Spatial pattern of tree diversity and evenness across forest types in Majella National Park,Italy

Background： Estimation of tree diversity at broader scale is important for conservation planning. Tree diversity should be measured and understood in terms of diversity and evenness, two integral components to describe the structure of a biological community. Variation of the tree diversity and evenness with elevation, topographic relief, aspect, terrain shape, slope, soil nutrient, solar radiation etc. are well documented. Methods： Present study explores the variation of tree diversity （measured as Shannon diversity and evenness indices） of Majella National Park, italy with five available forest types namely evergreen oak woods, deciduous oak woods, blacWaleppo pine stands, hop-hornbeam forest and beech forest, using satellite, environmental and field data. Results： Hop-hornbeam forest was found to be most diverse and even while evergreen Oak woods was the lowest diverse and even. Diversity and evenness of forest types were concurrent to each other i.e. forest type which was more diverse was also more even. As a broad pattern, majority portion of the study area belonged to medium diversity and high evenness class. Conclusions： Satellite images and other GIS data proved useful tools in monitoring variation of tree diversity and evenness across various forest types. Present study findings may have implications in prioritizing conservation zones of high tree diversity at Majella.

Resource selection of moose(Alces alces cameloides) and their response to human disturbances in the northwestern slope of Lesser Khingan Mountains, northeastern China

Moose （Alces alces cameloides） is typically representative of the fauna of the frigid temperate zone and has been put on the Chinese second priority list of protected animals. The moose of northeast China is on the southern most edge of its distribution in Asia. To study resource selection characteristics of moose and their response to human distur- bances and forest resource variables, the field work was conducted in Heilongiiang Provincial Shengshan Forestry Farm, which is located in the northwestern slope of Lesser Khingan Mountains, northeastern China, from January to March in both 2006 and 2007. A total of 428 plots were examined within the study area. Signs of moose use were found in 19 plots. Based on the analysis of resource selection function, we found that moose selected areas with higher densities of mixed deciduous broadleaf patch and mixed coniferous and broad leaf patch, and a higher NDVI value. Moose avoided settlement 6 km away and remained low probability of occurrence within 3 km from roads,

Boundary Recognition of Light-Pause Marks via Grammar Testing Method

Boundary recognition is an important research of natural language processing, and it provides a basis for the application of Chinese word segmentation, chunk analysis, named entity recognition, etc. Based on ambiguity in boundary recognition of Chinese punctuation marks, this paper proposes grammar testing methods for boundary recognition of slight-pause marks and then calculates the annotation consistency of these methods. The statistical results show that grammar testing methods can greatly improve the annotation consistency of slight-pause marks boundary recognition. The consistency during the second time is 0.030 3 higher than during the first, which will help guarantee the consistency of large-scale corpus annotation and improve the quality of corpus annotation.