Biomedical subjects

J M Chen

Publications and source records attributed to J M Chen.

At least 19 recordsLinked to original sources

PubMed2006

Future carbon balance of China's forests under climate change and increasing CO2.

The possible response of the carbon (C) balance of China's forests to an increase in atmospheric CO(2) concentration and climate change was investigated through a series of simulations using the Integrated Terrestrial Ecosystem Carbon (InTEC) model, which explicitly represents the effects of climate, CO(2) concentration, and nitrogen deposition on future C sequestration by forests. Two climate change scenarios (CGCM2-A2 and -B2) were used to drive the model. Simulations showed that China's forests were a C sink in the 1990 s, averaging 189 Tg C yr(-1) (about 13% of the global total). This sink peaks around 2020 and then gradually declines to 33.5 Tg C yr(-1) during 2091-2100 without climate and CO(2) changes. Effects of pure climate change of CGCM2-A2 and -B2 without allowing CO(2) effects on C assimilation in plants might reduce the average net primary productivity (NPP) of China's forests by 29% and 18% during 2091-2100, respectively. Total soil C stocks might decrease by 16% and 11% during this period. China's forests might broadly act as C sources during 2091-2100, with values of about 50 g Cm(-2)yr(-1) under the moderate warming of CGCM2-B2 and 50-200 g Cm(-2)yr(-1) under the warmer scenario of CGCM2-A2. An increase in CO(2) might broadly increase future C sequestration of China's forests. However, this CO(2) fertilization effect might decline with time. The CO(2) fertilization effects on NPP by the end of this century are 349.6 and 241.7 Tg C yr(-1) under CGCM2-A2 and -B2 increase scenarios, respectively. These effects increase by 199.1 and 126.6 Tg C yr(-1) in the first 50 years, and thereafter, by 150.5 and 115.1 Tg C yr(-1) in the second 50 years under CGCM2-A2 and -B2 increase scenarios, respectively. Under a CO(2) increase without climate change, the majority of China's forests would be C sinks during 2091-2100, ranging from 0 to 100 g Cm(-2)yr(-1). The positive effect of CO(2) fertilization on NPP and net ecosystem productivity would be exceeded by the negative effect of climate change after 2050. Under the CGCM2-A2 climate scenario and with direct CO(2) effects, China's forests may be a small C source of 7.6 Tg C yr(-1) during 2091-2100. Most forests act as C sources of 0-40 g Cm(-2)yr(-1). Under the CGCM2-B2 climate scenario and with direct CO(2) effects, China's forests might be a small C sink of 10.5 Tg C yr(-1) during 2091-2100, with C sequestration of most forests ranging from 0 to 40 g Cm(-2)yr(-1). Stand age structure plays a more dominant role in determining future C sequestration than CO(2) and climate change. The prediction of future C sequestration of China's forests is very sensitive to the Q(10) value used to estimate maintenance respiration and to soil water availability and less sensitive to N deposition scenario. The results are not yet comprehensive, as no forest disturbance data were available or predicted after 2001. However, the results indicate a range of possible responses of the C balance of China's forests to various scenarios of increase in CO(2) and climate change. These results could be useful for assessing measures to mitigate climate change through reforestation.

Atmosphere↗

PubMed2006

Effects of topography on simulated net primary productivity at landscape scale.

Local topography significantly affects spatial variations of climatic variables and soil water movement in complex terrain. Therefore, the distribution and productivity of ecosystems are closely linked to topography. Using a coupled terrestrial carbon and hydrological model (BEPS-TerrainLab model), the topographic effects on the net primary productivity (NPP) are analyzed through four modelling experiments for a 5700 km(2) area in Baohe River basin, Shaanxi Province, northwest of China. The model was able to capture 81% of the variability in NPP estimated from tree rings, with a mean relative error of 3.1%. The average NPP in 2003 for the study area was 741 gCm(-2)yr(-1) from a model run including topographic effects on the distributions of climate variables and lateral flow of ground water. Topography has considerable effect on NPP, which peaks near 1350 m above the sea level. An elevation increase of 100 m above this level reduces the average annual NPP by about 25 gCm(-2). The terrain aspect gives rise to a NPP change of 5% for forests located below 1900 m as a result of its influence on incident solar radiation. For the whole study area, a simulation totally excluding topographic effects on the distributions of climatic variables and ground water movement overestimated the average NPP by 5%.

Biomass↗

PubMed2006

Enhancing forest carbon sequestration in China: toward an integration of scientific and socio-economic perspectives.

This article serves as an introduction to this special issue, "China's Forest Carbon Sequestration", representing major results of a project sponsored by the Canadian International Development Agency and the Chinese Academy of Sciences. China occupies a pivotal position globally as a principle emitter of carbon dioxide, as host to some of the world's largest reforestation efforts, and as a key player in international negotiations aimed at reducing global greenhouse gas emission. The goals of this project are to develop remote sensing approaches for quantifying forest carbon balance in China in a transparent manner, and information and tools to support land-use decisions for enhanced carbon sequestration (CS) that are science based and economically and socially viable. The project consists of three components: (i) remote sensing and carbon modeling, (ii) forest and soil assessment, and (iii) integrated assessment of the socio-economic implications of CS via forest management. Articles included in this special issue are highlights of the results of each of these components.

Air Pollution↗

PubMed2006

An integrated assessment model of carbon sequestration benefits: a case study of Liping county, China.

This research attempts to model the complexity of planting trees to increase China's CO(2) sequestration potential by using a GIS-based integrated assessment (IA) approach. We use the IA model to assess the impact of China's Grain for Green reforestation and afforestation program on farmer and state incomes as well as CO(2) sequestration in Liping County, Guizhou Province. The IA model consists of five sub-models for carbon sequestration, crop income, timber income, Grain for Green, and carbon credits. It also includes a complementary qualitative module for assessing program impacts by gender and ethnicity. Using four scenarios with various assumptions about types of trees planted, crop incomes by township, CO(2) credit prices, state subsidies, methods for estimating carbon sequestered, and harvesting of trees, we find great variation in the impact of the Grain for Green program on incomes and on carbon sequestered over a 48 year period at both the county and township levels.

Carbon↗

PubMed2006

Retrieving leaf area index for coniferous forest in Xingguo County, China with Landsat ETM+ images.

Spatial distributions of the leaf area index (LAI) needed for carbon cycle modeling in Xingguo County, China were estimated based on correlations between the field-measurements and vegetation indices (VIs). After making geometric and atmospheric corrections to two Landsat ETM+ images, one in January 2000 and the other in May 2003, three VIs (SR, NDVI, and RSR) were derived, and their separate correlations with ground LAI measurements were established. The correlation with RSR was the highest among the three VIs. The retrieved LAI values for January 2000 were lower than those for May 2003 because of a small seasonal variation in the coniferous forests (predominantly masson pine) and the decrease in the understorey vegetation during winter.

Atmosphere↗

PubMed2006

Measurements and simulation of forest leaf area index and net primary productivity in Northern China.

Large scale process-based modeling is a useful approach to estimate distributions of global net primary productivity (NPP). In this paper, in order to validate an existing NPP model with observed data at site level, field experiments were conducted at three sites in northern China. One site is located in Qilian Mountain in Gansu Province, and the other two sites are in Changbaishan Natural Reserve and Dunhua County in Jilin Province. Detailed field experiments are discussed and field data are used to validate the simulated NPP. Remotely sensed images including Landsat Enhanced Thematic Mapper plus (ETM+, 30 m spatial resolution in visible and near infrared bands) and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER, 15m spatial resolution in visible and near infrared bands) are used to derive maps of land cover, leaf area index, and biomass. Based on these maps, field measured data, soil texture and daily meteorological data, NPP of these sites are simulated for year 2001 with the boreal ecosystem productivity simulator (BEPS). The NPP in these sites ranges from 80 to 800 gCm(-2)a(-1). The observed NPP agrees well with the modeled NPP. This study suggests that BEPS can be used to estimate NPP in northern China if remotely sensed images of high spatial resolution are available.

Biomass↗

PubMed2006

Dissociation dynamics of positive-ion and negative-ion fragments of gaseous and condensed Si(CH(3))(2)Cl(2) via Si 2p, Cl 2p, and Cl 1s core-level excitations.

The state-selective positive-ion and negative-ion dissociation pathways of gaseous and condensed Si(CH(3))(2)Cl(2) following Cl 2p, Cl 1s, and Si 2p core-level excitations have been characterized. The excitations to a specific antibonding state (15a(1) (*) state) of gaseous Si(CH(3))(2)Cl(2) at the Cl 2p, Cl 1s, and Si 2p edges produce significant enhancement of fragment ions. This ion enhancement at specific core-excited states correlates closely with the ion kinetic energy distribution. The results deduced from ion kinetic energy distribution are consistent with results of quantum-chemical calculations on Si(CH(3))(2)Cl(2) using the ADF package. The Cl(-) desorption yields for Si(CH(3))(2)Cl(2)Si(100) at approximately 90 K are notably enhanced at the 15a(1) (*) resonance at both Cl 2p and Si 2p edges. The resonant enhancement of Cl(-) yield occurs through the formation of highly excited states of the adsorbed molecules. These results provide insight into the state-selective ionic fragmentation of molecules via core-level excitation.

Chlorine↗

PubMed2006

Comprehensive study of lead pollution in Shanghai by multiple techniques.

Aerosol samples of PM10 particulates were examined with particle-induced X-ray emission (PIXE and micro-PIXE ), inductively coupled plasma-mass spectrometry, and X-ray absorption fine structures (XAFS) to investigate atmospheric Pb concentrations and its chemical species and to decide the source assignment. From the elemental analyses, lead concentrations were averaged at 369 and 237 ng.m-3 in aerosol samples of PM10 collected from 19 monitor sites in Shanghai in the winter of 2002 and 2003, respectively. The XAFS results show that major chemical forms of the lead particulates are probably PbCl2, PbSO4, and PbO. A calculation of isotope ratio and chemical mass balance of the PM10 samples revealed that the atmospheric lead particulates in Shanghai in the two periods were mainly from coal combustors, iron and steel plants, and automobile exhausts, with coal combustion dominating the lead pollution after the phasing out of leaded gasoline in 1997 in Shanghai.

Air Pollutants↗

PubMed2006

Carbon sinks and sources in China's forests during 1901-2001.

This paper reports the annual carbon (C) balance of China's forests during 1901-2001 estimated using the Integrated Terrestrial Ecosystem C-budget model (InTEC). Annual carbon source and sink distributions are simulated for the same period using various spatial datasets including land cover and leaf area index (LAI) obtained from remote sensing, soil texture, climate, forest age, and nitrogen deposition. During 1901-1949, China's forests were a source of 21.0+/-7.8 Tg C yr(-1) due to disturbances (human activities). Its size increased to 122.3+/-25.3 Tg C yr(-1) during 1950-1987 due to intensified human activities in the late 1950s, early 1960s, 1970s and early 1980s. The forests became large sinks of 176.7+/-44.8 Tg C yr(-1) during 1988-2001, owing to large-scale plantation and forest regrowth in previously disturbed areas as well as growth stimulation by nondisturbance factors such as climatic warming, atmospheric CO(2) fertilization, and N deposition. From 1901 to 2001, China's forests were a small carbon source of 3.32 Pg C, about 32.9+/-22.3 Tg C yr(-1). The overall C balance in biomass from InTEC generally agrees with previous results derived from forest inventories of China's forests. InTEC results also include C stock variation in soils and are therefore more comprehensive than previous results. The uncertainty in InTEC results is still large, but it can be reduced if a detailed forest age map becomes available.

Agriculture↗

PubMed2006

Observation and simulation of net primary productivity in Qilian Mountain, western China.

We modeled net primary productivity (NPP) at high spatial resolution using an advanced spaceborne thermal emission and reflection radiometer (ASTER) image of a Qilian Mountain study area using the boreal ecosystem productivity simulator (BEPS). Two key driving variables of the model, leaf area index (LAI) and land cover type, were derived from ASTER and moderate resolution imaging spectroradiometer (MODIS) data. Other spatially explicit inputs included daily meteorological data (radiation, precipitation, temperature, humidity), available soil water holding capacity (AWC), and forest biomass. NPP was estimated for coniferous forests and other land cover types in the study area. The result showed that NPP of coniferous forests in the study area was about 4.4 tCha(-1)y(-1). The correlation coefficient between the modeled NPP and ground measurements was 0.84, with a mean relative error of about 13.9%.

Altitude↗

PubMed2006

Combining remote sensing imagery and forest age inventory for biomass mapping.

Aboveground biomass (AGB) of forests is an important component of the global carbon cycle. In this study, Landsat ETM(+) images and field forest inventory data were used to estimate AGB of forests in Liping County, Guizhou Province, China. Three different vegetation indices, including simple ratio (SR), reduced simple ratio (RSR), and normalized difference vegetation index (NDVI), were calculated from atmospherically corrected ETM(+) reflectance images. A leaf area index (LAI) map was produced from the RSR map using a regression model based on measured LAI and RSR. The LAI map was then used to develop an initial AGB map, from which forest stand age was deduced. Vegetation indices, LAI, and forest stand age were together used to develop AGB estimation models for different forest types through a stepwise regression analysis. Significant predictors of AGB changed with forest types. LAI and NDVI were significant predictors of AGB for Chinese fir (R(2)=0.93). The model using LAI and stand age as predictors explained 94% of the AGB variance for coniferous forests. Stand age captured 79% of the AGB variance for broadleaved forests (R(2)=0.792). AGB of mixed forests was predicted well by LAI and SR (R(2)=0.931). Without differentiating among forest types, the model with SR and LAI as predictors was able to explain 90% of AGB variances of all forests. In Liping County, AGB shows a strong gradient that increases from northeast to southwest. About 64% of the forests have AGB in the range from 90 to 180 t ha(-1).

Biomass↗

PubMed2006

LAI inversion algorithm based on directional reflectance kernels.

Leaf area index (LAI) is an important ecological and environmental parameter. A new LAI algorithm is developed using the principles of ground LAI measurements based on canopy gap fraction. First, the relationship between LAI and gap fraction at various zenith angles is derived from the definition of LAI. Then, the directional gap fraction is acquired from a remote sensing bidirectional reflectance distribution function (BRDF) product. This acquisition is obtained by using a kernel driven model and a large-scale directional gap fraction algorithm. The algorithm has been applied to estimate a LAI distribution in China in mid-July 2002. The ground data acquired from two field experiments in Changbai Mountain and Qilian Mountain were used to validate the algorithm. To resolve the scale discrepancy between high resolution ground observations and low resolution remote sensing data, two TM images with a resolution approaching the size of ground plots were used to relate the coarse resolution LAI map to ground measurements. First, an empirical relationship between the measured LAI and a vegetation index was established. Next, a high resolution LAI map was generated using the relationship. The LAI value of a low resolution pixel was calculated from the area-weighted sum of high resolution LAIs composing the low resolution pixel. The results of this comparison showed that the inversion algorithm has an accuracy of 82%. Factors that may influence the accuracy are also discussed in this paper.

Algorithms↗

PubMed2006

Regional patterns of soil organic carbon stocks in China.

Soil organic carbon (SOC) is of great importance in the global carbon cycle. Distribution patterns of SOC in various regions of China constitute a nation-wide baseline for studies on soil carbon changes. This paper presents an integrated and multi-level study on SOC stock patterns of China, and presents baseline SOC stock estimates by great administrative regions, river watersheds, soil type regions and ecosystem. The assignment is done by means of a recently completed 1: 1,000,000 scale soil database of China, which is the most detailed and reliable one in China at the present time. SOC densities of 7292 soil profiles collected across China in the middle of the 1980s were calculated and then linked to corresponding polygons in a digital soil map, resulting in a SOC Density Map of China on a 1: 1,000,000 scale, and a 1 km x 1 km grid map. Corresponding maps of administrative regions, river watersheds, soil types (ST), and ecosystems in China were also prepared with an identical resolution and coordinate control points, allowing GIS analyses. Results show that soils in China cover an area of 9.281 x 10(6)km(2) in total, with a total SOC stock of 89.14 Pg (1 Pg=10(15)g) and a mean SOC density of 96.0 t C/ha. Confidence limits of the SOC stock and density in China are estimated as [89.23 Pg, 89.08 Pg] and [96.143 t C/ha, 95.981 t C/ha] at 95% probability, respectively. The largest total SOC stock (23.60 Pg) is found in South-west China while the highest mean SOC density (181.9 t C/ha) is found in north-east China. The total SOC stock and the mean SOC density in the Yangtze river watershed are 21.05 Pg and 120.0 t C/ha, respectively, while the corresponding figures in the Yellow river watershed are 8.46 Pg and 104.3 t C/ha, respectively. The highest total SOC stocks are found in Inceptisols (34.39 Pg) with SOC density of 102.8 t C/ha. The lowest and highest mean SOC densities are found on Entisols (28.1 t C/ha), and on Histosols (994.728.1 t C/ha), respectively. Finally, the total SOC stock in shrub and forest ecosystem classes are 25.55 and 21.50 Pg, respectively; the highest mean SOC density (209.9 t C/ha) was recorded in the wetland ecosystem class and the lowest (29.0 t C/ha) in the desert ecosystem class. Among five forest ecosystem types, Evergreen conifer forest stores the highest SOC stock (6.81 Pg), and Deciduous conifer forest shows the highest SOC density (225.9 t C/ha). Figures of SOC stocks stratified by Administrative regions, river watersheds, soil types and ecosystem types presented in the study may constitute national-wide baseline for studies of SOC stock changes in various regions in the future.

Carbon↗

PubMed2006

Application of a new leaf area index algorithm to China's landmass using MODIS data for carbon cycle research.

An operational system was developed for mapping the leaf area index (LAI) for carbon cycle models from the moderate resolution imaging spectroradiometer (MODIS) data. The LAI retrieval algorithm is based on Deng et al. [2006. Algorithm for global leaf area index retrieval using satellite imagery. IEEE Transactions on Geoscience and Remote Sensing, 44, 2219-2229], which uses the 4-scale radiative transfer model [Chen, J.M., Leblancs, 1997. A 4-scale bidirectional reflection model based on canopy architecture. IEEE Transactions on Geoscience and Remote Sensing, 35, 1316-1337] to simulate the relationship of LAI with vegetated surface reflectance measured from space for various spectral bands and solar and view angles. This algorithm has been integrated to the MODISoft platform, a software system designed for processing MODIS data, to generate 250 m, 500 m and 1 km resolution LAI products covering all of China from MODIS MOD02 or MOD09 products. The multi-temporal interpolation method was implemented to remove the residual cloud and other noise in the final LAI product so that it can be directly used in carbon models without further processing. The retrieval uncertainties from land cover data were evaluated using five different data sets available in China. The results showed that mean LAI discrepancies can reach 27%. The current product was also compared with the NASA MODIS MOD15 LAI product to determine the agreement and disagreement of two different product series. LAI values in the MODIS product were found to be 21% larger than those in the new product. These LAI products were compared against ground TRAC measurements in forests in Qilian Mountain and Changbaishan. On average, the new LAI product agrees with the field measurement in Changbaishan within 2%, but the MODIS product is positively biased by about 20%. In Qilian Mountain, where forests are sparse, the new product is lower than field measurements by about 38%, while the MODIS product is larger by about 65%.

Algorithms↗

PubMed2006

Spatial scaling between leaf area index maps of different resolutions.

We developed algorithms for spatial scaling of leaf area index (LAI) using sub-pixel information. The study area is located near Liping County, Guizhou Province, in China. Methods for LAI spatial scaling were investigated on LAI images with 960 m resolution derived in two ways. LAI from distributed calculation (LAID) was derived using Landsat ETM+ data (30 m), and LAI from lumped calculation (LAIL) was obtained from the coarse (960 m) resolution data derived through resampling the ETM+ data. We found that lumped calculations can be considerably biased compared to the distributed (ETM+) case, suggesting that global and regional LAI maps can be biased if surface heterogeneity within the mapping resolution is ignored. Based on these results, we developed algorithms for removing the biases in lumped LAI maps using sub-pixel land cover-type information, and applied these to correct one coarse resolution LAI product which greatly improved its accuracy.

China↗

PubMed2006

Soil organic carbon decomposition and carbon pools in temperate and sub-tropical forests in China.

Decomposition of soil organic carbon (SOC) is a critical component of the global carbon cycle, and accurate estimates of SOC decomposition are important for forest carbon modeling and ultimately for decision making relative to carbon sequestration and mitigation of global climate change. We determined the major pools of SOC in four sites representing major forest types in China: temperate forests at Changbai Mountain (CBM) and Qilian Mountain (QLM), and sub-tropical forests at Yujiang (YJ) and Liping (LP) counties. A 90-day laboratory incubation was conducted to measure CO(2) evolution from forest soils from each site, and data from the incubation study were fitted to a three-pool first-order model that separated mineralizable soil organic carbon into active (C(a)), slow (C(s)) and resistant (C(r)) carbon pools. Results indicate that: (1) the rate of SOC decomposition in the sub-tropical zone was faster than that in the temperature zone, (2) The C(a) pool comprised approximately 1-3% of SOC with an average mean residence time (MRT) of 219 days. The C(s) pool comprised approximately 25-65% with an average MRT of 78 yr. The C(r) pool accounted for approximately 35-80% of SOC, (3) The YJ site in the sub-tropical zone had the greatest C(a) pool and the lowest MRT, while the QLM in the temperature zone had the greatest MRT for both the C(a) and C(s) pools. The results suggest a higher capacity for long-term C sequestration as SOC in temperature forests than in sub-tropical forests.

Carbon↗

PubMed2006

Tests of soil organic carbon density modeled by InTEC in China's forest ecosystems.

The integrated terrestrial ecosystem C-budget model (InTEC) developed by Chen and co-workers has been used successfully to predict carbon dynamics of forests in Canada. It was tested here for forest soil organic carbon (SOC) density of China's northern temperate zone and southern subtropical zone. The results show that the simulated SOC density is highly correlated and in broad agreement with observations in Liping and in Changbaishan, representing the southern subtropical zone and the northern temperate zone in China, respectively. SOC density ranged from 2.2 to 11.2 kg/m(2) in Liping and from 3.4 to 14.8 kg/m(2) in Changbaishan. The correlation coefficients (r(2)) are 0.63 (N=16) and 0.76 (N=14) between the simulated and measured data in Liping and Changbaishan, respectively. The SOC densities under different vegetation types in Liping decrease in the order of mixed forest, broadleaf forest, Chinese fir, couch grass, and Chinese redpine, and in Changbaishan in the order of mixed forest, silver fir, larch forest, and birch forest.

Carbon↗

PubMed2006

Acetylenic TACE inhibitors. Part 3: Thiomorpholine sulfonamide hydroxamates.

A series of thiomorpholine sulfonamide hydroxamate TACE inhibitors, all bearing propargylic ether P1' groups, was explored. In particular, compound 5h has excellent in vitro potency against isolated TACE enzyme and in cells, oral activity in a model of TNF-alpha production and a collagen-induced arthritis model, was selected as a clinical candidate for the treatment of RA.

ADAM Proteins↗