Quantitative Classification and Ordination of Plant Communities in the Upper and Middle Reaches of the Yarlung Zangbo River Basin

Based on vegetation survey data and environmental data of the Yarlung Zangbo River Basin, we conducted a quantitative ecological analysis of the vegetation community composition and the relationship between species and the environment in the study area. The results showed that 44 sampling sites and 68 plant species in the study area can be classified into seven subtypes: Artemisia minor + Stipa purpurea;Artemisia demissa + Stipa purpurea + Artemisia wellbyi;Kobresia pygmaea;Trikeraia hookeri;Sophora moorcroftiana + Cotoneaster multiflorus + Pennisetum centrasiaticum;Artemisia frigida;Potentilla fruticosa + Orinus thoroldii. Detrended correspondence analysis(DCA) indicated that both longitude and altitude play important roles in site and species distribution patterns. In addition, canonical correspondence analysis(CCA) revealed that in the upper and middle reaches of the Yarlung Zangbo River Basin, changes in temperature and precipitation caused by longitude are the main factors controlling the formation and transition of vegetation community types. Moreover, natural vegetation could be divided into three types: desert steppe community(source area), alpine steppe community(middle reaches region), and shrub community(confluence of Yarlung Zangbo River and Nyangqu River).

The quantitative classification of granites and their metallogenetic relations in West Qinling,Gansu Province,China

The quantitative classification of granite and their metallogenetic relations have never been discussed.The Q-system clustering analysis and discriminant analysis methods were alternately used to quantitatively analyze the 11 oxide data in granite samples from the West Qinling area of Gansu Province,and then to construct the quantitative classification series models of granite(oxide).The granites samples are divided into three categories and eight subcategories.The classification of granites is biased toward prospecting.According to the spatial correlation between eight types of granites and copper deposits,lead and zinc deposits,gold deposits,etc.(within 3 km of the intrusion)in the West Qinling area in Gansu Province,the“metallogenic related intrusions”are sought,and the prospecting target areas are defined.Furthermore,they provide reliable basis for regional geological prospecting.

Application of self-organizing neural networks to classification of plant communities in Pangquangou Nature Reserve, North China

Vegetation classification is an important topic in plant ecology and many quantitative techniques for classification have been developed in the field.The artificial neural network is a comparatively new tool for data analysis.The self-organizing feature map(SOFM)is powerful tool for clustering analysis.SOFM has been applied to many research fields and it was applied to the classification of plant communities in the Pangquangou Nature Reserve in the present work.Pangquangou Nature Reserve,located at 37°20′–38°20′ N,110°18′–111°18′ E,is a part of the Luliang Mountain range.Eighty-nine samples(quadrats)of 10 m×10 m for forest,4 m×4 m for shrubland and 1 m×1 m for grassland along an elevation gradient,were set up and species data was recorded in each sample.After discussion of the mathematical algorism,clustering technique and the procedure of SOFM,the classification was carried out by using NNTool box in MATLAB(6.5).As a result,the 89 samples were clustered into 13 groups representing 13 types of plant communities.The characteristics of each community were described.The result of SOFM classification was identical to the result of fuzzy c-mean clustering and consistent with the distribution patterns of vegetation in the study area and shows significant ecological meanings.This suggests that SOFM may clearly describe the ecological relationships between plant communities and it is a very effective quantitative technique in plant ecology research.