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The electro-osmotic peristaltic flow of a viscoelastic fluid through a cylindrical micro-channel is studied in this paper. The fractional Jeffreys constitutive model, including the relaxation time and retardation time, is utilized to describe the viscoelasticity of the fluid. Under the assumptions of long wavelength, low Reynolds number, and Debye-Hückel linearization, the analytical solutions of pressure gradient, stream function and axial velocity are explored in terms of Mittag-Leffler function by Laplace transform method. The corresponding solutions of fractional Maxwell fluid and generalized second grade fluid are also obtained as special cases. The numerical analysis of the results are depicted graphically, and the effects of electro-osmotic parameter, external electric field, fractional parameters and viscoelastic parameters on the peristaltic flow are discussed. [ABSTRACT FROM AUTHOR]

We improved the CASA model based on differences in the types of land use, the values of the maximum light use efficiency, and the calculation methods of solar radiation. Then, the parameters of the model were examined and recombined into 16 cases. We estimated the net primary productivity (NPP) using the NDVI3g dataset, meteorological data, and vegetation classification data from the Greater Khingan Mountain region, China. We assessed the accuracy and temporal-spatial distribution characteristics of NPP in the Greater Khingan Mountain region from 1982 to 2013. Based on a comparison of the results of the 16 cases, we found that different values of maximum light use efficiency affect the estimation more than differences in the fraction of photosynthetically active radiation (FPAR). However, the FPARmax and the constant T∈2 values did not show marked effects. Different schemes were used to assess different model combinations. Models using a combination of parameters established by scholars from China and the United States produced different results and had large errors. These ideas are meaningful references for the estimation of NPP in other regions. The results reveal that the annual average NPP in the Greater Khingan Mountain region was 760 g C/m².a in 1982-2013 and that the inter-annual fluctuations were not dramatic. The NPP estimation results of the 16 cases exhibit an increasing trend. In terms of the spatial distribution of the changes, the model indicated that the values in 75% of this area seldom or never increased. Prominent growth occurred in the areas of Taipingling, Genhe, and the Oroqen Autonomous Banner. Notably, NPP decreased in the southeastern region of the Greater Khingan Mountains, the Hulunbuir Pasture Land, and Holingol. [ABSTRACT FROM AUTHOR]

Time series of Normalized Difference Vegetation Index (NDVI) derived from multiple satellite sensors are crucial data to study vegetation dynamics. The Land Long Term Data Record Version 4 (LTDR V4) NDVI dataset was recently released at a 0.05 × 0.05° spatial resolution and daily temporal resolution. In this study, annual NDVI time series that are composited by the LTDR V4 and Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI datasets (MOD13C1) are compared and evaluated for the period from 2001 to 2014 in China. The spatial patterns of the NDVI generally match between the LTDR V4 and MOD13C1 datasets. The transitional zone between high and low NDVI values generally matches the boundary of semi-arid and sub-humid regions. A significant and high coefficient of determination is found between the two datasets according to a pixel-based correlation analysis. The spatially averaged NDVI of LTDR V4 is characterized by a much weaker positive regression slope relative to that of the spatially averaged NDVI of the MOD13C1 dataset because of changes in NOAA AVHRR sensors between 2005 and 2006. The measured NDVI values of LTDR V4 were always higher than that of MOD13C1 in western China due to the relatively lower atmospheric water vapor content in western China, and opposite observation appeared in eastern China. In total, 18.54% of the LTDR V4 NDVI pixels exhibit significant trends, whereas 35.79% of the MOD13C1 NDVI pixels show significant trends. Good agreement is observed between the significant trends of the two datasets in the Northeast Plain, Bohai Economic Rim, Loess Plateau, and Yangtze River Delta. By contrast, the datasets contrasted in northwestern desert regions and southern China. A trend analysis of the regression slope values according to the vegetation type shows good agreement between the LTDR V4 and MOD13C1 datasets. This study demonstrates the spatial and temporal consistencies and discrepancies between the AVHRR LTDR and MODIS MOD13C1 NDVI products in China, which could provide useful information for the choice of NDVI products in subsequent studies of vegetation dynamics. [ABSTRACT FROM AUTHOR]

Grassland fire is one of the most important disturbance factors of the natural ecosystem. Climate factors influence the occurrence and development of grassland fire. An analysis of the climate conditions of fire occurrence can form the basis for a study of the temporal and spatial variability of grassland fire. The purpose of this paper is to study the effects of monthly time scale climate factors on the occurrence of grassland fire in HulunBuir, located in the northeast of the Inner Mongolia Autonomous Region in China. Based on the logistic regression method, we used the moderate-resolution imaging spectroradiometer (MODIS) active fire data products named thermal anomalies/fire daily L3 Global 1km (MOD14A1 (Terra) and MYD14A1 (Aqua)) and associated climate data for HulunBuir from 2000 to 2010, and established the model of grassland fire climate index. The results showed that monthly maximum temperature, monthly sunshine hours and monthly average wind speed were all positively correlated with the fire climate index; monthly precipitation, monthly average temperature, monthly average relative humidity, monthly minimum relative humidity and the number of days with monthly precipitation greater than or equal to 5 mm were all negatively correlated with the fire climate index. We used the active fire data from 2011 to 2014 to validate the fire climate index during this time period, and the validation result was good (Pearson’s correlation coefficient was 0.578), which showed that the fire climate index model was suitable for analyzing the occurrence of grassland fire in HulunBuir. Analyses were conducted on the temporal and spatial distribution of the fire climate index from January to December in the years 2011–2014; it could be seen that from March to May and from September to October, the fire climate index was higher, and that the fire climate index of the other months is relatively low. The zones with higher fire climate index are mainly distributed in Xin Barag Youqi, Xin Barag Zuoqi, Zalantun Shi, Oroqen Zizhiqi, and Molidawa Zizhiqi; the zones with medium fire climate index are mainly distributed in Chen Barag Qi, Ewenkizu Zizhiqi, Manzhouli Shi, and Arun Qi; and the zones with lower fire climate index are mainly distributed in Genhe Shi, Ergun city, Yakeshi Shi, and Hailar Shi. The results of this study will contribute to the quantitative assessment and management of early warning and forecasting for mid-to long-term grassland fire risk in HulunBuir. [ABSTRACT FROM AUTHOR]

Grassland, as one of the most important ecosystems on Earth, experiences fires that affect the local ecology, economy and society. Notably, grassland fires occur frequently each year in northeastern China. Fire occurrence is a complex problem with multiple causes, such as natural factors, human activities and land use. This paper investigates the disruptive effects of grassland fire in the northeastern Inner Mongolia Autonomous Region of China. In this study, we relied on thermal anomaly detection from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor to identify fire occurrences, and land use data were acquired by Landsat Thematic Mapper/Enhanced Thematic Mapper (TM/ETM). We discussed the relationship between land use and the spatial distribution of grassland fires. The results showed that the impact of land use on grassland fires was significant. Spatially, approximately 80% of grassland fires were clustered within 10 km of cultivated land, and grassland fires generally occurred in areas of intense human activity. The correlation between the spatial distribution of grassland fires and the land use degree in 2000, 2005 and 2010 was high, with R2 values of 0.686, 0.716, 0.633, respectively (p < 0.01). These results highlight the importance of the relationship between land use and grassland fire occurrence in the northeastern Inner Mongolia Autonomous Region. This study provides significance for local fire management and prevention. [ABSTRACT FROM AUTHOR]

Vegetation is an important part of terrestrial ecosystems. Although vegetation dynamics have explicit spatial and temporal dimensions, the study of the temporal process is in its infancy. Evaluation of temporal scaling behavior could provide a unique perspective for exploring the temporal nature of vegetation dynamics. In this study, the Global Inventory Modeling and Mapping Studies (GIMMS) Normalized Difference Vegetation Index (NDVI) was used to reflect vegetation dynamics, and the temporal scaling behavior of the NDVI in China was determined via detrended fluctuation analysis (DFA). Our main objectives were to reveal the temporal scaling behavior of NDVI time series and to understand variation among vegetation types. First, DFA revealed similar exponents, which ranged from 0.6 to 0.9, for all selected pixels, implying that a long-range correlation was generally present in the NDVI time series at the individual pixel scale. We then extended the analysis to all of China and found that 99.30% of the pixel exponents ranged from 0.5 to 1. These results suggest that the NDVI time series displays strong long-range correlation throughout most of China; however, the exponents exhibited regional variability. To explain these differences, we further analyzed the exponents for 12 vegetation types based on a vegetation map of China. All of the vegetation types exhibited well-defined long-range correlation, with exponents ranging from 0.7189 to 0.8436. For all vegetation types, the maximum and average value and standard deviation of the exponents decreased with increasing annual maximum NDVI values, suggesting that low vegetation density is much more sensitive to external factors. These findings may be useful for understanding vegetation dynamics as a complex, temporally varying phenomenon. [ABSTRACT FROM AUTHOR]

Vegetation phenology is a key biological indicator for monitoring terrestrial ecosystems and global change, and regions with the most obvious phenological changes in vegetation are primarily located at high latitudes and altitudes. Over the past three decades, investigations of obvious phenological changes in vegetation at middle and high latitudes in the Northern Hemisphere have provided significant contributions to understanding global climate change. In this study, phenological parameters were extracted from the Global Inventory Modeling and Mapping Studies (GIMMS) Normalized Difference Vegetation Index (NDVI3g) to analyze the spatial and temporal characteristics of vegetation phenological changes above 40°N in the Northern Hemisphere from 1982-2013. The results showed that the start of season (SOS) was significantly advanced (-2.2 ± 0.6 days·decade-1, p < 0.05) and that the end of season (EOS) was slightly delayed (0.78 ± 0.6 days·decade-1, p = 0.21) over the entire study area in the initial 21 years (1982-2002). When the time scale was extended to 2013, the change rate of the SOS and EOS was significantly reduced; in addition, the SOS was delayed (3.2 ± 1.7 days·decade-1, p < 0.05), and the EOS was advanced (4.5 ± 0.9 days·decade-1, p < 0.05) over the entire study area in the last 11 years (2003-2013). The trends of advanced SOS and delayed EOS over the past three decades were slower than those over the initial two decades on a hemispheric scale. The change trends showed obvious variability with different vegetation types and were greater for woody plants than for herbaceous plants. For broad-leaved forest, the SOS was significantly advanced (2 ± 0.5 days·decade-1, p < 0.05) and the EOS was significantly delayed (2.7 ± 0.6 days·decade-1, p < 0.05) from 1982-2013. The trend of delayed EOS was greater than that of advanced SOS for different vegetation types. With respect to the spatial distribution of phenological trends in the Northern Hemisphere, the trends of advanced SOS and delayed EOS were strongest in Europe followed by North America, and the trends were least significant in Asia. Coniferous forest, shrub forest, grassland, and the entire study area have the same change trends for the two time periods (1982-2002 and 2003-2013), and the increased rate of the phenology parameters has decelerated over the most recent decade. The length of season (LOS) of broad-leaved forest and mixed forest over the past 32 years shows a strong increased trend, and simultaneously, the SOS and EOS show an advanced trend and a delayed trend, respectively. [ABSTRACT FROM AUTHOR]