Search

Characterized as a climatologically sensitive region, the southeastern Tibetan Plateau (STP) is an ideal location for dendrochronological research. Here, five tree-ring width (TRW) chronologies were developed: three for Picea likiangensis along altitudinal gradients from 3600 to 4400 m a.s.l. and two for Sabina saltuaria and Abies squamata from 4200 m a.s.l. Significant differences in the growth rates and age composition of Picea likiangensis were observed at various elevation gradients. The chronology statistics (mean sensitivity, etc.) fluctuated with the elevation gradient. Picea likiangensis showed distinct growth patterns in response to climatic variability along the altitude gradient: the minimum temperature influenced tree growth at lower and middle altitudes, while higher altitudes were affected by precipitation. The radial growth of different tree species growing in the same region is controlled by the same climatic factors. Sabina saltuaria and Abies squamata exhibited similar growth responses to Picea likiangensis. Stand conditions (wind speeds, slope, and elevation) and biotic factors (the depth of root, forest type, tree age, and sensitivity) can partially explain why the ring width–climate relationships change with altitude. [ABSTRACT FROM AUTHOR]

Terrestrial auroras are highly structured that visualize the perturbations of energetic particles and electromagnetic fields in Earth's space environments. However, the identification of auroral morphologies is often subjective, which results in confusion in the community. Automated tools are highly valuable in the classification of auroral structures. Both CNNs (convolutional neural networks) and transformer models based on the self-attention mechanism in deep learning are capable of extracting features from images. In this study, we applied multiple algorithms in the classification of auroral structures and performed a comparison on their performances. Trans-former and ConvNeXt models were firstly used in the analysis of auroras in this study. The results show that the ConvNeXt model can have the highest accuracy of 98.5% among all of the applied algorithms. This study provides a direct comparison of deep learning tools on the application of classifying auroral structures and shows promising capability, clearly demonstrating that auto-mated tools can help to minimize the bias in future auroral studies. [ABSTRACT FROM AUTHOR]

According to previous studies, the Lixiahe area in the east of the Jianghuai River was an alternate environment of land and sea in the middle Holocene, and it was not until the late Holocene that the eastern Jianghuai completely became a terrestrial environment. However, recent archaeological studies have found that the extensive Neolithic sites in the Lixiahe area have recorded the rich human activities and cultural connotations of the prehistoric civilization in the Middle Holocene. In this paper, the Gangxi section of Jianhu Lake, Jiangsu Province (GX2) was selected and pollen analysis was fulfilled, then the geomorphic evolution process of the study area from sea to land was investigated according to the palynological assemblages and algae fossils of brackish water, semi-saline water, fresh water and terrestrial in the section strata. During the period of 8500–3800 cal. BP, GX2 was affected by multiple factors such as sea surface fluctuation, ocean flow and sediment deposition carried by seagoing rivers. Since 5800 cal. BP, the area east of the Grand Canal between the Yangtze River and the Huaihe River, and the west of the Yangzhai town, Funing–Longgang town, Yancheng–Dagang town and Yancheng–west of the Dongtai–Hai'an line, have become a terrestrial environment. After the eastern Jianghuai became a land, the Liangzhu culture (5300–4300 cal. BP) in the Taihu Lake basin in the south wing of the Yangtze River delta expanded to the eastern Jianghuai area, and the Longshan culture and Yueshi culture in the Haidai area in the north also migrated south to the eastern Jianghuai area. Admittedly, the main reason in the process of Neolithic cultural development is the internal motivation that the ancient ancestors struggled with nature and pushed forward the continuous development of civilizations. However, our study explains the palaeogeographical origin of Neolithic culture in the eastern and coastal areas of Jianghuai in the middle Holocene, and meanwhile, provides an example for the man–land relationship research on Neolithic culture. [ABSTRACT FROM AUTHOR]

Dendroclimatology and dendroecology have entered mainstream dendrochronology research in subtropical and tropical areas. Our study focused on the use of the chronology series of Masson pine (Pinus massoniana Lamb.), the most widely distributed tree species in the subtropical wet monsoon climate regions in China, to understand the tree growth response to ecological and hydroclimatic variability. The boosted regression trees (BRT) model, a nonlinear machine learning method, was used to explore the complex relationship between tree-ring growth and climate factors on a larger spatial scale. The common pattern of an asymptotic growth response to the climate indicated that the climate-growth relationship may be linear until a certain threshold. Once beyond this threshold, tree growth will be insensitive to some climate factors, after which a nonlinear relationship may occur. Spring and autumn climate factors are important controls of tree growth in most study areas. General circulation model (GCM) projections of future climates suggest that warming climates, especially temperatures in excess of those of the optimum growth threshold (as estimated by BRT), will be particularly threatening to the adaptation of Masson pine. [ABSTRACT FROM AUTHOR]