Comparison of boosted regression trees vs WA-PLS regression on diatom-inferred glacial-interglacial climate reconstruction in Lake Tiancai (southwest China)

Abstract

Quantitative paleoclimate reconstructions based on biological fossils over glacial-interglacial timescales are a major source of information on long-term climate variability. However, such reconstructions can present major methodological challenges, as calibration methods based on modern climatic and biological patterns may yield biased results, especially when data are particularly sensitive to the influence of secondary environmental variables in the training set or fossil assemblage. A machine-learning technique, boosted regression tree (BRT), is compared with a weighted averaging-partial least squares (WA-PLS) regression in a diatom-based summer (mean July) temperature transfer function with a calibration set of 273 samples collected from China. Using these calibration methods and a fossil diatom sequence from Lake Tiancai (southwest China; 3898 m a.s.l.), the summer temperatures covering the last glaciation and entire Holocene (18000 cal yr BP to present) are reconstructed. The record is validated by applying several statistical reconstruction diagnostics and compared with pollen and diatom records from the same sediment core. The results suggest that the BRT-based calibration model, which produced a coefficient of determination (r2 = 0.85) and root-mean-square error of prediction (RMSEP = 1.65 °C) offers substantial improvements over WA-PLS. The record shows that the summer temperature varies by ~2.5 °C across the entire period. The temperature evolution inferred by diatom-based BRT model is characterized by an early cool phase (with a MJT of 9.3 °C) prior to 10000 cal yr BP, followed by a clear mid-Holocene thermal maximum (~1.1 °C above the present-day temperature) from 6000 to 3500 cal yr BP and a subsequent cooling that ended at 1500 cal yr BP. This contrasts with the chironomid-based temperature transfer function in the same sequence showing a warmer period between 8500 and 6000 cal yr BP. The overall pattern of diatom-based summer temperature reconstructions broadly matches the climate change inferred from pollen records from Tiancai Lake and other records from the surrounding regions, suggesting that summer temperatures respond to insolation forcing and the variability of the southwest monsoon. We argue that the BRT-based climate model potentially outperforms the other models in southwest China when using a large and non-linear calibration set of diatoms for reconstructing long-term temperature.