The patchwork loess of Central Asia: Implications for interpreting aeolian dynamics and past climate circulation in piedmont regions

0566952 - GLÚ 2024 RIV GB eng J - Článek v odborném periodiku
Dave, A. K. - Lisá, Lenka - Scardia, G. - Nigmatova, S. - Fitzsimmons, K. E.
The patchwork loess of Central Asia: Implications for interpreting aeolian dynamics and past climate circulation in piedmont regions.
Journal of Quaternary Science. Roč. 38, č. 4 (2023), s. 526-543. ISSN 0267-8179. E-ISSN 1099-1417
Institucionální podpora: RVO:67985831
Klíčová slova: Central Asia * Chinese Loess Plateau * loess * luminescence dating * mass accumulation rates
Obor OECD: Climatic research
Impakt faktor: 2.3, rok: 2022
Způsob publikování: Open access
https://onlinelibrary.wiley.com/doi/epdf/10.1002/jqs.3493

Reconstruction of mass accumulation rates (MARs) in loess deposits are widely used for interpreting long‐term aeolian transport and climate dynamics in terrestrial environments. However, these interpretations are often driven by a preponderance of reconstructions from individual or selected sites, which can bias our understanding of past climate, especially in the absence of other proxy information. Recent studies on MARs from multiple loess sites in Arid Central Asia (ACA) reveal disparities in the timing of peaks in accumulation between sites, as well as asynchronies with loess flux in the Chinese Loess Plateau (CLP). We investigate this issue by (1) dating five new sites from the western Ili Basin, therefore extending the spatial cover of loess chronologies across ACA and (2) combining that with MARs from >30 sites across ACA and the CLP over the last 60 ka. Our results indicate spatiotemporal inhomogeneity in the timing and rate of loess deposition across the ACA, and highlight the importance of interrogating local and regional influences on dust supply and transport. Our synthesis of MARs from ACA and the CLP suggests that the timing of peak dust flux as an indicator of large‐scale climate dynamics is best derived from an aggregate of sites, this removes site‐specific bias where local processes or topographic settings outweigh the climate signature.
Trvalý link: https://hdl.handle.net/11104/0342745