Chengcheng Gang

Spatio-temporal dynamics of vegetation coverage and its relationship with climate factors in Inner Mongolia, China

The vegetation coverage dynamics and its relationship with climate factors on different spatial and temporal scales in Inner Mongolia during 2001–2010 were analyzed based on MODIS-NDVI data and climate data. The results indicated that vegetation coverage in Inner Mongolia showed obvious longitudinal zonality, increasing from west to east across the region with a change rate of 0.2/10°N. During 2001–2010, the mean vegetation coverage was 0.57, 0.4 and 0.16 in forest, grassland and desert biome, respectively, exhibiting evident spatial heterogeneities. Totally, vegetation coverage had a slight increasing trend during the study period. Across Inner Mongolia, the area of which the vegetation coverage showed extremely significant and significant increase accounted for 11.25% and 29.13% of the area of whole region, respectively, while the area of which the vegetation coverage showed extremely significant and significant decrease accounted for 7.65% and 26.61%, respectively. On inter-annual time scale, precipitation was the dominant driving force of vegetation coverage for the whole region. On inter-monthly scale, the change of vegetation coverage was consistent with both the change of temperature and precipitation, implying that the vegetation growth within a year is more sensitive to the combined effects of water and heat rather than either single climate factor. The vegetation coverage in forest biome was mainly driven by temperature on both inter-annual and inter-monthly scales, while that in desert biome was mainly influenced by precipitation on both the two temporal scales. In grassland biome, the yearly vegetation coverage had a better correlation with precipitation, while the monthly vegetation coverage was influenced by both temperature and precipitation. In grassland biome, the impacts of precipitation on monthly vegetation coverage showed time-delay effects.

Vegetation dynamics and its driving forces from climate change and human activities in the Three-River Source Region, China from 1982 to 2012

The Three-River Source Region (TRSR), a region with key importance to the ecological security of China, has undergone climate changes and a shift in human activities driven by a series of ecological restoration projects in recent decades. To reveal the spatiotemporal dynamics of vegetation dynamics and calculate the contributions of driving factors in the TRSR across different periods from 1982 to 2012, net primary productivity (NPP) estimated using the Carnegie-Ames-Stanford approach model was used to assess the status of vegetation. The actual effects of different climatic variation trends on interannual variation in NPP were analyzed. Furthermore, the relationships of NPP with different climate factors and human activities were analyzed quantitatively. Results showed the following: from 1982 to 2012, the average NPP in the study area was 187.37gcm(-2)yr(-1). The average NPP exhibited a fluctuation but presented a generally increasing trend over the 31-year study period, with an increase rate of 1.31gcm(-2)yr(-2). During the entire study period, the average contributions of temperature, precipitation, and solar radiation to NPP interannual variation over the entire region were 0.58, 0.73, and 0.09gcm(-2)yr(-2), respectively. Radiation was the climate factor with the greatest influence on NPP interannual variation. The factor that restricted NPP increase changed from temperature and radiation to precipitation. The average contributions of climate change and human activities to NPP interannual variation were 1.40gcm(-2)yr(-2) and -0.08gcm(-2)yr(-2), respectively. From 1982 to 2000, the general climate conditions were favorable to vegetation recovery, whereas human activities had a weaker negative impact on vegetation growth. From 2001 to 2012, climate conditions began to have a negative impact on vegetation growth, whereas human activities made a favorable impact on vegetation recovery.

Assessing the spatiotemporal variation in distribution, extent and NPP of terrestrial ecosystems in response to climate change from 1911 to 2000.

To assess the variation in distribution, extent, and NPP of global natural vegetation in response to climate change in the period 1911–2000 and to provide a feasible method for climate change research in regions where historical data is difficult to obtain. In this research, variations in spatiotemporal distributions of global potential natural vegetation (PNV) from 1911 to 2000 were analyzed with the comprehensive sequential classification system (CSCS) and net primary production (NPP) of different ecosystems was evaluated with the synthetic model to determine the effect of climate change on the terrestrial ecosystems. The results showed that consistently rising global temperature and altered precipitation patterns had exerted strong influence on spatiotemporal distribution and productivities of terrestrial ecosystems, especially in the mid/high latitudes. Ecosystems in temperate zones expanded and desert area decreased as a consequence of climate variations. The vegetation that decreased the most was cold desert (18.79%), while the maximum increase (10.31%) was recorded in savanna. Additionally, the area of tundra and alpine steppe reduced significantly (5.43%) and were forced northward due to significant ascending temperature in the northern hemisphere. The global terrestrial ecosystems productivities increased by 2.09%, most of which was attributed to savanna (6.04%), tropical forest (0.99%), and temperate forest (5.49%). Most NPP losses were found in cold desert (27.33%). NPP increases displayed a latitudinal distribution. The NPP of tropical zones amounted to more than a half of total NPP, with an estimated increase of 1.32%. The increase in northern temperate zone was the second highest with 3.55%. Global NPP showed a significant positive correlation with mean annual precipitation in comparison with mean annual temperature and biological temperature. In general, effects of climate change on terrestrial ecosystems were deep and profound in 1911–2000, especially in the latter half of the period.

Desertification dynamic and the relative roles of climate change and human activities in desertification in the Heihe River Basin based on NPP

Relative roles of climate change and human activities in desertification are the hotspot of research on desertification dynamic and its driving mechanism. To overcome the shortcomings of existing studies, this paper selected net primary productivity (NPP) as an indicator to analyze desertification dynamic and its impact factors. In addition, the change trends of actual NPP, potential NPP and HNPP (human appropriation of NPP, the difference between potential NPP and actual NPP) were used to analyze the desertification dynamic and calculate the relative roles of climate change, human activities and a combination of the two factors in desertification. In this study, the Moderate Resolution Imaging Spectroradiometer (MODIS)-Normalised Difference Vegetation Index (NDVI) and meteorological data were utilized to drive the Carnegie-Ames-Stanford Approach (CASA) model to calculate the actual NPP from 2001 to 2010 in the Heihe River Basin. Potential NPP was estimated using the Thornthwaite Memorial model. Results showed that 61% of the whole basin area underwent land degradation, of which 90.5% was caused by human activities, 8.6% by climate change, and 0.9% by a combination of the two factors. On the contrary, 1.5% of desertification reversion area was caused by human activities and 90.7% by climate change, the rest 7.8% by a combination of the two factors. Moreover, it was demonstrated that 95.9% of the total actual NPP decrease was induced by human activities, while 69.3% of the total actual NPP increase was caused by climate change. The results revealed that climate change dominated desertification reversion, while human activities dominated desertification expansion. Moreover, the relative roles of both climate change and human activities in desertification possessed great spatial heterogeneity. Additionally, ecological protection policies should be enhanced in the Heihe River Basin to prevent desertification expansion under the condition of climate change.

Grassland coverage inter-annual variation and its coupling relation with hydrothermal factors in China during 1982-2010

GIMMS (Global Inventory Modeling and Mapping Studies) NDVI (Normalised Difference Vegetation Index) from 1982 to 2006 and MODIS (Moderate Resolution Imaging Spectroradiometer) NDVI from 2001 to 2010 were blended to extract the grass coverage and analyze its spatial pattern. The response of grass coverage to climatic variations at annual and monthly time scales was analyzed. Grass coverage distribution had increased from northwest to southeast across China. During 1982–2010, the mean nationwide grass coverage was 34% but exhibited apparent spatial heterogeneity, being the highest (61.4%) in slope grasslands and the lowest (17.1%) in desert grasslands. There was a slight increase of the grass coverage with a rate of 0.17% per year. Increase in slope grasslands coverage was as high as 0.27% per year, while in the plain grasslands and meadows the grass coverage increase was the lowest (being 0.11% per year and 0.1% per year, respectively). Across China, the grass coverage with extremely significant increase (P<0.01) and significant increase (P<0.05) accounted for 46.03% and 11% of the total grassland area, respectively, while those with extremely significant and significant decrease accounted for only 4.1% and 3.24%, respectively. At the annual time scale, there are no significant correlations between grass coverage and annual mean temperature and precipitation. However, the grass coverage was somewhat affected by temperature in alpine and sub-alpine grassland, alpine and sub-alpine meadow, slope grassland and meadow, while grass coverage in desert grassland and plain grassland was more affected by precipitation. At the monthly time-scale, there are significant correlations between grass coverage with both temperature and precipitation, indicating that the grass coverage is more affected by seasonal fluctuations of hydrothermal conditions. Additionally, there is one-month time lag-effect between grass coverage and climate factors for each grassland types.

Research of real-time image acquisition system based on ARM 7 for agricultural environmental monitoring

The internet of things (IOT) has brought a broader space to the intensive development of modern agriculture in the application of agricultural environmental monitoring. To solve the problems of real-time video acquisition, image acquisition and motion capture in the agricultural environment, this paper use the ARM S3C44B0X as the processor and put forward a new kind of real-time video acquisition technique based on 32bits embedded processor system. the optimized and minimized hardware system is designed, including designs the GAL gathering controller to control the output digital video signal data form SAA7111A to the frame buffer storage memory Al422, and expanded the interface of FLASH, SDRAM, CF Card, RS232, JTAG and so on; Secondly, through the transplanting of U-boot and uClinux system, the improved moving object examination algorithm using the difference of background was proposed based on the software platform constructed. Finally, the debug process of the unit circuit of the whole system is introduced in proper sequence. As a result, the digital image collecting system based on ARM S3C44B0X exists as a sole unit, and has lots of advantages such as small volume, low cost, good expansion, multifunctional and low power consumption. The system realized the functions of real-time video acquisition and processing. Combined with the GPS module and other sensors, the system can be widely used in the aspects of agricultural environmental monitoring, real-time data acquisition and remote monitoring and so on, with a more broad application prospects.

Grassland Carbon Sequestration Ability in China: A New Perspective from Terrestrial Aridity Zones ☆

ABSTRACT Current climate change (e.g., temperature and precipitation variations) profoundly influences terrestrial vegetation growth and production, ecosystem respiration, and nutrient circulation. Grasslands are sensitive to climate change, and the carbon sequestration ability is closely related to water availability. However, how the terrestrial water budget influences regional carbon sequestration by the grassland ecosystem is still unclear. In this study, we modified a terrestrial biogeochemical model to investigate net ecosystem productivity (NEP) of Chinese grasslands under different aridity index (AI) levels from 1982 to 2008. The results showed that Chinese grasslands acted as a carbon sink of 33.7 TgC. yr-1, with a clear decrease in the spatial distribution from the humid end (near-forest) to the arid end (near-desert). During these 27 years, gross primary productivity (GPP) and net primary productivity (NPP) significantly increased with regional warming over the entire range of the AI, but no significant tendency was found for NEP. Meanwhile, only NPP in the arid zone (AR) and the semiarid zone (SAR) were significantly correlated with mean annual precipitation (MAP), and no significant correlation was found between heterotrophic respiration (Rh and MAP; NPP and Rh were both positively correlated with mean annual temperature (MAT) in all AI zones except for NPP in AR; no significant correlation between NEP and MAP or MAT was found. These results revealed that the grasslands with different AI levels keep different response patterns to temperature and precipitation variations. On the basis of these results, we predicted that the gap of carbon sequestration ability between humid and arid grassland will expand. The total carbon sink in Chinese grasslands will continue to fluctuate, but there is a danger that it might shrink in the future because of a combination of climatic and human factors, although CO2 fertilization and N deposition might partly mitigate this reduction.

The comparisons of carbon sink/source of Chinese grassland ecosystem using different approaches

Grassland ecosystem, one of the widely distributed vegetation type, is of great significance in estimation of global carbon cycle. The grassland net primary productivity (NPP) plays an important role in global change and carbon balance; it is always used as an index of C cycle in terrestrial ecosystems at landscape and regional scales. This paper compaired grassland net primary productivity (NPP) estimation methods, including filed observation and models (mainly climate productivity model, process model and light energy use efficiency model). As every method has its limited, it was convenient and prompt to estimate NPP using remote sensing data and could achieve fast monitoring of all kinds of vegetation. Meanwhile, these researches, such as influence on the terrestrial ecosystem carbon source/sink caused by climate change and atmospheric CO2 increase and effects on carbon cycle caused by terrestrial ecosystems type conversion, are not studied enough; either scene simulation based on models or contrast studies, there is even larger gap in this research in China. Therefore, we studied the NPP of the main grassland in China( Sinkiang, Inner Mongolia, grassplot in Southern China) using the Remote Sensing(RS), Geography Information System(GIS), modified Cellular Automata(CA) and integrated model with high precision testified by MODIS data and meteorological data, which is much more suitable for grassland in China, and extend to the Europe and North America, then grassland ecosystem carbon source/sink estimation using remote sensing data is proposed. The results will provide the scientific basis for the government to account grassland carbon balance and carbon storage in the future. Under the condition of increasing measuring precision and region density, it is superior to use remote sensing in grassland NPP measurement, which provides baseline for the terrestrial carbon cycle mechanism and global carbon balance research.

Evaluating the responses of net primary productivity and carbon use efficiency of global grassland to climate variability along an aridity gradient

Net primary productivity (NPP) and carbon use efficiency (CUE) are common ecological indicators for assessing the terrestrial carbon cycle. However, despite their widespread use, considerable uncertainties exist toward the response patterns of NPP and CUE to climate variability along an aridity gradient, especially for grassland ecosystems. The aridity index (AI) was calculated in this study to specify arid-humid zones across the global grassland ecosystem. The dynamics of grassland NPP, CUE, and their dependence on climate under different AI levels from 2000 to 2013 were investigated. Results showed that the NPP and CUE of grasslands demonstrated a slightly increasing trend with regional increasing precipitation in most AI zones, except for arid regions (AR) from 2000 to 2013. The NPP and CUE of grasslands exhibited a remarkable spatial heterogeneity in different AI zones. High NPP values mainly occurred in the dry and sub-humid (DSH) and humid (HU) regions of Southern Hemisphere with warm and wet climate. High CUE values were mostly found in the HU of the Northern Hemisphere with cold and wet climate. In addition, low NPP and CUE values were observed in most parts of AR and semi-AR (SAR) with hot and dry climate. Overall, the NPP and CUE of grasslands were significantly affected by precipitation at the global scale. Specifically, grassland NPP was positively correlated with the mean annual precipitation (MAP) in SAR and AR, but negatively related with the MAP in the HU region. The positive correlation between NPP and mean annual temperature (MAT) was found only for HU regions. Grassland CUE indicated a positive relation with MAP, but a negative relation was observed with MAT in all AI zones. The correlation coefficients between CUE and MAP decreased from AR to HU regions. This finding indicated that grassland CUE was highly sensitive to precipitation in dry areas, but this relationship weakened in HU ecosystems.

Comparative Study on LUCC and CLID of Zhangjiagang, Hanoi and Dehradun in the developing countries of Asia-Pacific region: A real challenge to food security

Three cities with different degrees of urbanization in developing countries of Asia-Pacific region are selected as the study areas, They are Zhangjiagang city in China, Dehradun in India and Hanoi in Vietnam. In this paper, data was collected concluding nearly a decade of remote sensing data, population, economic data and other relevant information. We studied land-use and land-cover change (LUCC) and cultivated land instability degree (CLID) of three cities by the means of spatial analysis and CA model analysis supported by the 3S technology. The results show that: All three cities have significant land use/land cover (LULC) changes under the background of urbanization over the past decade, mainly in the increase of urban land and reduction of agricultural land. The changes of Dehradun is the greatest, Hanoi second, and Zhangjiagang city is the smallest; The CLID value shows the pressure size of transformation for the cultivated land in Zhangjiagang, Dehradun and Hanoi. Among three cities, the pressure of cultivated land in Dehradun is the greatest. Hanoi is the second, the minimum is Zhangjiagang. Facing the changes, rapid urbanization is increasing the risk of food security. Local government should make positive policy to the challenge of decreasing availability of cultivated land and offer unremitting efforts towards the goal of food security.