The quantitative knowledge of global forest litterfall is very important for understanding the global biogeochemical cycle and evaluating of forest ecosystem services. Our aims are to show the spatio‐temporal patterns of forest litterfall and the variation in different forest types and climate zones in the world. We compiled the global forest litterfall dataset of 2347 total litterfall and 1507 leaf litterfall measurements by a survey of literature published. The total litterfall and leaf litterfall were estimated in 2000 and 2009, respectively, through raster and vector calculation based on remote sensing‐based global vegetation cover data. The total litterfall and leaf litterfall were 31.5 Pg and 22 Pg in 2000 and 26 Pg and 18 Pg in 2009, respectively. The spatial pattern of litterfall and leaf litterfall at global scale between 2000 and 2009 was generally similar. The largest fractions of forest litterfall were in evergreen broadleaved forests (37%), followed by needle‐leaved forests (25%), deciduous broadleaved forests (20%), and others (18%) in 2000. The order of the fractions for forest litterfall was the tropical (50%), boreal (24%), temperate (17%), and subtropical forests (9%) in 2000. The ratios of leaf litterfall to litterfall were 70% in 2000 and 72% in 2009. The variability of global litterfall was most explained by the actual evapotranspiration. The reduction in total litterfall and leaf litterfall between 2000 and 2009 was coupled with the decrease in forest areas. The GIS‐based geostatistics combining with the regression model represents a powerful approach for estimating the global spatial distribution, composition, and magnitude of litterfall.

Land-use/land-cover (LULC) changes are occurring at rapid rates on the Chongming Island of Shanghai, China, giving rise to a major concern about environmental impacts. We herein carried out a sound analysis of the LULC dynamics, the conversions among different LULC classes, and land-surface temperature (LST) distribution using remote-sensing data from Landsat Multispectral Scanner (MSS), Thematic Mapper (TM), and Enhanced Thematic Mapper Plus (ETM+) time series spanning the last 35 years (1979–2014). Based on LULC class information and LST, we constructed a temperature/vegetation index space to study the temporal variability of thermal data, vegetation cover, and LULC. The results showed that the LULC change dynamics in Chongming Island have strongly impacted the LST in the recent decade. The spatial position conversion and quantitative change of vegetation cover totalled about 44.4% of LULC-type areas over the Island, and the comprehensive LULC dynamicity changed from 2.97 to 3.95 during the investigated period. Accordingly, significant LST changes took place in the portion of the Chongming Island showing normal temperature range, which accounted for 85.94% of the whole Island’s area as of 1 August 2000 and that decreased to 50.79% on 6 May 2009, while the surface extents under low- and with ultra-high-temperature ranges increased, respectively, both from 0 of 2000 to 6.67% and 0.41% of 2009. The results indicate that the pixel classes including vegetation cover, wetland, and waterbody, which have larger dynamicity and maximum change vector magnitudes, played a large role in alleviating the effect of the land-surface thermal environment, and were key driving factors contributing to the increasing trend of non-normal temperature range ratio over time. Our findings are expected to provide valuable information for decision-making regarding the development and construction of Chongming Island into an eco-region.

Chongming Island in China is currently undergoing a rapid urbanization and an increasing environmental pressure due to its fast-paced social economic development. Owing to natural silts deposit phenomenon as well as artificial land reclamation practices, the Island is also experiencing an expansion phenomenon. The synergy between these natural and artificial phenomena results in a rapidly changing landscape on Chongming Island. Consequently, the tools and methods for a rapid and cost-effective detection and assessment of related issues are urgently needed to ensure a harmonious and sustainable development of the Island. We herein investigate the urban growth and the landscape pattern change in relation to the Island’s expansion phenomenon and the associated complexity of land use/cover change. Our investigation is based on a time series of Landsat satellite images spanning the past 34 years. The methodological approach adopted in the present study combines vegetation indices, images textural features and social statistics data in an object-oriented classification framework. With Chongming Island expanding by an annual rate of 0.9% between 1979 and 2013, we found that the proportion of vegetation area to the total area decreased from 71 to 45%, whereas the proportion of built-up area to the total area increased from 5 to 19.9%. The urban area expanded about six times from 1979 to 2013, and during the same period, the Island’s population did not change significantly. The urban spatial expansion of Chongming Island caused distinct expansion intensity index for each intervals, and significant fragmentation and diversity in the landscape pattern between 1979 and 2013. It was also found that the rapid urbanization process took place at the expense of landscape pattern changes at any time within the study period. This is a strong indication that besides the natural geographic element, economic development and policy orientation were the dominant driving factors. If the current rate of urban expansion is to be maintained and the vegetation cover is to keep decreasing at an annual rate of 0.1% (period 1979–2013), their combined effects would profoundly alter the ecological environment in the long term. These findings provide a basic objective and scientific information for knowledgeable decision-making and policy formulation regarding regional planning and management to ensure harmonious transition of Chongming towards ecologically oriented development.

Appropriate agricultural practices for carbon sequestration and emission mitigation have a significant influence on global climate change. However, various agricultural practices on farmland carbon sequestration usually have a major impact on greenhouse gas (GHG) emissions. It is very important to accurately quantify the effect of agricultural practices. This study developed a platform—the Denitrification Decomposition (DNDC) online model—for simulating and evaluating the agricultural carbon sequestration and emission mitigation based on the scientific process of the DNDC model, which is widely used in the simulation of soil carbon and nitrogen dynamics. After testing the adaptability of the platform on two sampling fields, it turned out that the simulated values matched the measured values well for crop yields and GHG emissions. We used the platform to estimate the effect of three carbon sequestration practices in a sampling field: nitrogen fertilization reduction, straw residue and midseason drainage. The results indicated the following: (1) moderate decrement of the nitrogen fertilization in the sampling field was able to decrease the N₂O emission while maintaining the paddy rice yield; (2) ground straw residue had almost no influence on paddy rice yield, but the CH₄ emission and the surface SOC concentration increased along with the quantity of the straw residue; (3) compared to continuous flooding, midseason drainage would not decrease the paddy rice yield and could lead to a drop in CH₄ emission. Thus, this study established the DNDC online model, which is able to serve as a reference and support for the study and evaluation of the effects of agricultural practices on agricultural carbon sequestration and GHG emissions mitigation in China.

Greenhouse gas (GHG) emissions are an important part of the carbon (C) and nitrogen (N) cycle in forest soil. However, soil greenhouse gas emissions in dawn redwood (Metasequoia glyptostroboides) stands of different ages are poorly understood. To elucidate the effect of plantation age and environmental factors on soil GHG emissions, we used static chamber/gas chromatography (GC) system to measure soil GHG emissions in an alluvial island in eastern China for two consecutive years. The soil was a source of CO₂ and N₂O and a sink of CH₄ with annual emissions of 5.5–7.1 Mg C ha⁻¹ year⁻¹, 0.15–0.36 kg N ha⁻¹ year⁻¹, and 1.7–4.5 kg C ha⁻¹ year⁻¹, respectively. A clear exponential correlation was found between soil temperature and CO₂ emission, but a negative linear correlation was found between soil water content and CO₂ emission. Soil temperature had a significantly positive effect on CH₄ uptake and N₂O emission, whereas no significant correlation was found between CH₄ uptake and soil water content, and N₂O emission and soil water content. These results implied that older forest stands might cause more GHG emissions from the soil into the atmosphere because of higher litter/root biomass and soil carbon/nitrogen content compared with younger stands.