Co-evolution of network structure and consumer inequality in a spatially explicit model of energetic resource acquisition

Natalie Davis, Andrew Jarvis, J. Gareth Polhill

Research output: Contribution to JournalArticleAcademicpeer-review

Original languageUndefined/Unknown
Article number128261
JournalPhysica A: Statistical Mechanics and its Applications
Volume608, Part 1
DOIs
Publication statusPublished - 15 Dec 2022

Funding

Funding was provided by a joint Lancaster University/The James Hutton Institute, UK Ph.D. studentship to ND. The authors acknowledge useful comments from two anonymous reviewers, which helped sharpen the manuscript, and the efforts of the editor, Dr Michael Small, in finding said reviewers. In addition, ND acknowledges statistical advice from Dr Vicki Davis and discussions on the modelling framework with Dr Kirsti Ashworth, as well as feedback on model and experimental design from Dr Nanda Wijermans and Dr Émile Chappin at ESSA@work during Social Simulation Week 2020. The authors also acknowledge the Research/Scientific Computing teams at The James Hutton Institute and NIAB for providing computational resources and enduringly patient technical support for the “UK’s Crop Diversity Bioinformatics HPC” ( BBSRC, UK grant BB/S019669/1 ) and the James Hutton Institute computing cluster, which were used to run the simulations reported within this paper. GP is grateful for funding from the Scottish Government’s Strategic Research Programme, UK 2022–27 (project JHI-C5-1 ). Funding was provided by a joint Lancaster University/The James Hutton Institute, UK Ph.D. studentship to ND. The authors acknowledge useful comments from two anonymous reviewers, which helped sharpen the manuscript, and the efforts of the editor, Dr Michael Small, in finding said reviewers. In addition, ND acknowledges statistical advice from Dr Vicki Davis and discussions on the modelling framework with Dr Kirsti Ashworth, as well as feedback on model and experimental design from Dr Nanda Wijermans and Dr Émile Chappin at ESSA@work during Social Simulation Week 2020. The authors also acknowledge the Research/Scientific Computing teams at The James Hutton Institute and NIAB for providing computational resources and enduringly patient technical support for the “UK's Crop Diversity Bioinformatics HPC” (BBSRC, UK grant BB/S019669/1) and the James Hutton Institute computing cluster, which were used to run the simulations reported within this paper. GP is grateful for funding from the Scottish Government's Strategic Research Programme, UK 2022–27 (project JHI-C5-1).

FundersFunder number
Scottish Government's Strategic Research Programme
Scottish Government’s Strategic Research ProgrammeUK 2022–27, JHI-C5-1
James Hutton Institute
Biotechnology and Biological Sciences Research CouncilBB/S019669/1
National Institute of Agricultural Biotechnology

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