Growth characteristics of Dahurian larch (Larix gmelinii) in northeast China during 1965-2015

Dahurian larch (Larix gmelinii Rupr.) is the dominant species in northeast China, which situated in the southernmost part of the global boreal forest biome and undergoing the greatest climatically induced changes. Published studies (1965-2015) on tree aboveground growth of Larix gmelinii forests in northeast China were collected in this study, critically reviewed, and a comprehensive growth dataset was developed from 122 sites, which distributed between 40.85° N and 53.47° N in latitude, between 118.20° E and 133.70° E in longitude, between 130 m and 1260 m in altitude. The dataset was composed of 743 entries, including growth data (mean tree height, mean DBH, mean tree volume and/or stand volume) and the associated information, i.e., geographical location (latitude, longitude, altitude, aspect and slope), climate (mean annual temperature (MAT) and mean annual precipitation (MAP)), stand description (origin, stand age, stand density and canopy density), and sample regime (observing year, plot area and number). It would provide quantitative references for plantation management practices and boreal forest growth prediction under future climate change

Soil respiration at different time scales from 2000 to 2018 in forest ecosystems across China

The related studies on soil respiration (Rs) are increasing year by year in China, amounts of Rs data were published, especially in the form of monthly dynamics figures. Here, we compiled a comprehensive and uniform Rs database in China's forests from 568 literatures published up to 2018, including Rs and the concurrently measured soil temperature (N=8317), mean monthly Rs (N=5003), and annual Rs (N=634). Besides the Rs data directly given in the original papers, the monthly patterns of Rs and the concurrently measured soil temperature at 5 cm and/or 10 cm depth in the figures were digitized. These Rs data derived from the undisturbed forest ecosystems. The common measurement methods were selected, i.e. infrared gas analyzers (model Li-6400, Li-8100, Li-8150 (LI-COR Inc., Lincoln, Nebraska, USA)) and gas chromatography. Meanwhile, the associated information was recorded, e.g. geographical location (province, study site, latitude, longitude and elevation), climate factors (mean annual temperature and mean annual precipitation), stand description (forest type, origin, age, density, mean tree height and diameter at breast height), measurement regime (method, time, frequency, collar area, height and numbers). We hope the database will be used by the science community to provide a better understanding of carbon cycle in China's forests and reduce the uncertainty in evaluating of carbon budget at the large scale

A compiled soil respiration dataset at different time scales for forest ecosystems across China from 2000 to 2018

China's forests rank fifth in the world by area, covering a broad climatic gradient from cold-temperate to tropical zones, and play a key role in the global carbon cycle. Studies of forest soil respiration (R-s) have increased rapidly in China over the last two decades, but the resulting R-s data need to be summarized. Here, we compile a comprehensive dataset of R-s in China's undisturbed forest ecosystems from the literature published up to 31 December 2018, including monthly R-s and the concurrently measured soil temperature (N=8317), mean monthly R-s (N=5003), and annual R-s (N=634). Detailed plot information was also recorded, such as geographical location, climate factors, stand characteristics, and measurement description. We examine some aspects of the dataset - R-s equations fitted with soil temperature, temperature sensitivity (Q10), monthly variations, and annual effluxes in cold-temperate, temperate, subtropical, and tropical zones. We hope the dataset will be used by the science community to provide a better understanding of the carbon cycle in China's forest ecosystems and reduce uncertainty in evaluating of carbon budget at a large scale. The dataset is publicly available at (Sun et al., 2022)

Atmospheric Pollution Mapping of the Yangtze River Basin: An AQI-Based Weighted Co-Word Analysis

The purpose of this paper is to analyze the characteristics and human effects of atmospheric pollution in the Yangtze River Basin (YRB). An AQI(Air Quality Index)-based weighted co-word method is applied to explore the characteristics of keywords taken from the data, using authoritative media sources and government reports. Hierarchical clustering techniques are utilized to classify and visualize the keywords and display the different types of incidents. The results reveal the following four main clusters: enterprise pollution, coal-burning pollution, traffic pollution, and air pollutants. Cluster 1 is divided into 7 sub-clusters to offer powerful insight into the structural characteristics of industrial activities. This study is one of the first attempts to use a bibliometric approach to visualize the underlying and interconnected sub-clusters from grey data. It also provides an atmospheric pollution mapping for formulating government policies by understanding the human effects of air pollution incidents

Historical trends of forest fires and carbon emissions in China from 1988 to 2012

A larger amount of carbon is stored in forest ecosystems than in the entire atmosphere. Thus, relatively small changes in forest carbon stocks can significantly impact net carbon exchange between the biosphere and atmosphere. Changes in forest stocks can result from various disturbances, such as insect pests, windstorms, flooding, and especially forest fires. Globally, the impact of forest fires has been enhanced due to ongoing warming of the climate. The current study reported an evaluation of carbon emissions from historical forest fires in China during 1988-2012 with observational data collected from national agriculture statistics. Historical fire trends and fire-induced carbon emissions were described over space and time at both national and regional levels. The results indicated that no significant increases in fire occurrence and carbon emissions were observed during the study period at the national level. However, at the regional level, there was a significant increasing trend in fire occurrence, and drought severity was a major driver of fire activity. Most carbon emissions were from north and northeast China, and these emissions contributed significantly to total carbon emissions. The results also showed that annual fire-induced emissions ranged from 0.04TgC to 7.22TgC, with an average of 1.03TgC. Large interannual and spatial variabilities of carbon emissions were also indicated, and these were attributed to spatial and temporal variations in fire regimes. The results improve understanding of fire characteristics and provide significant information for reducing model-related uncertainty of fire-induced carbon emissions