Climate Change Analysis Based On Tree-ring Data In Saihanwula

The article research region in Saihanwula national nature reserve, and take Meyer spruce as the investigative object, combined with meteorological data Balinyouqi Meteorological Bureau, analyzed the the relationship between Meyer spruce rings and climate change. The research results are as follows:(1)Core white stick tree species in two sampling points established chronology, found two plots longest table just under a year, Erlinba (ELB) was83years, Zhengou (ZG) is84years. The average sequences correlation coefficient is0.597, the average sensitivity is0.27, the average correlation coefficient between trees is0.380. This indicates that the chronology includes a large amount of information of environment change, therefore, tree-ring analysis of the climate of the region is suitable.(2) By Saihanwula protected area two sampling point analysis, The signal to noise ratio of chronology in positive groove (ZG) is19.74, Erlin dam (ELB) is20.52, and the more environmental information was contained in the large signal to noise ratio, so the information of climate between two sample points is relatively similar. The Sample Population representativeness of Meyer spruce ring width both in0.9, and exceeded the acceptable level of85%.So, The trend of changes was consistent in both groups, and the totalClimate limiting factors with Similarity.(3) Ring chronologies based on correlation analysis between climatic factors and the corresponding results:white stick in the ring width chronology and in October last year to April this year the average temperature was significantly negatively correlated, with in May the average temperature was a positive correlation, but with in from July to September the average temperature was a significant positive correlation; The rainfall in November last year and January and September of the year was significantly negatively correlated, but with in Aprilwas a significant positive correlation; The average minimum temperature in December last year and January, February, April, June, July and September that year was significantly negatively correlated; The humidity index in November last year and January and September of the year was significantly negatively correlated, but with in April was a significant positive correlation; The mean maximum temperature in April, June of the year was significantly negatively correlated; Description, trees growing radial Saihanwula protected areas simultaneously affected by temperature and precipitation.icant. which the rainfall is weak.