{
  "abstract": "This study develops a spatial agent-based framework for examining how unequal resource access, environmental stress, institutional support, movement, and adaptive cooperation jointly shape conflict pressure and resource inequality. A Uganda case study initializes spatial heterogeneity from WorldPop 2020 population data and CHIRPS v2.0 October–November 2025 rainfall. The primary experiment uses an 80×80 grid, 250 agents, 120 time steps, and 20 baseline seeds. Parameter dependence is evaluated using 128 Latin-hypercube designs with five stochastic replicates per design, time-aware cluster-robust regressions, partial rank correlations, dense one-at-a-time sweeps, structural ablations, and grid/agent-count robustness checks. In the baseline ensemble, the Gini coefficient rises from 0.192 to 0.868 while mean cooperation falls from 0.547 to 0.118; conflict pressure stabilizes near 0.207 after an early transient. Institutional support increases cooperation and mean resources and reduces inequality over the tested range, while also altering the interaction-level conflict index, showing that lower modeled conflict is not necessarily a better system state. Removing the resource-disparity term reduces but does not eliminate conflict, and suppressing behavioral adaptation raises final conflict by about 40% relative to the baseline. The framework is therefore best interpreted as a transparent mechanism-exploration and stress-testing tool rather than an event-forecasting model.",
  "abstract_shown": true,
  "affiliations": [
    "Department of Mathematics, Kabale University, Kikungiri Hill, Kabale, Uganda"
  ],
  "article_type": "Research Article",
  "arxiv": null,
  "author_total": 1,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Ronald Katende"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/djb8k17apec8t.bib",
  "cited_by": 0,
  "doi": "10.1371/journal.pone.0357283",
  "fulltext_url": null,
  "id": "djb8k17apec8t",
  "issns": [
    "1932-6203"
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  "landing_url": "https://doi.org/10.1371/journal.pone.0357283",
  "language": null,
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "journal",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "openalex",
      "3312|Political Conflict and Governance"
    ],
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      "/Biology and life sciences/Neuroscience/Cognitive science/Cognitive psychology/Learning"
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      "plos",
      "/Biology and life sciences/Psychology/Cognitive psychology/Learning"
    ],
    [
      "plos",
      "/Biology and life sciences/Psychology/Collective human behavior"
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      "/Computer and information sciences/Systems science/Agent-based modeling"
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      "/Earth sciences/Geography/Human geography/Human mobility"
    ],
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      "plos",
      "/Earth sciences/Geography/Human geography/Land use"
    ],
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      "plos",
      "/Earth sciences/Geomorphology/Terrain"
    ],
    [
      "plos",
      "/Engineering and technology/Energy and power/Power distribution/Power grids"
    ],
    [
      "plos",
      "/People and places/Geographical locations/Africa/Uganda"
    ],
    [
      "plos",
      "/Physical sciences/Mathematics/Systems science/Agent-based modeling"
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      "/Research and analysis methods/Simulation and modeling/Agent-based modeling"
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      "/Social sciences/Human geography/Human mobility"
    ],
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      "plos",
      "/Social sciences/Human geography/Land use"
    ],
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      "plos",
      "/Social sciences/Psychology/Cognitive psychology/Learning"
    ],
    [
      "plos",
      "/Social sciences/Psychology/Collective human behavior"
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  "openalex": "W7213416728",
  "pdf_url": "https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0357283&type=printable",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-16",
  "publisher": "Public Library of Science",
  "ris": "https://research.draconitic.com/paper/djb8k17apec8t.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:17:49Z",
      "native_id": "10.1371/journal.pone.0357283",
      "source": "plos",
      "url": "https://doi.org/10.1371/journal.pone.0357283"
    }
  ],
  "subjects": [
    {
      "field": "biology",
      "origin": "plos:neuroscience",
      "subfield": "neuroscience"
    },
    {
      "field": "earth",
      "origin": "plos:geomorphology",
      "subfield": "geology-geochemistry"
    }
  ],
  "title": "Modeling resource conflict and inequality in fragile systems: A spatial agent-based framework with a Uganda case study",
  "title_text": "Modeling resource conflict and inequality in fragile systems: A spatial agent-based framework with a Uganda case study",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T12:17:49Z",
  "url": "https://research.draconitic.com/paper/djb8k17apec8t",
  "venue": "PLOS One",
  "versions": []
}