| Qinling Mountains are important geographic demarcation line between China's North and South, transition regions from the subtropical zone to the warm-temperate zone and sensitive areas to global climate change. Foping Nature Reserve in the middle of the southern slope of Qinling Mountains is the object of this study. Based on the observation data of the 31 meteorological stations in Qinling Mountains from 1959 to 2013, the NDVI data sets from 2000 to 2013, and remote sensing images including Landsat4-5TM in 1983 and Landsat 8 in 2013, the impacts of temperature and precipitation on different kinds of vegetation were researched via the method of special analysis in the Nature Reserve to explore the rules and regional differences of the response of terrestrial vegetation ecosystems to climate change.The results of this study are as follows:(1)The annual, seasonal, January and July average temperatures showed an upward tendency in Foping Nature Reserve from 1959 to 2013,and the area about 70% was increased significantly.In 55years, the annual averaged temperature in Foping Nature Reserve showed a rising trend with a rate of 0.21 degrees/10a. The annual average temperature in the Nature Reserve showed an obvious mutation in 2002, which is later than that of Qinling Mountains in 1993. The warming change rate at 0.46 degrees/10a was significantly higher after the mutation than that at 0.08 degrees/10a before. From the perspective of spatial analysis,in the study area, there was a significant increase about 75.09%, and the change rate of the annual average temperature was the increasing from the southwest to the northeast.In 55 years, the temperature of every season in this study area showed a rising trend. From Spring, summer, autumn to winter, the temperature change rates were 0.29 degrees/10a, 0.09 degrees/10a,0.61 degrees/10a, and 0.46 degrees/10a in turn. The mutation point of temperature in spring was in 1998, which was consistent with Qinling Mountains. The summer temperature mutation was in 2013,later than that of Qinling Mountains.The autumn temperature mutation was in 1971, earlier than that of Qinling Mountains. But the temperature in winter had no mutation point. By spatial analysis, we found that the ratio of the area where temperature increased significantly in spring, summer, autumn and winter were 67.19%,70.40%,69.43% and 71.85%, respectively. The temperature change rate in spring presented an increasing from the southeast to the northwest, while the temperature change rate in summer, autumn and winter showed the opposite trend.In 55 years, the temperature change rates in the coldest month Janury and the hottest month July in the study area were 0.32 degrees/10a and 0.41 degrees/10a, higher than that of the annual average temperature change rate at 0.21 degrees/10a. In January and July, the mutation points were in 1966 and 1991, respectively, which was earlier than that of annual temperature in this study area in 2002. About 66.56% regions in January average temperature was significantly increasing, and the temperature variation slope showed a rise from the northwest to the southeast. But about 72.95% in July was significantly increased, and the variation slope showed an increasing from the west to the east.(2) The annual total precipitation showed an increasing trend in Foping Nature Reserve from 1959 to 2013. The annual and seasonal precipitation had multiple mutation points.In 55 years, annual precipitation in this study area increased with a rate 13.06 mm/10a, and there were more than one mutation point. The precipitation increased at a rate of 12.97mm/10a and 0.43mm/10a in summer and winter, while the precipitation decreased at the radio of-4.53 mm/10a and -5.85 mm/10a in spring and autumn respectively. The seasonal precipitation had multiple mutation points, maybe because of the randomization of precipitation.(3)The vegetation coverage increased in Foping Nature Reserve from 1983 to 2013. That manifested the increase of the area of broad-leaved forest, coniferous broad-leaved forest and coniferous forest, and the NDVI in the whole study area and above coniferous forest area.From the vegetation types, the area of broad-leaved forest, coniferous broad-leaved forest and coniferous forest increased in 30 years,and the area of the shrub, meadow and bare rock reduced.The NDVI of in this study area showed an upward trend during 2000 to 2013 with a rate of 0.007/10a. And the NDVI in every season also showed an upward trend,which change rates were 0.003/10a,0.002/10a, and 0.004/10a respectively. The ratio of the area where the NDVI significantly increased were 42.84%,41.16%,52.49% and 61.79% in different seasons,respectively. The NDVI also showed a rising trend in the every month of growth season.The annual NDVI of coniferous forest and its above region in 14 years showed an upward trend,and change rates were 0.008/10a and 0.01/10a respectively. And the ratio of the area where NDVI significantly increased were 44.90% and 47.07% respectively in the coniferous and its above region.The NDVI of different seasons also showed an upward trend.The ratio of the area where NDVI significantly increased in the coniferous forest were 48.63%,38.23%,38.22% and 46.14% respectively in different seasons. And that were 50.00%,72.16%,63.68% and 50.66% in the coniferous above area.(4)The study area or the coniferous and the area above it, the NDVI in May and temperature in April was significantly positively correlated, while the NDVI in April and precipitation in April was significantly negatively correlated.In 14 years, NDVI in April and temperature in April, the NDVI in May and temperature in April showed significantly positive correlation. On the seasonal scale, the NDVI was only significantly positively correlated with temperature in winter. The NDVI in April and precipitation in April showed significantly negatively correlation.In the research of the correlation between NDVI and temperature in coniferous forest and its above area, the NDVI in May and temperature in April presented significantly positive crenelation. And the NDVI in September and temperature in September and NDVI and temperature in winter were also significantly positively correlated. The correlation between NDVI and precipitationand the NDVI and precipitation in April was significantly negative in coniferous forest and its above area. And the NDVI in May and precipitation in April also showed a significantly negative correlation above the coniferous area. |
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