Although climate change has convincingly been linked to the evolution of human civilization on different temporal scales, its role in influencing the spatial patterns of ancient civilizations has rarely been investigated. The northward shift of the ancient Silk Road (SR) route from the Tarim Basin (TB) to the Junggar Basin during -420-850 CE provides the opportunity to investigate the relationship between climate change and the spatial evolution of human societies. Here, we use a new high-resolution chironomidbased temperature reconstruction from arid China, combined with hydroclimatic and historical datasets, to assess the possible effects of climate fluctuations on the shift of the ancient SR route. We found that a cooling/drying climate in the TB triggered the SR route shift during -420-600 CE. However, a warming/ wetting climate during -600-850 CE did not inhibit this shift, but instead promoted it, because of the favorable climate-induced geopolitical conflicts between the Tubo Kingdom and the Tang Dynasty in the TB. Our findings reveal two distinct ways in which climate change drove the spatial evolution of human civilization, and they demonstrate the flexibility of societal responses to climate change. (c) 2024 Science China Press. Published by Elsevier B.V. and Science China Press. All rights reserved.

The long-term and continuous permafrost temperature data is of great significance to the study of permafrost, climate, ecology, hydrology and engineering on the Qinghai-Tibet Plateau (QTP), but the available observed data sequence is no longer than 25 years. To address the gap, we first attempt to reconstruct the sequences of permafrost temperature at three monitoring sites including Xidatan, Wudaoliang and Tanggula along the QTP engineering corridor from 1920 to 2019, based on one of the most used permafrost models worldwide (i.e., Geophysical Institute Permafrost Lab version 2 (GIPL2)). The GIPL2 model and its parameterized schemes were first evaluated and calibrated using the ground temperature observations at the three sites. The monthly near surface ground temperature at the depth of 5 cm after calibration and correction based on monitoring data was used as forcing dataset to simulate the temperature change of the permafrost from 1900 to 2019. The temperature change sequences since 1920 were selected to discuss the changes of permafrost on the QTP, and its responses to climate change. Results showed that (i) the GIPL2 model can well simulate the thermal state of permafrost on the QTP with low simulation errors (below 0.1 degrees C) at the depth of zero annual amplitude; (ii) the annual average ground temperature at different depths for all three sites experienced warming trends from 1920 to 2019, in which the average warming rate was 0.07 degrees C/10 a (0.05-0.09) at the depth of zero annual amplitude (15 m). Besides, the site with the largest warming rate at the shallow layer (3 m) was found in Wudaoliang, while the deep layer (30 m) was in Xidatan; (iii) the permafrost temperature at the shallow layer increased rapidly since 1980. Nevertheless, the response times of the thermal conditions to climate change varied with soil layers, among which the deep layer lagged by about 20 years compared to the shallow layer; (iv) permafrost thicknesses for the Xidatan, Wudaoliang and Tanggula sites were decreased by 13.9 m, 4.6 m and 4.7 m respectively. The average deepening rate of the permafrost table and rising rates of permafrost base for the three sites were 0.6 cm/a and 10.27 cm/a, respectively. More specifically, the deepening rate of the permafrost table was 0.5 cm/a for Xidatan, 0.6 cm/a for Wudaoliang and 0.7 cm/a for Tanggula, and the rising rate of the permafrost base was 13.4 cm/a for Xidatan and 4.0 cm/a for both Wudaoliang and Tanggula. Compared with that in Wudaoliang and Tanggula, the permafrost in Xidatan was relatively unstable and its response to climate change was more sensitive. Although the simulations of the GIPL2 model could be impacted by the accuracy of the forcing data (e.g., 5 cm ground temperature), the reconstructed permafrost temperature changes from 1920 to 2019 were consistent with the observations over the past 40 years. Besides, our results also confirmed the continuous warming phenomenon of permafrost on the QTP since 1920. These findings can well fill the narrow gap relating to the short sequence and discontinuity of the permafrost temperature dataset on the QTP, and provide a baseline of permafrost changes to the scientific community for a better understanding of the changes in the cryosphere, ecosystem, water resources, and even climate. Nevertheless, some limitations in temperature reconstruction and model processing were noted. In the future, multiple aspects including accurate forcing data and complex factors (e.g., heat convection and lateral heat flow exchange) should be considered comprehensively in the model to reduce the uncertainties of ground temperature simulations.

The annual mean temperature on the Tibetan Plateau (TP) has strongly increased over the past few decades, with larger warming in winter than in summer. Whether this different amplitude of change between seasons has persisted over longer time-scales in the past remains poorly understood, limiting our understanding of the mechanisms responsible. Here, we apply multivariate regression analysis and ensemble empirical mode decomposition (EEMD) to decompose winter (T-DJF) and summer (T-JJA) temperature reconstructions over the 1718-2005 CE period for the southeastern TP to investigate similarities and differences between winter and summer temperature changes, over multiple time-scales, as well as the driving factors behind the seasonal differences. The results reveal that the T-DJF and T-JJA reconstructions were significantly correlated throughout the study period, with the magnitude of the T-DJF variations approximately six times greater than the T-JJA variations. When the two reconstructions were decomposed over multiple time-scales, it was found that the consistency between winter and summer temperature reconstructions only existed at inter-annual scale. Assessing the driving factors, the main contributions to the T-JJA and T-DJF changes at the inter-annual and inter-decadal scales appear to be mainly the El Nino-Southern Oscillation (ENSO). The Pacific Decadal Oscillation (PDO) contribution was important to T-JJA and T-DJF changes at multi-decadal scales. Furthermore, we found that orbital parameters and the Atlantic Multidecadal Oscillation (AMO) was a major contributor to the changes in T-JJA and T-DJF at centennial scales, respectively. Both the T-JJA and T-DJF have a significant long-term increasing trend since c. 1850, mainly attributed to anthropogenic forcing. The detected similarities and differences between T-DJF and T-JJA at multiple time-scales provide new perspectives on the understanding the mechanisms behind climate change on the Tibetan Plateau and even entire East Asia.

Aim We aim to use species attributes such as distributions and indicator values to reconstruct past biomes, environment, and temperatures from detailed plant-macrofossil data covering the late glacial to the early Holocene (ca. 14-9 ka). Location Krakenes, western Norway. Methods We applied attributes for present-day geographical distribution, optimal July and January temperatures, and Ellenberg indicator values for plants in the macrofossil data-set. We used assemblage weighted means (AWM) to reconstruct past biomes, changes in light (L), nitrogen (N), moisture (F), and soil reaction (R), and temperatures. We compared the temperature reconstructions with previous chironomid-inferred temperatures. Results After the start of the Holocene around 11.5 ka, the Arctic-montane biome, which was stable during the late-glacial period, shifted successively into the Boreo-arctic montane, Wide-boreal, Boreo-montane, Boreo-temperate, and Wide-temperate biomes by ca. 9.0 ka. Circumpolar and Eurasian floristic elements characteristic of the late-glacial decreased and the Eurosiberian element became prominent. Light demand (L), soil moisture (F), nitrogen (N), and soil reaction (R) show different, but complementary responses. Light-demanding plants decreased with time. Soil moisture was relatively stable until it increased during organic soil development during the early Holocene. Soil nitrogen increased during the early Holocene. Soil reaction (pH) decreased during the Allerod, but increased during the Younger Dryas. It decreased markedly after the start of the Holocene, reaching low but stable levels in the early Holocene. Mean July and January temperatures show similar patterns to the chironomid-inferred mean July temperature trends at Krakenes, but chironomids show larger fluctuations and interesting differences in timing. Conclusion Assigning attributes to macrofossil species is a useful new approach in palaeoecology. It can demonstrate changes in biomes, ecological conditions, and temperatures. The late-glacial to early-Holocene transition may form an analogue for changes observed in the modern arctic and in mountains, with melting glaciers, permafrost thaw, and shrub encroachment into tundra.