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Permafrost melting due to climate warming in recent decades has produced significant effects on forest ecosystems, especially the boreal biome at its southernmost limit in Asia. How this warming affects wood formation of trees at intra-annual resolution is unclear, yet is crucial for assessing the impact of permafrost melting on boreal forest growth. In this study, we compared the radial growth and intra-annual wood density fluctuations (IADFs) of Dahurian larch (Larix gmelinii Rupr.) at a permafrost (PF) and a non-permafrost (NPF) site at the southernmost permafrost limit in northeast China and quantified their relationships with climate factors. Drought in early summer was the main factor limiting growth of Dahurian larch. The basal area increment (BAI) of trees at both sites increased initially and then decreased in the 1980s, probably in response to warm-dry climate conditions. Earlywood IADFs (IADF-E) occurred in 14.0% and 9.3% of dated rings at the NPF and PF sites, while the frequency of latewood IADFs (IADF-L) was 6.8% and 2.7% at these two sites. The frequency of IADF-E in trees at both sites was positively and negatively related to June temperatures (and vapor pressure deficit) and precipitation, respectively, suggesting drought stress in June triggered the formation of IADF-E. The IADF-Ls were probably formed in response to warm temperatures in the late growing season. A higher BAI and a lower frequency of IADF-Es of trees at the PF site than at the NPF site indicated that permafrost melting could alleviate drought stress in early summer and promote radial growth of Dahurian larch. This greatly improved forest carbon sequestration and wood quality of some northeastern Asian boreal forests may offset to some extent the adverse effects of warming-drying climates at some sites of northeast Asia. Larch IADF-Es recorded extreme droughts in early summer, giving us a new sight for reconstructing high-frequency extreme climate events. If climate warming continues, the benefits of permafrost melting will gradually disappear and even turn negative due to warmer-dryer climate conditions. Our findings provide valuable information for boreal forest management and conservation under future global warming.

Rapid warming and increasing drought intensity are exposing forest ecosystems to increasing stress, challenging silvicultural decision-making. Tree growth-climate relationships may provide valuable information on tree species’ adaptive potentials. However, it is not clear how subtropical trees will respond to climate change. Here, we present a dendrochronological study on Pinus massoniana and Castanopsis eyrei growing at two elevations (400 m and 890 m) at the northern Luoxiao Mountain in China to reveal their adaptability to climate change. Results show that long-term drought caused by rapid warming and reduced precipitation after 1997 led to a significant (p

Temperate forests in northeast Asia are crucial to maintaining biodiversity conservation and ecological security. Under the background of global warming and drought, it is of great significance to study the special indicator effect of tree growth on climate change. Dendrochronological analysis of different tree species in the same community under climate change can provide valuable information for the adaptive potential of tree species and the species-specific growth indications. Here, we compared the radial growth patterns of 13 co-occurring tree species in a temperate forest community in northeast China. Pearson correlation and moving interval analysis were used to reveal the key climate factors affecting radial growth and the temporal stability of growth-climate relationships, respectively. Results showed that temperature and moisture played a key role in the radial growth of the 13 co-occurring tree species in northeast China. The radial growth of Pinus sylvestris var. mongolica, Picea koraiensis, and Ulmus davidiana increased significantly after rapid warming (around the 1980s), while the radial growth of Pinus koraiensis, Acer mono, and Betula platyphylla decreased slightly. The radial growth of almost all tree species (except P. koraiensis, A. mono, and B. platyphylla) had a positive indication of temperature, especially Juglans mandshurica, Fraxinus mandshurica, and U. davidiana. The precipitation in the early growing season (May to June) and the relative humidity in the growing season were positively correlated with the growth of most species. Coniferous and diffuse-porous tree species were more resistant and recovery to extreme droughts than semi-ring-porous and ring-porous species (except U. davidiana). The 13 co-occurring tree species, especially conifers, showed low resistance and high recovery to extreme temperature. The differences in the growth-climate relationships among different species may be related to wood properties and ecological habits. If the climate continues to warm, coniferous trees will suffer the most serious impact, so they need protection most. Our results highlight that differentiated strategies are needed for the management and restoration of different tree species due to the species-specific indications of climate warming.

Xylem anatomy can provide valuable information about tree allometry and ecophysiological performance. It has unique advantages in the study of global climate change and forest adaptation compared to traditional ring-width or density proxy parameters. Developing appropriate detrended sequences of xylem features is necessary to carry out a series of further studies. However, the differences between detrending methods and their effects for xylem features are still unclear, presenting a challenge to the choice of proper detrending methods. In this study, we used the earlywood vessel features of Fraxinus mandshurica as an example and compared the differences in four common detrending methods (Spline, CSS: cubic smoothing spline, NEP: negative exponential curve, and RCS: regional curve standardization) to highlight the importance of the detrending methods in dendroanatomical studies. The results show that detrending methods significantly affect the long-term growth trends and climate signals recorded in xylem anatomical features. Among them, NEP has good performance in terms of ring width and vessel number, which is not suitable for other vessel features because of its deterministic nature. Spline and CSS are relatively conservative methods, in which are not easy to make mistakes, but the problem of overfitting (lack of climate signals) deserves attention. Multiple RCS may be a promising detrending method with quantitative wood anatomy technology development if sufficient samples are available. Our results highlight the importance of selecting detrending methods for xylem feature identification and emphasize the importance of testing various detrending methods rather than arbitrarily choosing a standard method. The detrending method should be selected based on the purpose, such as the balance between climate signals and thorough detrended effects. We recommend applying multiple methods to test the growth trends in xylem features before selecting a detrending method. More interdisciplinary studies involving ecophysiology, wood anatomy, and dendrochronology will help to distil the valuable information in xylem features accurately.

Next-generation sequencing (NGS) has drastically enhanced human cancer research, but diverse sequencing strategies, complicated open-source software, and the identification of massive numbers of mutations have limited the clinical application of NGS. Here, we first presented GPyFlow, a lightweight tool that flexibly customizes, executes, and shares workflows. We then introduced DIVIS, a customizable pipeline based on GPyFlow that integrates read preprocessing, alignment, variant detection, and annotation of whole-genome sequencing, whole-exome sequencing, and gene-panel sequencing. By default, DIVIS screens variants from multiple callers and generates a standard variant-detection format list containing caller evidence for each sample, which is compatible with advanced analyses. Lastly, DIVIS generates a statistical report, including command lines, parameters, quality-control indicators, and mutation summary. DIVIS substantially facilitates complex cancer genome sequencing analyses by means of a single powerful and easy-to-use command. The DIVIS code is freely available at https://github.com/niu-lab/DIVIS, and the docker image can be downloaded from https://hub.docker.com/repository/docker/sunshinerain/divis.

Automatic recognition of arrhythmias is particularly important in the diagnosis of heart diseases. This study presents an electrocardiogram (ECG) recognition system based on multi-domain feature extraction to classify ECG beats. An improved wavelet threshold method for ECG signal pre-processing is applied to remove noise interference. A novel multi-domain feature extraction method is proposed; this method employs kernel-independent component analysis in nonlinear feature extraction and uses discrete wavelet transform to extract frequency domain features. The proposed system utilises a support vector machine classifier optimized with a genetic algorithm to recognize different types of heartbeats. An ECG acquisition experimental platform, in which ECG beats are collected as ECG data for classification, is constructed to demonstrate the effectiveness of the system in ECG beat classification. The presented system, when applied to the MIT-BIH arrhythmia database, achieves a high classification accuracy of 98.8%. Experimental results based on the ECG acquisition experimental platform show that the system obtains a satisfactory classification accuracy of 97.3% and is able to classify ECG beats efficiently for the automatic identification of cardiac arrhythmias.