[Water sources of Picea schrenkiana and Berberis heteropoda in the Tianshan Mountains in summer]. / 天山林区雪岭云杉和异果小檗夏季水分来源.

Water use patterns of trees and shrubs in the Picea schrenkiana coniferous forest remain unclear, due to a lack of quantitative analysis on water use dynamics. In this study, the xylem water hydrogen and oxygen stable isotope compositions of P. schrenkiana and the companion shrub species Berberis heteropoda were measured to detect their water sources. The IsoSource model was used to analyze the relative contribution of each potential water source for both species during summer. The results showed that during July, P. schrenkiana and B. heterocarpa mainly extracted water from the 0-60 cm soil layer due to the relatively sufficient soil water content, with the relative contributions being 73.8% and 63.2% for the two species, respectively. In August, with the decreases in soil water content, water source of P. schrenkiana remained stable, and the relative contribution of soil water above 60 cm was 69.5%. In contrast, B. heterocarpa reverted to water source from deeper soil layer, with the relative contribution of shallow soil (0-20 cm) water decreasing to 14.3% and that of middle (20-60 cm) to deep (60-100 cm) soil water increased to 67.7%. In September, with the increases of water content in the shallow soil layer, both species extracted water from shallow soil layers, with the relative contribution reaching to 95.0%. In summary, P. schren-kiana exhibited typical shallow root characteristics, while B. heterocarpa extracted water from the 0-100 cm soil profile and could flexibly change its water source corresponding to changes in soil water content to cope with changing environmental water condition.

[Spatial distribution pattern of Picea schrenkiana var. tianshanica population and its relationships with topographic factors in middle part of Tianshan Mountain].

By the method of point pattern analysis, this paper studied the spatial distribution patterns of different age class individuals in the Picea schrenkiana var. tianshanica forest in middle part of Tianshan Mountain and the influence of topographic factors on the distribution patterns. It was observed that the density of different age class individuals in the forest decreased with the increasing DBH of the individuals, and except old trees which presented a random distribution at the scale of 0-12 m, the saplings and the small, medium, and big trees were in aggregative distribution at all scales. With the increase of age class, the scale at which the individuals presented the highest aggregation degree increased, whereas the aggregation intensity declined. At small scale (0-16 m), different age class individuals appeared negative association, and the greater difference the tree age, the more significant the negative association presented. Altitude had significant positive effects on the number of medium, big, and old trees but had little effects on the number of saplings and small trees. Slope grade had significant positive effects on the number of saplings and small and medium trees, significant negative effects on the number of old trees, but little effects on the number of big trees. Concavo-convex had significant negative effects on the number of saplings and small and medium trees but had little effects on the number of big and old trees.

[Markov process of vegetation cover change in arid area of northwest China based on FVC index].

Based on the fractional vegetation cover (FVC) data of 1982-2000 NOAA/AVHRR (National Oceanic and Atmospheric Administration/ the Advanced Very High Resolution Radiometer) images, the whole arid area of Northwest China was divided into three sub-areas, and then, the vegetation cover in each sub-area was classified by altitude. Furthermore, the Markov process of vegetation cover change was analyzed and tested through calculating the limit probability of any two years and the continuous and interval mean transition matrixes of vegetation cover change with 8 km x 8 km spatial resolution. By this method, the Markov process of vegetation cover change and its indicative significance were approached. The results showed that the vegetation cover change in the study area was controlled by some random processes and affected by long-term stable driving factors, and the transitional change of vegetation cover was a multiple Markov process. Therefore, only using two term image data, no matter they were successive or intervallic, Markov process could not accurately estimate the trend of vegetation cover change. As for the arid area of Northwest China, more than 10 years successive data could basically reflect all the factors affecting regional vegetation cover change, and using long term average transition matrix data could reliably simulate and predict the vegetation cover change. Vegetation cover change was a long term dynamic balance. Once the balance was broken down, it should be a long time process to establish a new balance.