关键词: 黑河下游, 荒漠河岸林, 种群斑块, 空间异质性

Abstract: Geo-statistical techniques are used to evaluate spatial characteristics of the desert riparian forest at the down stream of the Hei River in the arid area of northwest China. Spatial structures of different vegetation populations were characterized by means of nugget, range and sill parameters of spherical or exponent model variograms. Model variograms reveal that different vegetation populations have distinctive spatial properties, which are quantified effectively by the parameters of the models. Model variograms were fitted to the experimental variograms, which were calculated from width of plant bosom and vegetation coverage measured at 1 sampling transect of 2 000 m×5 m, 5 sampling transects of 500 m×5 m and 3 sampling transects of 200 m×2 m. Transects of 2 000 m×5 m were laid out between river and desert, the other transects were laid out in different vegetation populations. Desert riparian forests in the Hei River Basin show the spatial distributive pattern of patchiness, the main populations are older Populus euphratica; younger Populus euphratica; Tamarix chinensis; Sophora alopecuroides and so on. The maximum model variogram range was 55 m for all populations, suggesting that transects must at least be such long to classify the riparian forests unambiguously into the populations currently recognized. Experimental variograms were calculated for all plants in each of four mapped vegetation populations. The Tamarix chinensis and Sophora alopecuroides populations have distinctively long range, but the spatial heterogeneity of Populus euphratica populations has multiscale changes. At the scale of community, spatial heterogeneity of vegetation increases and also has multiscale changes. According to analyses, the spatial heterogeneity of community has distinctive change at the scale of 400 m, and this is also the scale of population patchiness turnover. These findings support use of high-resolution remote sensors and geostatistics for determining vegetation community structure of desert riparian forests. Spatial pattern information produced by these methods could improve broad scale vegetation classifications produced by low-resolution remote sensing systems.

Key words: lower reaches of Hei River Basin, desert riparian forest, population patch, spatial heterogeneity