The Change Of Vegetation And Its Response To Climate Change In Qinling Bingjingding Mountain

Qinling mountain is the sensitive area of climate change,which is the boundary of our country’s climate, geography, vegetation and so on.But the north slope of Qinling mountains is near xi’an and other cities with population intensive, developed industrial and agricultural production.In recent years,climate warming and urban effect impacted notably on the vegetation in north slope of Qinling. The study of climate change impact on vegetation in this area are greatly influenced by human, to eliminate influence of human activities on the vegetation response to climate change. we selected high altitude mountain located in the north slope of Qinling and ice crystals and the nearby hill as an object, to study the response of vegetation of north slope of Qinling mountain to climate change under the background of global change.This report based on meteorological data from 1959 to 2013, the NDVI dataset from 2000 to 2010, four remote sensing image of 1981-2013 as the foundation, use the space interpolation, linear regression, supervised classification, correlation analysis and other methods, we analyzed the emporal and spatial variation of climate and vegetation located in ice crystals top and near region, and discussed high mountain areas especially timberline area response to climate change.The main research conclusions are as follows:(1) Annual mild season mean temperature in the study area was significantly upward trend in 55 years from 1959 to 2013, and the annual average temperature has a mutations in 1988.We acquire the spatial distribution of annual average temperature in the study area and it distribution from 1.3 to 12.0 ℃, which is closely related to the elevation, the annual average temperature is lower than 5 ℃ above the altitude of 2300 m. Annual average temperature and mean temperature are on the rise in all areas of study area in 55 years from the point of space changes. The area ratio of annual average temperature which has a increase was 71.6%, and annual average temperature of high altitude area rise faster and significantlythe.The spatial variation of season mean temperature has changed remarkably in 55 years.Annual average temperature in the study area has a significant growth in 55 years and has a mutation in 1988.The temperature rise rate after mutation is significantly greater than before. The winter temperatures mutation is the earliest among four seaaons. And the winter warming rate declines after the mutation.Recent studies have shown that the mean annual temperature in Bingjingding have a higher rising rate than Qinling, but lower than taibai mountain.While it is close to north slope of qingling mountain.But the annual average temperature mutation is eralier than qingling mountain’s 1993 and taibai mountain’s 1997.Be different from that it has a falling trend before temperature mutation in Qinling mountain, it has a rising trend before and after tamperature mutation in Bingjingding. It has a obviously rising after mutation.When compared with that of north slope of qingling mountain, Season mean temperature has a riding trend, such as spring, autumn and winter. But it has a slightly different in rate.Otherwise, it has an opposite tendency in summer. It has a rising trend in Bingjingding, while it is falling in the north slope.(2) Under the background of global warming,11 years of the study area forest line shifts, significantly higher annual average NDVI.Remote sensing analysis shows that warming great influence on the distribution of vegetation types, mainly for the forest line shift.The study area belong to the vegetation cover a good area; altitude of 2000m below the seasons are good vegetation cover (NDVI> 0.5). With the slowdown in the process of increasing altitude NDVI distribution is closely related to altitude, NDVI with elevation and then decreased, and the increase in. In the 2000m at the maximum NDVI, NDVI decrease the turning point at an altitude of about 2400m.There was a significant increase in annual average NDVI trends, including high altitude NDVI trend was not significantly increased. Season both NDVI was not significant upward trend in winter NDVI increased rapidly. Most spring vegetation reduction, mainly in the low-altitude areas and frequent human activity central high altitudes. Summer, fall, winter and increasing vegetation in most areas. Seasons in the high altitude zone of vegetation increases and decreases are more obvious.With increasing altitude, Bingjingding region NDVI no significant change occurred after the proportion of the area first and then decreased, low altitude and high altitude change regional NDVI was not significant, the 1500-2000m altitude gradient, vegetation is more sensitive to changes. Altitude of more than 1000, with sea level rise in the region NDVI increase the proportion increases, indicating a higher altitude within the range of 11 years to have more regional NDVI increased, but the change did not reach significant levels.(3) NDVI and temperature in the month of the study area is most closely correlated, both the response lag is not obvious.NDVI correlation between the study area and the temperature of the month, with a maximum temperature coefficient of the month, especially in April and May NDVI showed a significant correlation between the temperature of the month; NDVI response to temperature lag is not obvious, only 3 May and August reflected. Low temperatures and NDVI altitudes mostly negative correlation, mostly high-altitude areas are related.(4) Timberline area for 11 years regardless of the rate of temperature rise or NDVI sensitivity to temperature changes are higher than the entire study area, as temperatures rise timberline position shift.Timberline area in 11 years the average annual temperature, mean temperature and annual average NDVI quarter showed no significant upward trend. Average annual rate of temperature rise speed 0.432 ℃/10a, compared to the entire study area, forest zone temperatures rose faster line; but the average annual NDVI increased rate (0.15%) lower than the forest line area (0.22%).Compared to the entire study area, forest line area NDVI response to temperature change is more sensitive, generally higher correlation coefficient. NDVI and temperature of the month is most closely correlated, February, April, May reached a significant correlation. Timberline zone NDVI and temperature correlations mainly as a positive correlation, but in most parts of the correlation was not significant. NDVI and air temperature was a significant positive correlation between the region and mainly in the higher elevations of the northern slope of ice near the top of the region.32 years ago in response to climate warming timberline zone is mainly manifested in two aspects timberline vegetation type changes and increased forest line position. Timberline area surrounded by forest area decreased, the study area is higher than the southern slope of the northern slope of the timberline position, the three sample areas are respectively the timberline elevation 5.6m,96.2m,37.0m, with elevation forests line the magnitude of the rise was downward trend.