| As an important geographical dividing line of China, Qinling Mountains, located in warm temperate and subtropical transition zone, is a sensitive area of climate change. The paper selected the mid-high altitude region (from Niubeiliang regions to Bald Mountain of Qinling Feng yukou) which located in the center of Qinling with good vegetation protection as the study area. The author studied the temporal-spatial change of climate and vegetation index, the response characteristics of vegetation NDVI to temperature and precipitation in this area, using the GIS spatial analysis technology, based on the meteorological data from 1975 to 2013 and the MODIS NDVI data from 2000 to 2013. Its purpose is to study quantitatively the change law of climate and vegetation in the mid-high altitude region in Qinling, and explored the mechanism about theresponse of vegetation to climate under the background of global climate change, thus providing the basis for the region's ecological construction and management. The research results and progress are as follows:(1) From 1975 to 2013, the annual average temperature showed a significant rise trend and warm mutated was occurred in 1994; the annual precipitation presented cyclical fluctuations, which had multiple mutations. And spring climate had obvious warm and dry trend.In recent 40 years, the annual average temperature rised significantly, as a trend rate of 0.335?/10 a, and mutated in 1994, the primary cycle of annual average temperature variation is 6a.On the seasonal scale, the average temperature of spring, summer and winter, showed a significant upward trend,the change rate was 1.19?/10a?1.43?/10a?0.62?/10a respectively, significantly higher than the rate of warming Qinling region; the temperature in Autumn was no significant rising as a trend rate of 0.09?/10a. In addition to autumn, the mutations of other season average temperature occurred between 1997 and 1999.Annual precipitation was not significantly increased (3.98mm/10a), and mutated from less to more occurred in 1979 and 2002, mutated from more to less in 1990,2011 and 2012. The primary cycle of annual precipitation variation is 7a from 1975 to 2013. On the seasonal scale, the total precipitation of spring and autumn showed a insignificant decreasing (spring at-1.18mm/10a, autumn at -2.16mm/10a) trend. The total precipitation of summer and winter showed a non-significant increase (summer at 3.67mm/10a, winter at 0.84mm/10a), and seasonal rainfall had mutations along recent 40 years.(2) From 2000 to 2013, the NDVI in the study area showed a trend of slight degradation with remarkable regional differences.For 14 years, the average annual NDVI change kept stability essentially, and showed an extremely slow decrease trend. The average NDVI change trends of four seasons were not significant, and in Spring, Summer and Autumn, NDVI presented a slow downward trend. Spatial analysis showed that the area which vegetation had slight degradation (Lslope<-0.002/ a) accounts for 48.02% in the study area at the year scale. And in the seasonal scale, the vegetation of spring, summer and autumn are main in slight degradation trends, and the degraded area ratio was 63.97%(spring),59.97%(summer),44.4%(autumn);While winter vegetation degraded areas and increase regional the area was essentially flat.(3) In the study area, the average annual NDVI was positively correlated with air temperature. In spring and winter, NDVI was significant positively correlated with air temperature, but which was not significant negative correlation in autumn. NDVI in May is the most sensitive to temperature reaction.For 14 years, the average annual NDVI was positively correlated with air temperature up to 96.12% of the pixels, to achieve a significant positive correlation (P<0.05) as pixels accounted for 16.71% of the study area. NDVI in Spring and winter with air temperature was significant positive correlation pixels 98.44% and 81.12% respectively, which was significant accounted for 18.36% and 21.20%; The negative correlation between NDVI of Autumn and the air temperature was enhanced, the negative correlation pixels were accounted for 77.49% of the study region, but achieve significant less than 3%; However, the correlation between summer air temperatures and NDVI is not obvious. Vegetation NDVI response degree from different months differs from each other to air temperature. Especially, vegetation of May is most sensitive to air temperature, which was positively related pixels accounted for 94.67%, significant ones accounted for 52.15%, and vegetation of mid-high altitude areas is more sensitive than vegetation from the low altitude in response to the air temperature.(4) The vegetation NDVI in high altitude area is mainly positively affected by air temperature which is also negatively affected by precipitation, meanwhile, the most significant factor that influence the meadow is air temperature.For 14 years, different kinds of vegetation's NDVI of growing season in addition to meadow was rising outside, while shrubs, coniferous forests and mixed broadleaf-conifer forest were declining slowly. Different kinds vegetation's NDVI of growing season was positively correlated with the air temperature, but only correlation between meadow's growing season NDVI and the air temperature reached significant level; The correlation between different kinds vegetation's NDVI of growing season and precipitation was negative and weak.The average annual NDVI and the air temperature were mainly positively correlated, and with the rise of temperature, the correlation slowly decreased; and the correlation between the average annual NDVI and precipitation had obvious north-south aspect differences spatially, positively correlated pixels were mainly distributed in the North Slope, while the negative correlation pixels concentrated in the southern slope. And with the increasing precipitation, the negative effects of annual average NDVI and precipitation was significantly enhanced, when the rainfall is more than 750 mm, the number of negative correlation pixels had increased obviously.(5)In addition to the temperature of the same period, different types of vegetation have been influenced by the accumulated temperature. The accumulated temperature has an significant positive effect on NDVI in spring, but it has a negative impact on NDVI on July.Most positive correlation has been found between various types of vegetation's monthly NDVI and contemporary temperature, especially for that of May when the correlation reached extreme significant level.In March and April at the beginning of the growing season, vegetation growth was affect by the temperature in January and February and early spring, which has the greatest impact on the meadow. In May, different kinds of vegetation's NDVI had positive correlation with the accumulation temperature from March to May. While shrub, coniferous and mixed coniferous forest were affected by the weakening of the early accumulation temperature, except for meadow in June. At July during the promising growth, different kinds of vegetation's NDVI had negative correlation with the accumulation temperature from April to June, which is significant for mixed coniferous forest and coniferous. At the end of growing season (October), the increasing of cumulative temperature will have the negative influence on different types of vegetation, and the negative effect increased from the meadow, shrub, coniferous and mixed coniferous forest in turn. |
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