Evidence map›Paper›PMID 35198973›Full record

ArticleFrontiers in big data2022

Network Models and Simulation Analytics for Multi-scale Dynamics of Biological Invasions.

Abhijin Adiga, Nicholas Palmer, Young Yun Baek, Henning Mortveit, S S Ravi

Abstract read
In one paragraph

Article in Frontiers in big data, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Abhijin AdigaBiocomplexity Institute and Initiative, University of Virginia, Charlottesville, VA, United States.
Nicholas PalmerBiocomplexity Institute and Initiative, University of Virginia, Charlottesville, VA, United States.
Young Yun BaekBiocomplexity Institute and Initiative, University of Virginia, Charlottesville, VA, United States.
Henning MortveitBiocomplexity Institute and Initiative, University of Virginia, Charlottesville, VA, United States.
S S RaviBiocomplexity Institute and Initiative, University of Virginia, Charlottesville, VA, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Globalization and climate change facilitate the spread and establishment of invasive species throughout the world via multiple pathways. These spread mechanisms can be effectively represented as diffusion processes on multi-scale, spatial networks. Such network-based modeling and simulation approaches are being increasingly applied in this domain. However, these works tend to be largely domain-specific, lacking any graph theoretic formalisms, and do not take advantage of more recent developments in network science. This work is aimed toward filling some of these gaps. We develop a generic multi-scale spatial network framework that is applicable to a wide range of models developed in the literature on biological invasions. A key question we address is the following: how do individual pathways and their combinations influence the rate and pattern of spread? The analytical complexity arises more from the multi-scale nature and complex functional components of the networks rather than from the sizes of the networks. We present theoretical bounds on the spectral radius and the diameter of multi-scale networks. These two structural graph parameters have established connections to diffusion processes. Specifically, we study how network properties, such as spectral radius and diameter are influenced by model parameters. Further, we analyze a multi-pathway diffusion model from the literature by conducting simulations on synthetic and real-world networks and then use regression tree analysis to identify the important network and diffusion model parameters that influence the dynamics.

Indexed as

diffusion processesinvasive speciesmulti-scale networksnetwork modelssimulation analyticsspatial networks

Identifiers

PMID35198973
PMCPMC8859470

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.