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Developing effective climate mitigation strategies under global warming requires a comprehensive understanding of the biophysical mechanism of how afforestation affects the climate and environment. The planted forests in southern China are an essential carbon sink. However, the impacts of radiative and non‐radiative processes on land surface temperature caused by converting open land (i.e., grassland and cropland) and natural forests to planted forests remain unclear. We used satellite observations and intrinsic biophysical mechanism theory‐based energy balance models to estimate the biophysical impacts of potential afforestation of open land and natural forests on surface temperature from 2000 to 2010 in Guangdong Province, southern China. Results showed that afforestation of open land had a consistent net cooling effect. Due to the afforestation of natural forests, the modeled results revealed that afforestation among all conversion types had a net warming effect of 0.15 ± 0.5 K, which caused by the change in energy redistribution factor although uncertainty remains. While the most significant warming caused by converting natural forest to planted forests was also slightly affected by albedo. The afforestation's non‐radiative and radiative processes led to a slight warming of 0.143 ± 0.43 K and a cooling of −0.096 ± 0.19 K, respectively. The non‐radiative process dominates the effect of afforestation on the surface temperature, with the overall non‐radiative forcing index greater than 73% ± 0.59%. Our study highlights the need of protecting natural forests and provides a practical method for assessing the impacts of afforestation on the local climate and the effectiveness of climate mitigation efforts. Plain Language Summary: Afforestation is an important tool for mitigating climate change. However, the land cover change induced by afforestation may affect the land‐atmosphere balance of water and energy. Accurate estimation of surface temperature change in response to afforestation‐induced surface energy change is challenging. From 2000 to 2010, afforestation activities in southern China were frequent, resulting in a significant increase in carbon sinks. Yet, how these land‐use changes can affect the local climate is unclear. Here we prepared the high‐resolution land cover data and utilized satellite observations and a physical‐based method to estimate the impacts of afforestation on land surface temperature in southern China. This strategy can provide insights for designing rational afforestation policies in southern China and similar geographic areas. Key Points: The modeled land surface temperature due to afforestation had a net warming effectThe non‐radiative process mainly drives the effect of afforestation on local surface temperatureThe detailed distribution of afforestation and a precise energy balance model allow accurate evaluation of the temperature response [ABSTRACT FROM AUTHOR]

Treatment of malignant tumors encompasses multidisciplinary comprehensive diagnosis and treatment and reasonable combination and arrangement of multidisciplinary treatment, which is not a simple superimposition of multiple treatment methods, but a comprehensive consideration of the characteristics and specific conditions of the patients and the tumor. The mechanism of tumor elimination by restoring the body's immune ability is consistent with the concept of "nourishing positive accumulation and eliminating cancer by itself" in traditional Chinese medicine (TCM). The formation and dynamic changes in the tumor microenvironment (TME) involve many different types of cells and multiple signaling pathways. Those changes are similar to the multitarget and bidirectional regulation of immunity by TCM. Discussing the relationship and mutual influence of TCM and antitumor therapy on the TME is a current research hotspot. TCM has been applied in the treatment of more than 70% of cancer patients in China. Data have shown that TCM can significantly enhance the sensitivity to chemotherapeutic drugs, enhance tumor-suppressing effects, and significantly improve cancer-related fatigue, bone marrow suppression, and other adverse reactions. TCM treatments include the application of Chinese medicine monomers, extracts, classic traditional compound prescriptions, listed compound drugs, self-made compound prescriptions, as well as acupuncture and moxibustion. Studies have shown that the TCM functional mechanism related to the positive regulation of cytotoxic T cells, natural killer cells, dendritic cells, and interleukin-12, while negatively regulating of regulatory T cells, tumor-associated macrophages, myeloid-derived suppressive cells, PD-1/PD-L1, and other immune regulatory factors. However, the application of TCM in cancer therapy needs further study and confirmation. This article summarizes the existing research on the molecular mechanism of TCM regulation of the TME and provides a theoretical basis for further screening of the predominant population. Moreover, it predicts the effects of the combination of TCM and antitumor therapy and proposes further developments in clinical practice to optimize the combined strategy. [ABSTRACT FROM AUTHOR]

Key message: By integrating vegetation change tracker (VCT), spatial analysis (SA), and random forest regression (RF), the spectral-temporal patterns of forest stand age were mapped for three typical plantations in Southern China. The spectral-temporal distribution of age structure indicated that the plantation stands in the study area were increasingly aging. Context: Plantations play a major role in China for ecosystem restoration and carbon sequestration. Mapping plantation stand age distributions is essential for developing sustainable plantation forest management plans. Aims: The purpose of this study was to propose two new remote sensing based models for mapping plantation ages and to test the model feasibility and accuracy in determining the spectral-temporal patterns of forest ages. Methods: We first integrated vegetation change tracker (VCT) algorithm and spatial analysis (VCT-SA) for the pixels that were disturbed at least once from 1987 to 2017, and integrated VCT and random forest (VCT-RF) for the pixels were not disturbed during the study period. Then the forest age of these two parts were merged separately to generate annual forest age. Results: The spectral-temporal (30-m resolution, from 1987 to 2017) of forest age for the three typical plantations in Lishui were generated. The results indicated that the plantation stands in our large study area were increasingly aging. Conclusion: Our results revealed that it is reasonable to derive the distribution of plantation stand ages from combined remote sensing models. Besides, we confirmed that the stand ages of the plantations in our large study area of Lishui City are on the rise as the result of forest protection policies. [ABSTRACT FROM AUTHOR]

• An IEU-Net model and high-resolution images are reliable for urban forest mapping. • Afforestation and deforestation exerted a net cooling and warming. • Two landscape-type conversions displayed greater cooling and weaker warming. • A robust and accurate land surface temperature feedback framework was proposed. Accurate characterization of urban forest change can help quantify its impact on the urban thermal environment. Taking Hangzhou City and Zhaoqing City, China as two cases, we proposed a deep learning-based approach to extract forest/non-forest types using China's Gaofen data and the labels it generates. We then explored the impacts of urban forest patterns on land surface temperature (LST). Our results indicate that Gaofen-1/6 images performed well for urban forest/non-forest mapping with an accuracy of over 90%. We found that afforestation and deforestation exerted a net cooling of -0.62±0.30°C and -1.23±0.26°C and warming of 1.71±0.16°C and 1.29±0.14°C in Hangzhou and Zhaoqing, respectively. Balancing the LST changes of both afforestation and deforestation found total warming due to deforestation, especially in Hangzhou. Latitudinal reduced cooling and enhanced warming were found from Zhaoqing to Hangzhou, which can be explained by strong evaporative effects and inconsistent albedo effects. Moreover, a more pronounced cooling when other types converted to landscape core type and a weaker warming when landscape core type converted to other types were detected, especially in Zhaoqing. This study highlights the importance of designing rational afforestation plans, avoiding deforestation activities, and reducing forest fragmentation in delineating effective climate mitigation strategies. [ABSTRACT FROM AUTHOR]

Many post-fire on-site factors, including fire severity, management strategies, topography, and local climate, are concerns for forest managers and recovery ecologists to formulate forest vegetation recovery plans in response to climate change. We used the Vegetation Change Tracker (VCT) algorithm to map forest disturbance in the Daxing'anling area, Northeastern China, from 1987 to 2016. A support vector machine (SVM) classifier and historical fire records were used to separate burned patches from disturbance patches obtained from VCT. Afterward, stepwise multiple linear regression (SMLR), SVM, and random forest (RF) were applied to assess the statistical relationships between vegetation recovery characteristics and various influential factors. The results indicated that the forest disturbance events obtained from VCT had high spatial accuracy, ranging from 70% to 86% for most years. The overall accuracy of the annual fire patches extracted from the proposed VCT-SVM algorithm was over 92%. The modeling accuracy of post-fire vegetation recovery was excellent, and the validation results confirmed that the RF algorithm provided better prediction accuracy than SVM and SMLR. In conclusion, topographic variables (e.g., elevation) and meteorological variables (e.g., the post-fire annual precipitation in the second year, the post-fire average relative humidity in the fifth year, and the post-fire extreme maximum temperature in the third year) jointly affect vegetation recovery in this cold temperate continental monsoon climate region. [ABSTRACT FROM AUTHOR]

Background: Aboveground biomass (AGB) is a fundamental indicator of forest ecosystem productivity and health and hence plays an essential role in evaluating forest carbon reserves and supporting the development of targeted forest management plans. Methods: Here, we proposed a random forest/co-kriging framework that integrates the strengths of machine learning and geostatistical approaches to improve the mapping accuracies of AGB in northern Guangdong Province of China. We used Landsat time-series observations, Advanced Land Observing Satellite (ALOS) Phased Array L-band Synthetic Aperture Radar (PALSAR) data, and National Forest Inventory (NFI) plot measurements, to generate the forest AGB maps at three time points (1992, 2002 and 2010) showing the spatio-temporal dynamics of AGB in the subtropical forests in Guangdong, China. Results: The proposed model was capable of mapping forest AGB using spectral, textural, topographical variables and the radar backscatter coefficients in an effective and reliable manner. The root mean square error of the plot-level AGB validation was between 15.62 and 53.78 t∙ha− 1, the mean absolute error ranged from 6.54 to 32.32 t∙ha− 1, the bias ranged from − 2.14 to 1.07 t∙ha− 1, and the relative improvement over the random forest algorithm was between 3.8% and 17.7%. The largest coefficient of determination (0.81) and the smallest mean absolute error (6.54 t∙ha− 1) were observed in the 1992 AGB map. The spectral saturation effect was minimized by adding the PALSAR data to the modeling variable set in 2010. By adding elevation as a covariable, the co-kriging outperformed the ordinary kriging method for the prediction of the AGB residuals, because co-kriging resulted in better interpolation results in the valleys and plains of the study area. Conclusions: Validation of the three AGB maps with an independent dataset indicated that the random forest/co-kriging performed best for AGB prediction, followed by random forest coupled with ordinary kriging (random forest/ordinary kriging), and the random forest model. The proposed random forest/co-kriging framework provides an accurate and reliable method for AGB mapping in subtropical forest regions with complex topography. The resulting AGB maps are suitable for the targeted development of forest management actions to promote carbon sequestration and sustainable forest management in the context of climate change. [ABSTRACT FROM AUTHOR]

Long-term surface mining and subsequent vegetation recovery greatly alter land cover types, reshape landscape patterns and impose several impacts on local ecosystem services. However, studies on the history of forest changes in mining areas from the 1960s to the present have not been reported. This study developed a new idea to investigate the spatial and temporal dynamics of forest cover in a mining area of Mufu Mountain (Mt. Mufu) from 1967 to 2019 by integrating Landsat and Corona data, and to explore the relationships among the forest changes, landscape structures and ecosystem functions. Firstly, we applied the vegetation change tracker (VCT) algorithm and visual interpretation to create annual forest change datasets. Subsequently, the forest loss process was divided into subdivision, shrinkage, perforation and attrition components. An improved forest restoration model in this study extended the recovery process to bridge, branch, infilling and increment components. Finally, remote sensing variables and crown density were coupled to assess the forest aboveground biomass (AGB) to reflect the ecosystem function in the restoration area. Results showed that the combined use of Corona and the dense time series of Landsat can provide more detailed information on forest changes. Forest cover sharply decreased from 343.89 in 1967 to 298.44 ha in 1990, and after 2003, the forest area substantially increased and finally reached a maximum of 434.16 ha in 2019. Subdivision and bridge not only occupied the larger areas in the process of forest loss and restoration, but also they had strong correlations with forest changes and the Pearson correlation coefficients (r) were respectively 0.96 and 0.91. These all revealed that forest changes mainly affected landscape structure connectivity. The total forest AGB of Mt. Mufu increased from 20,173.35 in 2006 to 31,035.77 t in 2017, but the increases in AGB were only 30-40 t/ha in most recovery areas with high structure connectivity (bridge regions), indicating there is room for improving restoration projects in the future. The obtained findings can provide mining site restoration managers with clear, long-term forest change information and mine restoration assessment methods. [ABSTRACT FROM AUTHOR]

• Change of afforested area led to a cooling effect, especially from croplands. • Afforestation in northern Guangdong has a warming effect, especially from natural forests. • An increase in cooling for the tropical forest zone across latitudes was observed. • ET dominated the cooling during the wet and warm season. • Enhanced precipitation influenced the ET-induced cooling. Estimating the effects of large scale afforestation is essential for the accurate understanding of its potential for the mitigation of climate warming. We used satellite observations to quantify the effects of the conversion of open lands (i.e., grassland and cropland) and natural forests to plantation forests and their associated biophysical processes (i.e., albedo and evapotranspiration (ET)) on land surface temperature (LST) in Guangdong Province, China. The hypothetical change (mean 2002–2018 values of LST difference between plantation forests and nearby lands in 2010) using the moving window searching-based method and actual change (changes of afforested area affecting the LST difference from 2000 to 2010) using the spatial pattern change trend method were detected in order to characterize the spatiotemporal variations in surface temperature, related albedo, and ET. The relationships between albedo, ET, and surface temperature change were also determined in combination with interpolated air temperature and precipitation. Results showed that the two methods-based afforestation changes had a similar net cooling effect, but a discrepancy in diurnal, seasonal, and spatial variations occurred. Overall, the actual change of afforested area led to a cooling effect by an average of −0.18 ± 0.02 °C, especially from croplands, which was greater than the air temperature. Individually, afforestation in the mid-subtropical forest zone (north of 24 °N, northern Guangdong) had a warming effect, especially during the transition from natural forests to plantation forests. We also observed an increase in cooling for the tropical forest zone across latitudes. Warming during the dry season was triggered by the albedo from plantation forests, but the albedo-induced forest cover change impacts on LST were quite complex. Meanwhile, ET dominated the cooling during the wet season and warm season. Additionally, enhanced precipitation played a more prominent role in the ET-induced cooling. Evaluation of the effect of temperature change induced by afforestation illustrates the importance of protecting natural forests and avoiding extensive artificial afforestation, especially in northern Guangdong Province, and reverting agricultural land to forest, especially in western Guangdong Province. This analysis also provides a basis for feedback from forest management activities to climate change in southern China. [ABSTRACT FROM AUTHOR]

Simple sequence repeats (SSRs) are an important part of the genome and have become powerful auxiliary DNA markers in animal breeding using marker-assisted selection (MAS). Based on previous sequencing data of Qinghai Bamei pigs, a total of three novel candidate SSR loci were analysed in this study. Time-of-flight mass spectrometry (TOF-MS) was used for SSR genotyping, and association analyses between SSRs and the litter size of Qinghai Bamei sows was also performed. The results of genotyping showed that the (ATC) n -P1, (AC) n -P2 and (AC) n -P3 loci had 2, 3 and 18 genotypes, respectively; 2, 3 and 8 alleles were also identified at these loci. Except for the (AC) n -P2 locus, the polymorphism information content (PIC) values of other loci were greater than 0.25. Association analyses indicated that only the (ATC) n -P1 locus was significantly associated with the litter size of Qinghai Bamei sows (p = .047). Compared to 189-/189- genotype, individuals with the 189-/195- genotype had the senior litter size, which was 9.04 ± 0.21. Our results enrich the data on SSRs in Qinghai Bamei pigs and indicate that (ATC) n -P1 is a candidate locus for MAS in the pig industry., (© 2021 The Authors Veterinary Medicine and Science Published by John Wiley & Sons Ltd.)

Background: Acute respiratory infections (ARI) cause considerable morbidity and mortality worldwide, especially in children. Unfortunately, there are limited multi-center data on common viral respiratory infections in south China., Methods: A total of 4403 nasal swabs were collected from children in 10 cities in Guangdong, China in 2019. Seven respiratory viruses, influenza A virus (IFA), influenza B virus (IFB), respiratory syncytial virus (RSV), adenoviruses (ADV) and parainfluenza virus types 1-3 (PIV1, PIV2 and PIV3), were detected by direct immunofluorescence antibody assay. The personal information and clinical characteristics were recorded and analyzed., Results: The results showed that at least one virus was detected in 1099 (24.96 %) samples. The detection rates of RSV, IFA, ADV, PIV3, PIV1 and PIV2 were 7.13 % (314/4403), 5.31 % (234/4403), 4.02 % (177/4403), 3.04 % (134/4403), 1.70 % (75/4403) and 1.16 % (51/4403), respectively. The detection rate of RSV was highest in 0-6-month-old children at 18.18 % (106/583), while the detection rate of IFA was highest in 12-18-year-old children at 20.48 % (17/83). The total detection rates in winter and spring were 35.67 % (219/614) and 34.56 % (403/1166), higher than those in summer, 17.41 % (284/1631), and autumn, 19.46 % (193/992)., Conclusions: RSV and IFA were the main respiratory viruses in children. With increasing age the detection rate of RSV decreased in children, but the trends for the detection rates of IFA and IFB were the opposite. This study provided the viral etiology and epidemiology of pediatric patients with ARI in Guangdong, China.