The Research Of The Net Primary Productivity And Its Response Of Climate Change In Tibet

Tibetan, a part of Qing-Tibet plateau, is not only a sensitive area to global climatechange, but also the water-headers of the major rivers in China and even in Asia. Netprimary production (NPP) is the net amount of carbon captured by land plants throughphotosynthesis. NPP is an important part in the nutrient cycling and energy flow in theterrestrial ecosystem. It is a vital indicator to the ecosystem health and a scientific hotin the field on global climate change. To simulation and predict the past and future NPPis a important approach to understand the spatial and temporal pattern of vegetationfunction and its change mechanism for the interaction between ecosystem and climatesystem and take measures to avoid the possible negative influences.GLOPEM-CEVSA, which combined the remote sensing-based GLObalProduction Efficiency Model (GLOPEM) and the ecosystem process-based model, theCarbon Exchange between Vegetation, Soil and Atmosphere model (CEVSA), wasapplied to estimate the NPP of plant in Tibet from2000to2012this study. The maininputs include the meteorological spatial data interpolated and the Fraction of AbsorbedPhotosynthetically Active radiation (FPAR) from the land product (MOD15A2) ofModerate Resolution Imaging Spectroradiometer (MODIS). The estimated NPP wasanalyzed to explore its spatial and temporal pattern as well as the influences fromprecipitation and temperature on regional scale. The results were summered as thefollows.The model was evaluated its performance to estimate the NPP of grasslandthrough the comparison between the modeled NPP and the sampled above-groundbiomass (AGB). The linear regression showed that the model can well capture thevariability of AGB with a multiple correlation coefficient (R2) of0.86(the significantlevel p <0.001and the sample number n=43).The average NPP of vegetation in Tibet from2000to2012is115.43gCm-2a-1andits spatial distribution is characterized as a decreasing trend from southeast to northwest.Among the ecosystem types, forest showed the highest NPP (452.38gCm-2a-1) andfollowed farmland (290.82gCm-2a-1), wetlands (181.41gCm-2a-1), grassland (81.88gCm-2a-1) in a descending order and the lowest is desert (60.37gCm-2a-1).However, its variability in the13years was different, which was showed from thecoefficient of variance (CV) of each ecosystem. The crop had the highest variability(28.12%) and was almost same with grassland (28.02%), followed by desert (25.61%),wetlands (20.38%) and forest (15.67%).The change trend of NPP in the13years showed the spatial pattern that increasedby a speed of0.15~0.82gCm-2per10years in the eastern area of Shannan andNyingchi and Chamdo. while it was a decreasing trend with a0.15~0.82gCm-2per10 years in the Midwest, Ali, Nagqu, Xigaze and Lhasa area.From the spatial pattern of view, Ngari in west Tibet has experienced warm andhumid climate trend, but a small amount of precipitation increases dramatically failedto ease the drought in the region, the NPP decline. Northern Qiangtang plateau climatewarming and drying trend, resulting in a decrease in the area of vegetation NPP.Qamdo Northeast experienced a warming and drying climate trend, but the trend ofvegetation NPP is more complicated, mainly due to the region is located in the humidand semi-humid climate, abundant rainfall, the NPP can contribute to global warmingincreases, but at the same due to human activities, such as enhanced externalinterference, the NPP decreased in most areas.The precipitation use efficient, a key to understanding the coupling betweenecosystem carbon and water cycles, was calculated as the ratio of NPP to the annualsum of precipitation. PUE varies in different vegetation types with an order of thebroad-leaved forest, cultivated vegetation, coniferous forest, bushes, meadow, alpinevegetation, desert and prairie.Tibetan Plateau is a sensitive area to climate change and an ecological vulnerableregion. This study analyzed the spatial and temporal pattern of NPP and its mechanismcontrolled by climate. However, we did not consider the influence from humanactivities that would be more serious and urgent under global climate change for thisvulnerable area and should be paid close attention to in future. This research provided afundament of data and knowledge to quantify the influence from global climate changeand human activities for relative researches in future.