A Novel Method for Calculating Stand Structural Diversity Based on the Relationship of Adjacent Trees

Understanding the diversity and complexity of stand structure is important for managing the biodiversity of forest ecosystem, and stand structural diversity is essential for evaluating forest management activities. Based on the relationship of adjacent trees, a quantitative method of stand structure diversity is proposed to express the heterogeneity of stand structure in tree species, distribution pattern, species separation and size differentiation. In this study, we defined the diversity of structural unit types and derived a new index of forest structural diversity (SD ') employing the additivity principle of the Shannon-Weiner index. The efficiency of the index was verified by applying the new measure to sixteen field survey samples at different locations. The mountain rainforest in Hainan had the highest forest structural diversity, followed by broad-leaved Korean pine forests in Jiaohe (2), Jiaohe (1) and an oak-broadleaved mixed natural forest at Xiaolongshan (2). The SD ' values of plantations and pure natural forest were lower. The simulated data of different thinning methods and the intensity of broad-leaved Korean pine forests show that the new measure can reflect forest management changes on stand structure diversity. The value of SD ' compared with no treatments and the differences were greater as thinning intensity increased. The SD ' index provides minimum and maximum values for different structural unit types in forests to achieve a unified comparative basis for calculating forest structure diversity. It has the characteristics of the general diversity index and can well express the diversity of tree species, distribution pattern and size differentiation simultaneously. The SD ' index can not only calculate the structural diversity of mixed species forests but can also be used to calculate the structural diversity of pure forests. It can also be used to evaluate the change in stand structure diversity after management interventions.