Understanding Late Pleistocene human land preference using ecological niche models in an Australasian test case

Alexandra J. Zachwieja, Anne Marie Bacon, Thi Mai Huong Nguyen, Anh Tuan Nguyen, Kira Westaway, Philippe Duringer, Jean Luc Ponche, Élise Patole-Edoumba, Phonephanh Sichanthongtip, Thongsa Sayavongkhamdy, Tyler E. Dunn, Fabrice Demeter, Laura L. Shackelford

Research output: Contribution to journalArticlepeer-review

Abstract

Ecological niche models (ENM) of species distributions and dispersal patterns are well established in the biological sciences. Their use in paleoanthropological reconstructions of hominin niches is relatively recent, successfully focusing on out of Africa dispersals and human land preference in Europe and Central Asia. These studies have suggested that some of the most important variables for predicting human site use in these regions are moderate annual temperature and rainfall. Here, we used ENM to combine these long-used abiotic predictors of human land preference with landform data (slope) and one potentially important biotic variable (human-carnivore competition quantified using a competition index) in an Australasian test case. We constructed ENMs in the program Maxent to investigate the impact of these abiotic and biotic variables on human land preference patterns in Late Pleistocene Australasia. Though calculated competition across test sites was high, models including this biotic data produced ill-fitting localized models (AUC = 0.695) that relied on mean annual temperature. Large-scale models including solely temperature and rainfall fit well (AUC = 0.84) but are poor predictors of land preference compared to models including slope in this mountainous region (AUC = 0.924) showcasing a discrepancy between accuracy and precision in abiotic models. While the biotic data included in these models was considered unimportant to predictions of human land preference, the inclusion of additional landform data in temperate ENMs should be pursued given the importance of slope as a predictor in large-scale models.

Original languageEnglish (US)
Pages (from-to)13-28
Number of pages16
JournalQuaternary International
Volume563
DOIs
StatePublished - Oct 20 2020

Bibliographical note

Funding Information:
This work was fundamentally collaborative and could not have been completed without the generosity of researchers in promoting open climate data, as well as researchers and institutions whose collaboration was integral for competition index data collection. Tremendous thanks to those institutions and persons whose permissions and assistance made data collection possible, specifically at the Lao Ministry of Information, Culture, and Tourism and the Vietnamese Institute of Archaeology. Special thanks to Becky Vandewalle for assistance with GIS structure, data formatting, and guiding me through ArcMap. This work and these questions could not have been possible without the generous data sharing of the many researchers whose climate data made these analyses possible. Funding for this work was provided by: University of Illinois at Urbana-Champaign (UIUC) Anthropology Department, UIUC Graduate College , The Explorer's Club Exploration Fund, and the UIUC Beckman Institute CS/AI Award.

Funding Information:
This work was fundamentally collaborative and could not have been completed without the generosity of researchers in promoting open climate data, as well as researchers and institutions whose collaboration was integral for competition index data collection. Tremendous thanks to those institutions and persons whose permissions and assistance made data collection possible, specifically at the Lao Ministry of Information, Culture, and Tourism and the Vietnamese Institute of Archaeology. Special thanks to Becky Vandewalle for assistance with GIS structure, data formatting, and guiding me through ArcMap. This work and these questions could not have been possible without the generous data sharing of the many researchers whose climate data made these analyses possible. Funding for this work was provided by: University of Illinois at Urbana-Champaign (UIUC) Anthropology Department, UIUC Graduate College, The Explorer's Club Exploration Fund, and the UIUC Beckman Institute CS/AI Award.

Publisher Copyright:
© 2020 Elsevier Ltd and INQUA

Keywords

  • Competition
  • Ecological niche modeling
  • Human land preference
  • Late pleistocene
  • Southeast Asia

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