Modeling resource conflict and inequality in fragile systems: A spatial agent-based framework with a Uganda case study
- 1Department of Mathematics, Kabale University, Kikungiri Hill, Kabale, Uganda
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.
Related
- RBApy: Extending resource allocation modeling to eukaryotes in complex environments
- AI-guided discovery for low-resource peptide engineering using evolutionary scale modeling
- TRACE: a framework for traceable biomedical resource construction demonstrated through single-cell glaucoma data
- Bridging the performance-efficiency gap: a resource-efficient hybrid DL-ML framework for jackfruit disease detection.
- Altered stimulus-specific adaptation at the auditory cortex of a mouse model of Fragile X Syndrome
BibTeX
@article{katende2026modeling,
title = {{Modeling resource conflict and inequality in fragile systems: A spatial agent-based framework with a Uganda case study}},
author = {Ronald Katende},
journal = {PLOS One},
year = {2026},
month = sep,
doi = {10.1371/journal.pone.0357283},
url = {https://doi.org/10.1371/journal.pone.0357283},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Modeling resource conflict and inequality in fragile systems: A spatial agent-based framework with a Uganda case study
AU - Ronald Katende
PY - 2026
DA - 2026/09/16
JO - PLOS One
DO - 10.1371/journal.pone.0357283
UR - https://doi.org/10.1371/journal.pone.0357283
AB - 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.
SN - 1932-6203
ER -