that those cells become refractory to infection. Previous experimental studies have identified the detailed molecular mechanisms for the IFN signaling and response. However, the principles underlying how host cells use IFN to communicate with each other to collectively and robustly halt an infection is not understood. Here we take a multiplex network modeling approach to provide a theoretical framework to identify key factors that determine the effectiveness of the IFN response against virus infection of a host. In this approach, we consider the virus spread among host cells and the interferon signaling to protect host cells as a competition process on a two-layer multiplex network. We focused on two types of network topology, i.e., the Erdős-Rényi (ER) network and the Geometric Random (GR) network, which represent the scenarios when infection of cells is mostly well mixed (e.g., in the blood) and when infection is spatially segregated (e.g., in tissues), respectively. We show that in general, the IFN response works effectively to stop viral infection when virus infection spreads spatially (a most likely scenario for initial virus infection of a host at the peripheral tissue). Importantly, we show that the effectiveness of the IFN response is robust against large variations in the distance of IFN diffusion as long as IFNs diffuse faster than viruses and they can effectively induce antiviral responses in susceptible host cells. This suggests that the effectiveness of the IFN response is insensitive to the specific arrangement of host cells in peripheral tissues. Thus, our work provides a quantitative explanation of why the IFN response can serve an effective and robust response in different tissue types to a wide range of viral infections of a host.
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Affiliation(s)
- Yufan Huang
- Department of Electrical and Computer Engineering, North Carolina State University, Raleigh, NC, United States
| | - Huaiyu Dai
- Department of Electrical and Computer Engineering, North Carolina State University, Raleigh, NC, United States
| | - Ruian Ke
- Department of Mathematics, North Carolina State University, Raleigh, NC, United States.,T-6, Theoretical Biology and Biophysics, Los Alamos National Laboratory, Los Alamos, NM, United States
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9
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Friesen SK, Martone R, Rubidge E, Baggio JA, Ban NC. An approach to incorporating inferred connectivity of adult movement into marine protected area design with limited data. Ecol Appl 2019; 29:e01890. [PMID: 30929286 PMCID: PMC6850429 DOI: 10.1002/eap.1890] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/10/2018] [Revised: 12/12/2018] [Accepted: 02/20/2019] [Indexed: 05/28/2023]
Abstract
Marine protected areas (MPAs) are important conservation tools that can support the resilience of marine ecosystems. Many countries, including Canada, have committed to protecting at least 10% of their marine areas under the Convention on Biological Diversity's Aichi Target 11, which includes connectivity as a key aspect. Connectivity, the movement of individuals among habitats, can enhance population stability and resilience within and among MPAs. However, little is known about regional spatial patterns of marine ecological connectivity, particularly adult movement. We developed a method to assess and design MPA networks that maximize inferred connectivity within habitat types for adult movement when ecological data are limited. We used the Northern Shelf Bioregion in British Columbia, Canada, to explore two different approaches: (1) evaluating sites important for inferred regional connectivity (termed hotspots) and (2) assessing MPA network configurations based on their overlap with connectivity hotspots and interconnectedness between MPAs. To assess inferred connectivity via adult movement, we used two different threshold distances (15 and 50 km) to capture moderate home ranges, which are most appropriate to consider in MPA design. We applied graph theory to assess inferred connectivity within 16 habitat and depth categories (proxies for distinct ecological communities), and used novel multiplex network methodologies to perform an aggregated assessment of inferred connectivity. We evaluated inferred regional connectivity hotspots based on betweenness and eigenvector centrality metrics, finding that the existing MPA network overlapped a moderate proportion of these regional hotspots and identified key areas to be considered as candidate MPAs. Network density among existing MPAs was low within the individual habitat networks, as well as the multiplex. This work informs an ongoing MPA planning process, and approaches for incorporating connectivity into MPA design when data are limited, with lessons for other contexts.
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Affiliation(s)
- Sarah K. Friesen
- School of Environmental StudiesUniversity of VictoriaVictoriaBritish ColumbiaV8W 2Y2Canada
| | - Rebecca Martone
- Ministry of Forests, Lands, Natural Resource Operations and Rural Development, Province of British ColumbiaVictoriaBritish ColumbiaV8W 9N1Canada
| | - Emily Rubidge
- Institute of Ocean Sciences, Fisheries and Oceans CanadaSidneyBritish ColumbiaV8L 4B2Canada
- Department of Forest and Conservation SciencesUniversity of British ColumbiaVancouverBritish ColumbiaV6T 1Z4Canada
| | - Jacopo A. Baggio
- Department of Political ScienceUniversity of Central FloridaOrlandoFlorida32816USA
- Sustainable Coastal Systems ClusterNational Center for Integrated Coastal ResearchUniversity of Central FloridaOrlandoFlorida32816USA
| | - Natalie C. Ban
- School of Environmental StudiesUniversity of VictoriaVictoriaBritish ColumbiaV8W 2Y2Canada
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10
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Gómez-Gardeñes J, de Domenico M, Gutiérrez G, Arenas A, Gómez S. Layer-layer competition in multiplex complex networks. Philos Trans A Math Phys Eng Sci 2015; 373:rsta.2015.0117. [PMID: 26527811 DOI: 10.1098/rsta.2015.0117] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 09/01/2015] [Indexed: 06/05/2023]
Abstract
The coexistence of multiple types of interactions within social, technological and biological networks has moved the focus of the physics of complex systems towards a multiplex description of the interactions between their constituents. This novel approach has unveiled that the multiplex nature of complex systems has strong influence in the emergence of collective states and their critical properties. Here we address an important issue that is intrinsic to the coexistence of multiple means of interactions within a network: their competition. To this aim, we study a two-layer multiplex in which the activity of users can be localized in each of the layers or shared between them, favouring that neighbouring nodes within a layer focus their activity on the same layer. This framework mimics the coexistence and competition of multiple communication channels, in a way that the prevalence of a particular communication platform emerges as a result of the localization of user activity in one single interaction layer. Our results indicate that there is a transition from localization (use of a preferred layer) to delocalization (combined usage of both layers) and that the prevalence of a particular layer (in the localized state) depends on the structural properties.
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Affiliation(s)
- J Gómez-Gardeñes
- Departamento de Física de la Materia Condensada, Universidad de Zaragoza, Zaragoza 50009, Spain Instituto de Biocomputación y Física de Sistemas Complejos, Universidad de Zaragoza, Zaragoza 50018, Spain
| | - M de Domenico
- Departament d'Enginyeria Informàtica i Matemàtiques, Universitat Rovira i Virgili, Tarragona 43007, Spain
| | - G Gutiérrez
- Departamento de Ciencias Aplicadas, Instituto Tecnológico Metropolitano, Medellín 354, Colombia
| | - A Arenas
- Departament d'Enginyeria Informàtica i Matemàtiques, Universitat Rovira i Virgili, Tarragona 43007, Spain
| | - S Gómez
- Departament d'Enginyeria Informàtica i Matemàtiques, Universitat Rovira i Virgili, Tarragona 43007, Spain
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11
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Abstract
Multiple diseases (acute or chronic events) occur together in a patient, which refers to the disease comorbidities, because of the multi ways associations among diseases. Due to shared genetic, molecular, environmental, and lifestyle-based risk factors, many diseases are comorbid in the same patient. Methods for integrating multiple types of omics data play an important role to identify integrative biomarkers for stratification of patients into groups with different clinical outcomes. Moreover, integrated omics and clinical information may potentially improve prediction accuracy of disease comorbidities. However, there is a lack of effective and efficient bioinformatics and statistical software for true integrative data analysis. With the availability of the wide spread huge omics, phenotype and ontology information, it is becoming more and more practical to help doctors in clinical diagnostics and comorbidity prediction by providing appropriate software tool. We developed an R software POGO to compute novel estimators of the disease comorbidity risks and patient stratification. Starting from an initial diagnosis, omics and clinical data of a patient the software identifies the association risk of disease comorbidities. The input of this software is the initial diagnosis of a patient and the output provides evidence of disease comorbidities. The functions of POGO offer flexibility for diagnostic applications to predict disease comorbidities, and can be easily integrated to high-throughput and clinical data analysis pipelines. POGO is compliant with the Bioconductor standard and it is freely available at www.cl.cam.ac.uk/~mam211/POGO/.
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Affiliation(s)
- Mohammad Ali Moni
- Computer Laboratory, University of CambridgeCambridge, UK
- Department of Computer Science and Engineering, Pabna University of Science and TechnologyPabna, Bangladesh
- Bone Biology, Garvan Institute of Medical Research, The University of New South WalesSydney, NSW, Australia
| | - Pietro Liò
- Computer Laboratory, University of CambridgeCambridge, UK
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