Back to Search Start Over

Finding karstic caves and rockshelters in the Inner Asian mountain corridor using predictive modelling and field survey.

Authors :
Patrick Cuthbertson
Tobias Ullmann
Christian Büdel
Aristeidis Varis
Abay Namen
Reimar Seltmann
Denné Reed
Zhaken Taimagambetov
Radu Iovita
Source :
PLoS ONE, Vol 16, Iss 1, p e0245170 (2021)
Publication Year :
2021
Publisher :
Public Library of Science (PLoS), 2021.

Abstract

The area of the Inner Asian Mountain Corridor (IAMC) follows the foothills and piedmont zones around the northern limits of Asia's interior mountains, connecting two important areas for human evolution: the Fergana valley and the Siberian Altai. Prior research has suggested the IAMC may have provided an area of connected refugia from harsh climates during the Pleistocene. To date, this region contains very few secure, dateable Pleistocene sites, but its widely available carbonate units present an opportunity for discovering cave sites, which generally preserve longer sequences and organic remains. Here we present two models for predicting karstic cave and rockshelter features in the Kazakh portion of the IAMC. The 2018 model used a combination of lithological data and unsupervised landform classification, while the 2019 model used feature locations from the results of our 2017-2018 field surveys in a supervised classification using a minimum-distance classifier and morphometric features derived from the ASTER digital elevation model (DEM). We present the results of two seasons of survey using two iterations of the karstic cave models (2018 and 2019), and evaluate their performance during survey. In total, we identified 105 cave and rockshelter features from 2017-2019. We conclude that this model-led approach significantly reduces the target area for foot survey.

Subjects

Subjects :
Medicine
Science

Details

Language :
English
ISSN :
19326203
Volume :
16
Issue :
1
Database :
Directory of Open Access Journals
Journal :
PLoS ONE
Publication Type :
Academic Journal
Accession number :
edsdoj.97401faaf55b4ef08262ba3f9e232bc6
Document Type :
article
Full Text :
https://doi.org/10.1371/journal.pone.0245170