Study On Growth Dynamics Of Abies Fabri Forest On The North And South Slopes Of Taibai Mountains Based On Biome-BGC Model

Global warming has attracted the attention of all sectors of society,and gradually affects the balance and stability of ecosystems.Vegetation is the most sensitive group to climate change in terrestrial ecosystem.However,different vegetation and the same vegetation have different sensitivity to climate change at the same time in different areas.In order to better explore the growth dynamics,spatial variability and its response to climate change of Abies fabri on the northern and southern slopes of Taibai Mountains,this paper collects and collates the meteorological data from 1959 to 2013 in the Taibai Mountains area for 55 years,uses BiomeBCC model to simulate and calculate the output data,extracts and analyses the NPP,ET,LAI,NEP and carbon of Abies fabri forest on the northern and southern slopes of Taibai Mountains.Density and its correlation with climatic factors were analyzed.Then,using ARIMA model,R language and NAR dynamic neural network,the trend fitting and short-term prediction of NPP dynamic change of Abies fabri forest on the southern slope of Taibai Mountain were carried out,and the time series model of NPP of Abies fabri forest on the southern slope of Taibai Mountain was established.The predictive effects of the three models are confirmed by the white noise test and other related test methods.The main conclusions are as follows:(1)From 1959 to 2013,NPP,ET,NEP,LAI and carbon density fluctuated in varying degrees on the northern and southern slopes of the Taibai Mountains,but generally showed an upward trend.The growth of Abies fabri forests on the northern and southern slopes of Taibai Mountain is not synchronous.Under the combined effects of temperature,precipitation,topography,light and other factors,Abies fabri forests on the southern slopes grow faster than those on the northern slopes.NPP,ET,LAI,NEP and carbon density are higher than those on the northern slopes.(2)During 1959-2013,55 years,climate factors such as temperature and precipitation had an important impact on the development and succession of Abies fabri forest ecosystem on the northern and southern slopes of the Taibai Mountains,especially on the role of temperature.(3)Climate factors have different impacts on the ecosystem of Abies fabri forest on the northern and southern slopes of the Taibai Mountains.The Abies fabri forest ecosystem on the southern slope is less disturbed by climate,while the Abies fabri forest ecosystem growing on the northern slope of Taibai Mountain is more sensitive to climate change.(4)After simulating several sample sites in Qinling area,it can be found that NPP of Abies fasciata forest in Bashan began to increase with the increase of altitude,and tended to be stable after reaching a certain altitude,then declined again.The highest value is adjacent to 2800 meters.Slope-up also confirms the simulation results of Abies fabri forest ecosystem in Taibai Mountains,that is,the accumulation rate of NPP in Abies fabri forest on the southern slope is faster than that on the northern slope,and relatively less affected by climate.(5)NPP of Abies fabri forest on the southern slope of Taibai Mountains still keeps the trend of fluctuating and rising in a short period of time,and it is possible to reach the highest value since 1959.The three forecasting methods adopted in this paper have achieved good results in fitting effect and forecasting results,and a time series model suitable for fitting NPP dynamic changes of Abies fabri forest on the southern slope of Taibai Mountains has been established.(6)Prediction of future NPP changes in Abies fabri forests,each of the three prediction models has its own characteristics.For example,the ARIMA model has passed the white noise test on the NPP prediction results of Abies fabri forest on the southern slope of Taibai Mountains,and given the possible results under different confidence intervals.The NAR dynamic neural network model has a good fitting effect and has passed the test of error autocorrelation,and the prediction results better simulate the NPP of Abies fabri forest on the southern slope of Taibai Mountains.Trends in the future.After eliminating abnormal data points,R language can use basic data to simulate the dynamic changes of NPP of Abies fabri forest on the southern slope of Taibai Mountain.The results show that the correlation between the predicted results and the validated results is 0.944,and the P value of the error term is much lower than 0.01.