Dynamics of Pteroceltis tatarinowii Population in Langya Mountain of Anhui Province

Based on the theories of population life table and survival analysis, a static life table and curves of the survival rate, mortality rate and vanishing rate as well as survival function curve, of Pteroceltis tatarinowii population in the Langya Mountain of Anhui Province were worked out for analysis of quantitative characteristics of the population using the diameter at breast height(DBH) classification method and the section smoothing technique.Further on for analysis of dynamics of the population quantity using the method of quantification of population dynamics and the time series prediction model were used. Results show that 1) the population of Pteroceltis tatarinowii in the Langya Mountain is of the type of steady growth. The structure of DBH class of the population appeared roughly in the shape of an invert “J”; trees middle and young in age were relatively high in number, but those old in age relatively low. Although the population may be subject to certain fluctuation during its development process, the two dynamic indexes of V_p,i and V_p,i' (taking into account the external interference) of the population quantity were both higher than zero. 2) The curves of the mortality rate and the vanishing rate of the population varied in a similar trend, each with two peaks popping up at the 2^nd age class and the other at the 11^th or 12^th. Statistic test shows that the survival rate curve tends to be of the type of Deevey-Ⅱ. 3) The survival rate of the population decreased monotonically, while the cumulative mortality rate increased in the same manner. The falling trend of the survival rate was more apparent in the early stage than in the late stage, whereas that of the cumulative mortality rate was just the reverse. The survival functional curve shows that the Pteroceltis tatarinowii population is characterized by weakness in the early age period, stableness in the middle age period, but decline in the old age period. 4) The time sequence model predicts that young individuals would be relatively abundant, and the population will show a trend of steady growth in the next 2, 4, 6, 8 and 10 years.