Microbial production of CO_2 in red soil in Stone Forest National Park

Lunan stone forest is a kind of typical karst in China, which is mainly developed under red soil. In the winter of 1999, three study sites were chosen in stone forest national park according to vegetation cover, geomorphologic location and soil types. CO 2 concentration was measured with Gastec pump at different depths of soil (20, 40, 60 cm) and at the same time soil samples were gathered and soil properties such as soil moisture, pH, soil organic content were analyzed and the total number of viable microbes were counted in laboratory. In the study, dependent variable was chosen as the mean soil log (PCO 2 ), and soil properties were chosen as the independent variables. Multiple stepwise regression analysis showed that the total amount of microbes and soil moisture are the best indicators of the CO 2 production, with the equation LOG(PCO 2 ) = - 0.039(TNM) - 0.056(Mo) + 1.215 accounting for 86% of the variation of the soil CO 2 concentration, where TNM is the total number of microbes in the soil and Mo is the moisture of soil sample.

Theoretical derivation of risk-ratios for assessing wind damage in a coastal forest

Based on the discussion of relationships between thinning and wind damage, and published information, a method for estimating risk ratios of wind damage was developed. Estimations of risk-ratio for Pinus thunbergii trees and stands were de-duced from stem bending theory and coefficients characterizing wind profile, distribution of branches and optical stratification po-rosity. The results showed that if the value of constant b in the branch distribution-model equals the attenuation coefficient s in the wind profile model for a single tree crown, then the parameter H/D1.33 (height over stem diameter cubed) can be used to compare and evaluate the risk-ratio of wind damage for individual trees. The same method can be applied to stands using the coefficient of wind profile in a stand, i.e. attenuation coefficient , the coefficient from distributions of optical stratification porosity, i.e. extinction coefficient , and the parameter D1.33. The application of parameter H/D1.33 and the process of determining risk ra-tios of wind damage for stands were also given in the paper.

Forest landscape patterns dynamics of Yihe-Luohe river basin

Based on the information from forest resources distribution maps of Luoning County of 1983 and 1999, six indices were used to analyze spatial patterns and dynamics of forest landscapes of the typical region in the middle of the Yihe-Luohe river basin. These indices include patch number, mean patch area, fragment index, patch extension index, etc. The results showed that: (1) There was a rapid increase in the number of patch and total area from 1983 to 1999 in the study area. The fragment degree became very high. (2) The area of all the forest patch types had witnessed great changes. The fractal degree of each forest patch type became big from 1983 to 1999. The mean extension index of Robinia pseudoacacia forest, non-forest, shrub forest, sparse forest, and Quercus species forest increased rapidly, but that of economic forest became zero. The fractal dimension each showed that forest coverage has been promoted. (3) The changes of landscape patterns were different in different geomorphic regions. From 1983 to 1999 the vegetation cover area, the gross number and the density of patch, diversity and evenness of landscape were all reduced greatly in gullies and ravines, but the maximum area and the mean area of patch types were increased. In hilly region, both the forest cover area and the number of patch increased from 1983 to 1999, but the mean area of patch was reduced greatly. In mountain region, even though the area under forest canopy reduced from 1983 to 1999, the patch number was increased greatly, the mean area of all patch types was reduced, the extension index, diversity index and evenness index of landscape were all increased. Furthermore, because of different types of land use, human activity and terrain, the vegetation changes on northern and southern mountain slopes were different. According to these analyses, the main driving forces, such as the policies of management, market economy, influence of human activities etc. are brought out.