{
  "abstract": "Understanding the long-term drivers of settlement location requires disentangling ecological constraints from historically contingent choices. Here I apply a Random Forest machine-learning framework, coupled with explainable AI techniques, to investigate settlement dynamics in Latium vetus (central Italy) from the Early Bronze Age to the early Iron Age (c. 2100–725 BCE). Using 108 securely dated sites and a set of environmentally constrained pseudo-absence points, I model phase-specific patterns and evaluate predictor importance through both normalized split frequencies and SHAP values, capturing structural roles as well as the magnitude and direction of effects. The results reveal a coherent diachronic transformation in the environmental logic of settlement. Early phases are primarily structured by hydrological accessibility, whereas from MBA3 onwards topographic configuration and elevation progressively dominate, marking a shift towards morphologically distinctive and defensible locations. This transition culminates in highly canalised settlement signatures during the Final Bronze Age and RMCA phases, before the RMCAIII phase signals a landscape that is increasingly saturated, hierarchically organised and functionally diversified, despite overall political stability. While the reliance on pseudo-absences and uneven sample sizes constrain predictive robustness, the approach demonstrates the value of Random Forest and SHAP as exploratory tools to expose non-linear, threshold-like relationships and to formalise long-standing archaeological interpretations. The study shows how explainable machine learning can provide a quantitative backbone for reconstructing the emergence, consolidation and transformation of territorially structured landscapes in protohistoric central Italy.",
  "abstract_shown": true,
  "affiliations": [
    "Groningen Institute of Archaeology, University of Groningen, Groningen, Netherlands"
  ],
  "article_type": "Research Article",
  "arxiv": null,
  "author_total": 1,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Luca Alessandri"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/0qk7bxd1ccd4m.bib",
  "cited_by": 1,
  "doi": "10.1371/journal.pone.0357054",
  "fulltext_url": null,
  "id": "0qk7bxd1ccd4m",
  "issns": [
    "1932-6203"
  ],
  "landing_url": "https://doi.org/10.1371/journal.pone.0357054",
  "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",
      "1204|Ancient Mediterranean Archaeology and History"
    ],
    [
      "plos",
      "/Biology and life sciences/Agriculture/Agricultural soil science"
    ],
    [
      "plos",
      "/Earth sciences/Geomorphology/Topography/Landforms/Shores"
    ],
    [
      "plos",
      "/Earth sciences/Hydrology/Surface water"
    ],
    [
      "plos",
      "/Earth sciences/Marine and aquatic sciences/Aquatic environments/Freshwater environments/Fresh water"
    ],
    [
      "plos",
      "/Earth sciences/Marine and aquatic sciences/Aquatic environments/Freshwater environments/Rivers"
    ],
    [
      "plos",
      "/Earth sciences/Marine and aquatic sciences/Aquatic environments/Marine environments/Sea water"
    ],
    [
      "plos",
      "/Earth sciences/Marine and aquatic sciences/Bodies of water/Rivers"
    ],
    [
      "plos",
      "/Earth sciences/Soil science/Agricultural soil science"
    ],
    [
      "plos",
      "/Ecology and environmental sciences/Aquatic environments/Freshwater environments/Fresh water"
    ],
    [
      "plos",
      "/Ecology and environmental sciences/Aquatic environments/Freshwater environments/Rivers"
    ],
    [
      "plos",
      "/Ecology and environmental sciences/Aquatic environments/Marine environments/Sea water"
    ],
    [
      "plos",
      "/Physical sciences/Mathematics/Discrete mathematics/Combinatorics/Permutation"
    ],
    [
      "plos",
      "/Social sciences/Archaeology"
    ]
  ],
  "openalex": "W7131617765",
  "pdf_url": null,
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-16",
  "publisher": "Public Library of Science",
  "ris": "https://research.draconitic.com/paper/0qk7bxd1ccd4m.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:17:49Z",
      "native_id": "10.1371/journal.pone.0357054",
      "source": "plos",
      "url": "https://doi.org/10.1371/journal.pone.0357054"
    }
  ],
  "subjects": [
    {
      "field": "earth",
      "origin": "plos:geomorphology",
      "subfield": "geology-geochemistry"
    },
    {
      "field": "earth",
      "origin": "plos:hydrology",
      "subfield": "hydrology-soils"
    },
    {
      "field": "mathematics",
      "origin": "plos:combinatorics",
      "subfield": "combinatorics"
    }
  ],
  "title": "Tracing settlement dynamics in Latium vetus: Explainable machine learning perspectives from the Bronze to the Early iron age",
  "title_text": "Tracing settlement dynamics in Latium vetus: Explainable machine learning perspectives from the Bronze to the Early iron age",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T12:17:49Z",
  "url": "https://research.draconitic.com/paper/0qk7bxd1ccd4m",
  "venue": "PLOS One",
  "versions": []
}