Papers by Keyword: Spatial Distribution Pattern

Abstract: Using methods of spatial autocorrelation analysis and trend analysis, the paper studies the spatial distribution pattern of NDVI based on the GIMMS NDVI dataset (1998-2008), in Western Jilin. The maximum value for 15d is got through the method of MAX processing. Results show that: the NDVI in growing season shows a rising trend in western Jilin in 1998-2008. In the study area, the NDVI in Western Jilin shows positive spatial autocorrelation in the whole region, but the partial NDVI is apt to scattered distribution, which means the vegetation cover of Western Jilin is generally fragmental.

Abstract: The aim of this study was to investigate the spatial distribution patterns and the amounts of seedling density of S. pennata in different sample dunes in Gurbantonggut Desert. Results indicate that spatial patterns of seedling emergence of S. pennata were of general similar with the distribution patterns of its associated standing vegetations, and was greatly associated with spatial distribution of the threshold wind (≥6m.s^-1) frequency from the various directions. There existed a significant difference in its seedling emergence patterns among the different parts of the dunes and the different directions around its parent vegetation beds. The highest seedling density was found to be on the top parts of sampling dunes and at the underlayer of standing vegetation beds of S. pennata, and higher seedling densities usually took place in the leeward side of the vegetation beds. These results had revealed the ecological characteristics of the population distribution rule and the recruitments mechanism of S. pennata.

Abstract: Field data were sampled by the method of contiguous grid quadrate. The spatial patterns of Pseudolarix amabilis populations were studied by the following methods: DispItalic textersal index (C), David moores index (I), Lloyd index (m*/m), Morisita index (Iδ), Parameter of negative index (K) and Cassie index (1/K). The quadrate variance analysis, Greig-Smith and Kershaw methods were used to study the spatial distribution pattern, pattern scale and pattern intensity of Pinus armandi population at different sizes. The result showed that P. amabilis population is most clumped. The result indicated the pattern intensity was decreasing with the size increasing and a single peak value appeared in the curve with the area increasing. There was a slow change in the pattern intensity of population, which means a smaller variation in environment and a bigger difference in the relative density of population patches during diffusion process.