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Topsoil characteristics and their determinants in the steppe on the central Inner Mongolian Plateau were investigated. Percentages of different grain size fractions of topsoil samples from 236 plots and corresponding standardized data of four environmental/human‐activity factors, namely mean annual temperature (MAT), mean annual precipitation (MAP), human disturbance index (HDI) and land use/land cover (LULC) types were used to perform canonical correspondence analysis (CCA). The roles of both human land uses and climatic factors on topsoil grain size distribution are highlighted. Climatic factors seem to have played a significant role in determining the coarse sand (0.2–1 mm in size) percentages in the steppe and meadow by affecting the vegetation cover, while human disturbance indicated by species composition appears to have significantly influenced the percentages of clay (<0.002 mm in size) and fine‐medium silt (0.002–0.016 mm in size) in the typical steppe (P < 0.01). Soil Organic Carbon (SOC) content is negatively correlated with coarse sand percentages (P < 0.01), implying that reduction of soil fertility is linked to soil coarsening. Percentages of fine‐medium silts (0.002–0.016 mm in size) are still more abundant in the area where artificial vegetation are planted and remains as the major source of dust storms. This study implies that afforestation in the steppe region has not improved soil conditions and thus reduced dust storms as earlier expected.

Vegetation classification models play an important role in studying the response of the terrestrial ecosystem to global climate change. In this paper, we study changes in global Potential Natural Vegetation (PNV) distributions using the Comprehensive Sequential Classification System (CSCS) approach, a technique that combines geographic information systems. Results indicate that on a global scale there are good agreements among maps produced by the CSCS method and the globally well-accepted Holdridge Life Zone (HLZ) and BIOME4 PNV models. The potential vegetation simulated by the CSCS approach has 6 major latitudinal zones in the northern hemisphere and 2 in the southern hemisphere. In mountainous areas it has obvious altitudinal distribution characteristics due to topographic effects. The distribution extent for different PNV classes at various periods has different characteristics. It had a decreasing trend for the tundra and alpine steppe, desert, sub-tropical forest and tropical forest categories, and an increasing trend for the temperate forest and grassland vegetation categories. The simulation of global CSCS-based PNV classes helps to understand climate-vegetation relationships and reveals the dynamics of potential vegetation distributions induced by global changes. Compared with existing statistical and equilibrium models, the CSCS approach provides similar mapping results for global PNV and has the advantage of improved simulation of grassland classes.

A novel method based on Pulse Coupled Neural Network(PCNN) algorithm for the highly accurate and robust compass information calculation from the polarized skylight imaging is proposed,which showed good accuracy and reliability especially under cloudy weather,surrounding shielding and moon light. The degree of polarization (DOP) combined with the angle of polarization (AOP), calculated from the full sky polarization image, were used for the compass information caculation. Due to the high sensitivity to the environments, DOP was used to judge the destruction of polarized information using the PCNN algorithm. Only areas with high accuracy of AOP were kept after the DOP PCNN filtering, thereby greatly increasing the compass accuracy and robustness. From the experimental results, it was shown that the compass accuracy was 0.1805° under clear weather. This method was also proven to be applicable under conditions of shielding by clouds, trees and buildings, with a compass accuracy better than 1°. With weak polarization information sources, such as moonlight, this method was shown experimentally to have an accuracy of 0.878°.

Bamboo and Miscanthus species are perennial low-input plants that are excellent candidates for bioenergy feedstock production. Biological characteristics, dry matter yields and fuel properties of the bamboo and Miscanthus have been studied. Genotype growth characteristics were determined by measurements of plant height, tillering, tuft diameter, and shoot diameter. To date, comparisons of biomass yields of bamboo and Miscanthus have not been previously reported in the literature. Bamboo and Miscanthus species were collected and previous articles describing the productivity of bamboo and Miscanthus were examined. Genotypes differed in plant height, tillering, tuft diameter, and shoot diameter. Nitrogen, temperature, water and plant density have effects on mature stands biomass production, which ranged from 5.9 to 49.5 tonnes/ha/yr for bamboo and 3.2 to 49.0 tonnes/ha/yr for Miscanthus. With such biomass yields, bamboo and Miscanthus should be considered as two very promising plants for biomass production in Zhejiang, China in the near future.

This study investigates vegetation responses to climate changes by analyzing 19 years (1982–2000) of both climatic data and growing season Normalized Difference Vegetation Index (NDVI) for vertically distributed desert, steppe, forest and meadow, in the middle part of the northern slope of Tianshan Mountains. Vegetation activity exhibited greening trend in all biomes, owing mainly to reduction of water stress caused by increasing precipitation, although warming trend negated that effect because of temperature‐induced drought. Precipitation acted as a remarkable driving force of plant growth in each biome through the whole growing season (spring, summer, autumn), its effect could always persist into the next season, however, the sensitivity decreased across biomes with increasing precipitation. Warming‐induced snow melt played a positive role in boosting plant growth during spring in steppe, forest and meadow. Except that, warming produced negative effects.

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Alpine meadow plays important roles in the animal production and conservation of water resources in the upper basin of Yellow River. In recent decades, desertification of this alpine meadow has resulted in changes in vegetation and soil features, as well as threatening the ecosystem functions and security. A field study was conducted to explain the response of vegetation pattern and soil features to desertification of alpine meadows. Results of vegetation studies indicated that hygrophytes were gradually replaced by mesophytes, xerophytes, and some annual psammophilous plants, and that cover and herbaceous biomass decreased along with the progressive desertification. Vegetation height increased in the slightly desertified stage, and then decreased in the very severe stage. Species diversity decreased, suggesting that desertification of alpine meadow contributedto species loss. This study also indicated that soil features gradually declined with increasing desertification of alpine meadow with A07027;